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Case, Shane. « Remora aggressive power management for Apache HTTPD web server / ». Diss., Online access via UMI:, 2009.
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Huo, Weikun, et Lihua Liu. « Embedded web server remote control and communication ». Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-19035.
Texte intégralRésumé :
This is a embedded system that designed to achieve the goal of remote control andwireless communication with web page. The embedded web server using uIP whichis TCP/IP stack. Web page are designed using HTML5, JavaScript and CSS languageto format the layout. On the home page, you can see the index of different items.
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Figueiredo, Gleyce Kelly Dantas Araújo 1984. « Determinação e mapeamento de inicio do ciclo para culturas de verão no estado do Parana por meio de imagens de satelite e dados de precipitação ». [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256952.
Texte intégralRésumé :
Orientadores: Jansle Vieira Rocha, Rubens Augusto Camargo LamparelliDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
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Resumo: A agricultura está fortemente ligada às condições meteorológicas, tornando-se uma atividade de risco. Sendo assim, um sistema de monitoramento e previsão de safras é necessário para evitar grandes perdas. O monitoramento agrícola, aliado a estudos de varibilidade meteorológica, é de extrema importância, pois determina a melhor época em que deve ocorrer a semeadura, bem como os períodos de maior necessidade hídrica da planta. A utilização do sensoriamento remoto para monitoramento agrícola e sua associação a dados meteorológicos viabilizam o monitoramento de culturas, desde o plantio até a colheita. Desta forma, o objetivo deste trabalho foi mapear culturas de verão (soja e milho) no estado do Paraná por meio de composições decendiais NDVI de imagens do satélite SPOT Vegetation nas safras 2005/2006, 2006/2007 e 2007/2008, e associar a dados de precipitação para determinar e mapear épocas de semeadura. Para isso, foi utilizado o método de classificação digital supervisionada em composições multitemporais das imagens, de forma a gerar máscaras da cultura da soja para cada composição decendial. A verificação da acurácia das máscaras foi realizada utilizando o índice Kappa alcançando valores de 0,70, 0,75 e 0,77, Exatidão Global 0,91, 0,91 e 0,93 e Índice de concordância de Willmot (d) entre 0,93, 0,93 e 0,99. Os perfis temporais de NDVI possibilitaram a detecção do início do ciclo vegetativo das culturas. Foram utilizados dados de precipitação da rede de estações meteorológicas do SIMEPAR e do modelo atmosférico ECMWF. Os dados das estações meteorológicas foram compilados a partir de dados diários a dados decendiais, tendo em vista que as informações do modelo são decendiais. Em seguida foi necessário especializá-las e reamostrá-las para um grid de 1 km x 1 km. Essas duas informações foram interpoladas através do Inverso Quadrado da Distância a fim de obter o perfil de precipitação da região estudada durante a safra de verão. A interpolação de dados de precipitação mostrou-se expressiva, uma vez que os valores interpolados e os valores reais foram significativos quando avaliado pelo índice de concordância 'd' de Willmot, variando entre 0,74 a 0,99. Para as três safras em estudo, apenas o comportamento da última foi distinta das demais, onde foi possível detectar atraso da chuva de um mês em relação às outras safras. Com a espacialização da precipitação dentro do estado foi possível fazer o cruzamento entre as máscaras da cultura de verão e os mapas de precipitação decendial, de modo a descobrir o inicio do desenvolvimento do ciclo da cultura. Desta forma foi possível perceber que houve um retardamento no início do ciclo da cultura para regiões em que a semeadura ocorreu antes do período mais chuvoso. A associação entre o perfil temporal de NDVI e precipitação permitiu identificar e mapear diferenças entre épocas de início de ciclo dentro do estado do Paraná
Abstract: Agriculture is highly dependent on meteorological conditions, making it a risky activity, so, in order to avoid large losses, it is necessary to devlop an appropriate crop yield forecasting system. Agricultural monitoring coupled with studies of weather variability is extremely important to determine the best time to sown as well as periods of higher water requirement by the plants. The use of remote sensing for agricultural monitoring in addition to meteorological data enables crop monitoring from planting to harvest. Thus, the goal of this study was to map summer crops in the state of Parana through dekadal composition of SPOT Vegetation NDVI imagery for the 2005/2006, 2006/2007 and 2007/2008 cropping seasons. Supervised classification of multitemporal image composites was used to generate cropland masks for each dekad. Accuracy assessment was performed using Kappa Index reaching values of 0.70, 0.75 and 0.77 and overall accuracy 0.91, 0.91 and 0.93. NDVI temporal profiles were used to detect the beginning of the crop vegetative cycles. Rainfall data from SIMEPAR network of meteorological ground stations and ECMWF atmospheric model were used. The data from the ground stations were compiled from daily to dekadal in order to comply with model data, which is a ten days compilation . Then it was necessary to spatialize and resample them to a 1 km x 1 km grid. These two data were interpolated using the inverse distance to square method to extract the profile of precipitation in the region during the summer harvesting season. The interpolation of rainfall generated good results, once the interpolated values as copared to actual values were significant when evaluated by the agreement index 'd' of Willmot, ranging between 0.74 to 0.99. For the three cropping seasons studied only the behavior of last season was distinct from the others , it was possible to detect a rain delay of one month in relation to other seasons. With the rainfall spacialization within the state it was possible to cross the masks of the summer crops with the maps of the decadal rainfall, in order to discover the beginning of the crop vegetative cycle. So it was possible to see that there was a delay at the beginning of the crop cycle in areas where the sowing occurred before the rainy season. The association between NDVI temporal profile and rainfall allowed to identify and to map the differences among starting of the crop vegetative cycle in the state of Parana
Mestrado
Planejamento e Desenvolvimento Rural Sustentável
Mestre em Engenharia Agrícola
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Gu, Yan. « ROSENET : a remote server-based network emulation system ». Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22662.
Texte intégralRésumé :
Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2008.Committee Chair: Fujimoto, Richard; Committee Member: Ammar, Mostafa; Committee Member: Bader, David; Committee Member: Goldsman, David; Committee Member: Park, Haesun; Committee Member: Riley, George.
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Brabec, František. « Optimizing client-server communication for remote spatial database access ». College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/3087.
Texte intégralRésumé :
Thesis (Ph. D.) -- University of Maryland, College Park, 2005.Thesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Maluleke, Enock Vongani. « Satellite-based web server ». Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/53040.
Texte intégralRésumé :
Thesis (MScEng)--Stellenbosch University, 2002.ENGLISH ABSTRACT: There is a large variety of telemetry recervmg software currently available for the reception of telemetry information from different satellites. Most of the software used in receiving telemetry data is satellite specific. Hence, a user-friendly way is needed to make telemetry data easily accessible. A satellite-based web server is aimed at providing telemetry information to any standard web browser as a way of bringing space technology awareness to the people. Two different satellite-based web server methods are examined in this thesis. Based on the evaluation, the on-board File server with proxy server was proposed for satellite-based web server development. This requires that the File server be ported to the on-board computer of the satellite. The web proxy server is placed on the ground segment with the necessary communication requirements to communicate with the on-board File server. In the absence of satellite, the satellite-based web server was successfully implemented on two computers, laying a good foundation for implementation on the on-board computer of the satellite (OBe).
AFRIKAANSE OPSOMMING: Daar is 'n groot verskeidenheid telemetrie ontvangs sagteware huidiglik beskikbaar vir die ontvangs van telemetrie informasie vanaf verskillende satelliete. Die meeste van die sagteware wat gebruik word om telemetrie data te ontvang is satelliet spesifiek. Gevolglik, 'n gebruikers vriendelike metode is nodig om telemetrie data maklik beskikbaar te maak. 'n Satelliet-gebaseerde web-bediener word beoog om telemetrie informasie te verskaf aan enige standaard web-blaaier as 'n metode om mense bewus te maak van ruimte tegnologie. Twee verskillende satelliet gebaseerde web-bediener metodes salondersoek word in hierdie tesis. Gebaseer op 'n evaluering, word die aanboord leêr-bediener met instaanbediener voorgestel vir satelliet-gebaseerde webbediener ontwikkeling. Hiervoor is dit nodig dat die leêr-bediener na die aanboord rekenaar van die satelliet gepoort word. Die web instaanbediener word op die grond segment geplaas met die nodige kommunikasie benodighede, om te kommunikeer met die aanboord leêr-bediener. In die afwesigheid van die satelliet was die satellietgebaseerde web-bediener met sukses geïmplementeer op twee rekenaars, met die gevolg dat 'n goeie fondasie gelê is vir die implementering op die aanboord rekenaar van die satelliet (OBC).
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Fernandes, Jeferson Lobato. « Monitoramento da cultura de cana-de-açucar no Estado de São Paulo por meio de imagens spot vegetation e dados meteorologicos ». [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256961.
Texte intégralRésumé :
Orientadores: Jansle Vieira Rocha, Rubens Augusto Camargo LamparelliDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
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Resumo: O atual sistema de previsão de safras para a cultura da cana-de-açúcar utilizado no Brasil depende, em boa parte, de informações subjetivas, baseadas no conhecimento de técnicos do setor e informações da cadeia produtiva. Apesar da experiência dos técnicos envolvidos, este sistema está sujeito a questionamentos sobre a qualidade dos números apresentados e abre margem a ações especulativas por parte de agentes externos. O monitoramento da cultura de cana-de-açúcar por meio de séries multitemporais de índices NDVI do sensor SPOT Vegetation, associado a dados meteorológicos provenientes do modelo do ECMWF, viabiliza o acompanhamento do desenvolvimento da cultura e sua correlação com a produtividade, diminuindo assim a subjetividade das estimativas. Este trabalho avaliou o potencial de uso de imagens decendiais do sensor SPOT Vegetation para a identificação de áreas canavieiras do estado de São Paulo e a capacidade de inferir sobre os dados de produtividade oficiais registrados em municípios e safras previamente selecionados, baseando-se em dados provenientes dos perfis temporais do NDVI - SPOT Vegetation e de variáveis meteorológicas do modelo do ECMWF. Foram selecionados 20 municípios do estado de São Paulo e sete safras compreendidas entre o período de 1999 e 2006. A identificação das áreas canavieiras foi realizada por meio do perfil temporal do NDVI de cada pixel, onde foram selecionados os pixels que ao longo da safra apresentaram comportamento característico da cultura. Para a determinação da produtividade média da safra por meio de dados espectrais e meteorológicos, foram extraídos valores dos perfis temporais do NDVI e das variáveis meteorológicas temperatura mínima, temperatura média, temperatura máxima, precipitação e radiação global, onde, utilizando-se técnicas de mineração de dados, separou-se a produtividade média da safra em 3 classes, baixo-média, média e média-alta. Os resultados de identificação de áreas canavieiras no estado de São Paulo foram avaliados em escala estadual e municipal. Para a escala estadual, o método proposto apresentou resultados satisfatórios. Os índices de determinação (R²), obtidos através da correlação entre a área colhida de cana-de-açúcar oficial e a estimada, por município e safra, considerando os 637 municípios do Estado, variaram entre 0,771 e 0,829. Para a escala municipal não foi possível determinar com exatidão a área de cana-de-açúcar colhida de cada município devido à baixa resolução espacial das imagens. Para o método de classificação da produtividade média municipal proposto, houve maior correlação com os dados os dados espectrais que com os dados meteorológicos. Valores extraídos do perfil temporal do NDVI entre os meses de dezembro e janeiro permitiram classificar a tendência do resultado de produtividade alcançado no final da safra. Os resultados foram mais efetivos para os casos onde a produtividade foi classificada como sendo média ou acima da média, com acertos de 86,5 e 66,7% respectivamente. Existe potencial no uso de imagens de NDVI do SPOT Vegetation para a identificação de áreas canavieiras em escala estadual e para a classificação da produtividade média municipal da safra.
Abstract: The current crop yield forecasting system for sugar cane used in Brazil is dependent on subjective information which are based on personal knowledge of technicians and information from the industry. Despite the experience of technicians, this system is vulnerable once it allows questioning about the quality of the figures presented, what could lead to speculation by market agents. Sugar cane monitoring through multitemporal series of the NDVI data from SPOT Vegetation, associated with meteorological data from the ECMWF model, provides information about the plant development and its correlation with yield, contributing to the decrease in the subjectivity of the forecasts. This study evaluated the potential use of decadal images of the SPOT Vegetation sensor to identify sugar cane areas in São Paulo state and the feasibility to estimate the official productivity registered in municipalities and crops previously selected by the use of NDVI - SPOT Vegetation and ECMWF meteorological data. For this study 20 municipalities of São Paulo state and seven cropping seasons were selected between 1999 and 2006. To identify sugar cane areas the temporal profile of each pixel was analysed during the cropping season, selecting pixels that presented a characteristic temporal NDVI profile of sugar cane. To determine the average yield using spectral and meteorological data, values of the temporal profiles of NDVI and minimum, mean and maximum temperature, precipitation and global radiation were extracted. Through data mining techniques, the average yield was classified in three classes: low-mean, mean and mean-high. Results for the identification of sugar cane areas in São Paulo state were evaluated at regional and local scale. For the regional scale the proposed method showed good results. The R² for the correlation between official and estimated sugar cane planted area, considering the 637 municipalities of the state, varied between 0,771 and 0,829. For the local scale, it was not possible to determine the sugar cane area due to the low spatial resolution of the images. For the classification of the average crop yield, by proposed method, spectral data was more relevant than meteorological data. Some values extracted from the temporal profile of NDVI between December and January permitted to classify the yield tendency. Best results were found when the yield was classified as mean or mean-high, with 86,5 and 66,7 percent correctively classified, respectively. The results showed that there is potential for the use of NDVI - SPOT Vegetation images to identify sugar cane areas at regional scale and to classify the average crop yield.
Mestrado
Planejamento e Desenvolvimento Rural Sustentável
Mestre em Engenharia Agrícola
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Tesař, Jan. « Web server s mikroprocesorem ARM ». Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-219962.
Texte intégralRésumé :
Diploma thesis is dealing with design and implementation of the web server and manage- ment website in the developing kit FriendlyARM Mini6410 with installed OS GNU/Linux. The embedded packaging system PTXdist is described in terms of Kernel configuration and selection of suitable applications. The device should be later used for the remote management of atmospheric optical link.
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Tang, Chih-Yu. « A generic framework for the personal omni-remote controller using M2MI / ». Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/437.
Texte intégral
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Lundemo, Anna. « Detecting change points in remote sensing time series ». Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-212995.
Texte intégralRésumé :
We analyse methods for detecting change points in optical remote sensing lake drainage time series. Change points are points in a data set where the statistical properties of the data change. The data that we look at represent drained lakes in the Arctic hemisphere. It is generally noisy, with observations missing due to difficult weather conditions. We evaluate a partitioning algorithm, with five different approaches to model the data, based on least-squares regression and an assumption of normally distributed measurement errors. We also evaluate two computer programs called DBEST and TIMESAT and a MATLAB function called findchangepts(). We find that TIMESAT, DBEST and the MATLAB function are not relevant for our purposes. We also find that the partitioning algorithm that models the data as normally distributed around a piecewise constant function, is best suited for finding change points in our data.Vi analyserar metoder för att hitta brytpunkter i optisk fjärranalysdata som beskriver uttorkning av sjöar. Brytpunkter är punkter i en tidsserie vid vilka de statistiska egenskaperna förändras. Datan som vi använder representerar uttorkande sjöar i norra hemisfären. Den är generellt väldigt fluktuerande och många observationer kan saknas på grund av väderförhållandena i dessa områden. Vi undersöker en partitionsalgoritm, med fem olika sätt att modellera datan, baserade på minstakvadratmetoden och på antagande om att mätfelen är normalfördelade. Vi utvärderar också två program som heter DBEST och TIMESAT och en funktion i MATLAB som heter findchangepts(). Vi kommer fram till att TIMESAT, DBEST och MATLAB-funktionen inte är lämpliga för att analysera vår data. Vår slutsats är också att partitionsalgoritmen som modellerar datan som normalfördelad runt en styckvis konstant funktion bäst lämpar sig för att hitta brytpunkter i vår data.
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Naumann, Torsten. « Client-Server-Backup fuer dezentrale Filesysteme auf Basis von rse ». Thesis, Universitätsbibliothek Chemnitz, 1996. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-199600202.
Texte intégralRésumé :
Ziel der Arbeit war es, eine Client-Server-basierte Loesung zu
entwickeln, welche eine Backupfunktionalitaet in einer heterogenen
Workstationumgebung mit dezentralen Filesystemen bereitstellt.
Das System sollte mit Hilfe einer Scriptsprache implemetiert werden,
um die Systemunabhaengigkeit der Komponenten zu gewaehrleisten.
Zu diesem Zwecke wurde als Grundlage das ¨Remote Scripting Environment¨,
welches Gegenstand der Diplomarbeit von Andre Glaesz am Lehrstuhl
Betriebssysteme war, gewaehlt.
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Moraes, Rafael Aldighieri. « Monitoramento e estimativa da produção da cultura de cana-de-açúcar no estado de São Paulo por meio de dados espectrais e agrometeorológicos ». [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/256814.
Texte intégralRésumé :
Orientadores: Jansle Vieira Rocha, Rubens Augusto Camargo LamparelliTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola
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Resumo: O levantamento subjetivo para a estimativa da produção agrícola, baseado em entrevistas, ainda prevalece no Brasil, com consequencias em sua exatidão. Dada a sua importância para o planejamento de políticas públicas e preços de mercado, o monitoramento de áreas agrícolas e estimativas da produtividade com o uso de geotecnologias e dados espectrais e meteorológicos, pode contribuir significativamente para estimativas mais precisas e de menor custo. O estado de São Paulo é o maior produtor de etanol e açúcar de cana-de-açúcar do Brasil, assim, são de extrema importância a identificação de áreas de cana-de-açúcar e suas fases de cultivo de forma temporal e espacial. Além disso, o conhecimento da influência das condições do tempo permite tanto o monitoramento da produção como a aplicação de modelos de estimativa de produtividade. Neste trabalho foram utilizados dados presentes no produto MOD13Q1 do sensor MODIS, sendo NDVI, para identificação e monitoramento, qualidade (VI Quality) e confiabilidade (Reliability), aplicadas para a eliminação de pixels falhos nas imagens de NDVI. Estes foram utilizados para mapear áreas cujo perfil temporal se assemelhasse ao de cultivo de cana-de-açúcar, além de identificar as fases de pico do ciclo vegetativo, colheita, final da colheita e desenvolvimento. Os resultados mostraram que a metodologia foi capaz de identificar perfis característicos de cana-de-açúcar e suas respectivas fases de cultivo. Foram utilizados também dados meteorológicos do modelo global ECMWF para a determinação do total acumulado de precipitação, radiação global, evapotranspiração de referência e graus dias entre as fases de crescimento e colheita da cana-de-açúcar no estado de São Paulo e a estimativa da produtividade. Primeiramente, foi feita a verificação da precisão e acurácia do modelo atmosférico ECMWF pela comparação de dados decendiais simulados de precipitação, temperatura máxima e mínima do ar aos observados por mapas interpolados de estações meteorológicas do estado de São Paulo no período entre 2005 e 2010. Como resultado, observou-se que o modelo ECMWF simula satisfatoriamente, sendo a maior parte dos resultados com R² > 0,60; d > 0,7; RMSE < 5ºC e < 50mm; Es < 5°C e < 24mm. Após a verificação, os acumulados foram apresentados em formato de mapa temático na resolução espacial do sensor MODIS de 250 metros. A análise dos resultados mostrou que foi possível identificar a variabilidade espacial das variáveis climáticas e sua relação com a realidade apresentada por órgãos oficiais. Foi utilizada a metodologia do Zoneamento Agroecológico (ZAE) para a estimativa da produtividade da cana-de-açúcar nos períodos de 2006/2007, 2007/2008, 2008/2009 e 2009/2010. O modelo foi adaptado para a estimativa da produtividade potencial, estimada e o déficit hídrico. Os resultados foram comparados com dados oficiais divulgados pelo órgão IBGE na escala de município e apresentaram relativa eficácia, sendo grande parte com uma superestimativa entre 0 e 25 mil quilogramas por hectare. Foi possível também a geração de mapas de déficit hídrico no Estado de São Paulo para cada período, destacando assim áreas com queda na produtividade
Abstract: Subjective methods are normally used in Brazil to estimate agricultural production. These are based on interviews and therefore limited in terms of statistical evaluations and accuracy estimates of the results. This information is important for public and private planning. Agricultural monitoring and yield estimates using remote sensing and geotecnologies and weather data can contribute significantly for more accurate estimates with lower costs. Sao Paulo state is the largest producer of ethanol and sugarcane in Brazil, thus, it is extremely important to identify areas of sugarcane cultivation and detect the phenological phases, both spatial and temporally. Furthermore, knowledge of the influence of weather conditions allows production monitoring and the application of yield estimation models. NDVI images were used, for identification and monitoring of sugarcane. Quality and Reliability images were used for the elimination of contaminated pixels in NDVI images. These were used to map areas whose temporal profile resembled the sugarcane cultivation behavior, besides to identify the phases of peak of growth cycle (maximum vegetation biomass), harvest, end of harvesting and development of sugarcane. The results showed that the methodology was able to identify the characteristic profile of sugarcane and their respective stages of cultivation. Meteorological data from the ECMWF global model were also used for determining the total cumulated rainfall, global radiation, reference evapotranspiration and degree days between growth and harvesting phases of sugar cane in Sao Paulo and yield estimation. Previously a verification of accuracy and precision of the ECMWF was carried out by comparing 10-day period precipitation, maximum and minimum air temperature simulated with interpolated maps from 33 weather stations in Sao Paulo state between 2005 and 2010, generating statistical maps pixel by pixel. Statistical indexes showed to be satisfactory (most of the results with R² > 0.60, d > 0.7, RMSE < 5ºC and < 50 mm; Es < 5°C and < 24 mm) in the period studied and ECMWF model can be recommended for use in the Sao Paulo state. After verification, the periods accumulated were presented in map format using MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data. For sugarcane yield estimate the Agroecological Zone (ZAE) methodology was used in the periods of 2006/2007, 2007/2008, 2008/2009 and 2009/2010. The estimation of potential yield and water deficit were adapted to the model. The results were compared with official data released by IBGE at municipality scale and presented relative effectiveness, being largely an overestimate between 0 and 25,000 kg per hectare. It was possible to create maps of water deficit in the Sao Paulo state for each period, highlighting sugarcane yield reducing areas
Doutorado
Planejamento e Desenvolvimento Rural Sustentável
Doutor em Engenharia Agrícola
13
Matas, Jakub. « Server a klient pro správu hostingových služeb s využitím frameworku Qt4 a Linuxu ». Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-218860.
Texte intégralRésumé :
This thesis deals with the design and the implementation of a client/server application for the administration of hosting services. Other solutions of hosting services administration are listed as well and they are contrasted and compared with the assigned solution. A description of the particular hosting services and their setting for the Ubuntu Linux distribution are provided. A communication protocol and a data store serving to save all the client accounts and servers were designed. Basic principles of working with C++ framework Qt and its usage for the implementation of both the server and the client application are demonstrated. The basic settings of the server application enabling it to be launched on the server as a service are mentioned as well. In the last part a description is stated of working with the client applications and administration of the client accounts.
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LI, YUANXUN. « SVM Object Based Classification Using Dense Satellite Imagery Time Series ». Thesis, KTH, Geoinformatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233340.
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Kalyadin, Dmitry. « Robot data and control server for Internet-based training on ground robots ». [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002111.
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Nicolau, Rafaela Fernandes. « Índice de vegetação EVI para estimativa de área de milho 2.ª safra e lavouras de inverno ». Universidade Estadual do Oeste do Paraná, 2017. http://tede.unioeste.br/handle/tede/3057.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
The acquisition of effective technologies for prediction and monitoring of agricultural crops highlights the search for methodologies that make this information available before harvesting. Currently, the monitoring of agricultural production is still partially carried out through subjective and onerous techniques by Brazilian official bodies. The study of the agricultural monitoring and/or estimation of winter crops yield, using vegetation indexes extracted from multitemporal images of the MODIS sensor, is a reality that has been tested by several authors, in the search for greater objectivity to the generated figures. In this context, this research aims to map and estimate areas with winter and maize crops, using temporal series of the EVI vegetation index from the MODIS sensor of the Terra and Aqua satellites, for the 2012, 2013, and 2014 harvests for the state of Paraná. As a way of adjusting the mapping through the MODIS sensor (250 meters), the visual analysis was performed in which images of medium spatial resolution (30 meters) were used to identify the chosen cultures. In article 1, color compositions were generated using images from the pre-planting period until the initial development and images representing the vegetative peak of the crops. Subsequently, the extraction of cultivated areas with the crops of interest was performed, so that these could be compared with official data through statistics and correlations, as well as accuracy analyzes. In Article 2, colored compositions were generated using only the vegetative peak images of the cultures to be classified using the Spectral Angle Mapper (SAM) algorithm. Subsequently, the masks were compared with official data through statistics and correlations, as well as accuracy analyzes. In Article 1, an underestimation of the safflower and winter crops areas was found for the 2012 and 2013 crops, and an overestimation for the 2014 safflower, and for the winter crops, overestimation. By the accuracy analyzes, the masks were classified with excellence. In Article 2, it was verified that the data of areas were overestimated for the safflower corn and underestimated for the winter crops. The accuracy analyzes were classified as excellent, in relation to the medium resolution image.
A obtenção de tecnologias eficazes para a previsão e o acompanhamento de safras agrícolas ressalta a busca de metodologias que disponibilizem essas informações antes da colheita. Atualmente, o acompanhamento da produção agrícola é ainda em parte realizado por meio de técnicas subjetivas e onerosas por órgãos oficiais brasileiros. O estudo do monitoramento agrícola e/ou estimativa de safras das culturas de inverno, utilizando índices de vegetação extraídos de imagens multitemporais do sensor MODIS, é uma realidade que tem sido testada por diversos autores na busca de maior objetividade para os valores gerados. Nesse contexto, esta pesquisa tem por objetivo mapear e estimar áreas com as lavouras de inverno e de milho safrinha, utilizando séries temporais do índice de vegetação EVI, provenientes do sensor MODIS dos satélites Terra e Aqua, nas safras 2012, 2013 e 2014 para o estado do Paraná. Como forma de ajustar o mapeamento por meio do sensor MODIS (250 metros), foi realizada uma análise visual em que foram utilizadas imagens de média resolução espacial (30 metros) para identificação das culturas desejadas. No Artigo 1 foram geradas composições coloridas utilizando imagens do período de pré-plantio até o desenvolvimento inicial e imagens que representam o pico vegetativos das lavouras. Posteriormente, foi realizada a extração de áreas cultivadas com as lavouras de interesse para que pudessem ser comparadas com dados oficiais por meio de estatísticas e correlações, como também análises de acurácia. No Artigo 2 foram geradas composições coloridas utilizando somente as imagens que representam os picos vegetativos das lavouras para serem classificadas, utilizando o algoritmo SAM (Spectral angle mapper). Posteriormente, as máscaras foram comparadas com dados oficiais por meio de estatísticas e correlações, como também análises de acurácia. No Artigo 1 foi verificada subestimação para o milho 2ª safra nas safras 2012 e 2013 e superestimação em 2014 e, para lavouras de inverno, superestimação. Pelas análises de acurácia, as máscaras foram classificadas com excelência. No Artigo 2 foi verificado que os dados de áreas foram superestimados para o milho 2ª safra e subestimados para as lavouras de inverno. As análises de acurácia foram classificadas como excelentes em relação à imagem de média resolução.
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Brooks, Evan B. « Fourier Series Applications in Multitemporal Remote Sensing Analysis using Landsat Data ». Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23276.
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Researchers now have unprecedented access to free Landsat data, enabling detailed monitoring of the Earth's land surface and vegetation. There are gaps in the data, due in part to cloud cover. The gaps are aperiodic and localized, forcing any detailed multitemporal analysis based on Landsat data to compensate.
Harmonic regression approximates Landsat data for any point in time with minimal training images and reduced storage requirements. In two study areas in North Carolina, USA, harmonic regression approaches were least as good at simulating missing data as STAR-FM for images from 2001. Harmonic regression had an R^2"0.9 over three quarters of all pixels. It gave the highest R_Predicted^2 values on two thirds of the pixels. Applying harmonic regression with the same number of harmonics to consecutive years yielded an improved fit, R^2"0.99 for most pixels.
We next demonstrate a change detection method based on exponentially weighted moving average (EWMA) charts of harmonic residuals. In the process, a data-driven cloud filter is created, enabling use of partially clouded data. The approach is shown capable of detecting thins and subtle forest degradations in Alabama, USA, considerably finer than the Landsat spatial resolution in an on-the-fly fashion, with new images easily incorporated into the algorithm. EWMA detection accurately showed the location, timing, and magnitude of 85% of known harvests in the study area, verified by aerial imagery.
We use harmonic regression to improve the precision of dynamic forest parameter estimates, generating a robust time series of vegetation index values. These values are classified into strata maps in Alabama, USA, depicting regions of similar growth potential. These maps are applied to Forest Service Forest Inventory and Analysis (FIA) plots, generating post-stratified estimates of static and dynamic forest parameters. Improvements to efficiency for all parameters were such that a comparable random sample would require at least 20% more sampling units, with the improvement for the growth parameter requiring a 50% increase.
These applications demonstrate the utility of harmonic regression for Landsat data. They suggest further applications in environmental monitoring and improved estimation of landscape parameters, critical to improving large-scale models of ecosystems and climate effects.Ph. D.
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Bergvall, Ricardo. « Secure remote access to a work environment ». Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-45124.
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This project is about how free, open-source tools can create reasonable, secure and flexible remote access solutions for smaller companies with a limited budget. Secure remote access to a working environment is a solution for its time, as last year Covid-19 change the working environment for millions of employers and employees. The importance of secure remote access to a working environment became noticeable as offices closed down and employers started working from home. Still, the need for secure access to the company's infrastructure remains. This is where Virtual Private Networks (VPNs) enter the picture, as it has a broad application scope and is particularly useful for secure remote access. My project was subdivided into three parts: How to implement secure remote access to a working environment within the requirements of the chosen company, which are an inexpensive solution with high-security features. Automate the creation and distribution of all the necessary parts that their employees will need in a VPN structure. Research about the future direction regarding VPN and the importance of cybersecurity to help ensure security preparedness for the company. The chosen solution was OpenVPN and Google authenticator, together with a written bash script. It became a solution that was free, flexible, secure and scalable. But why the need and what about the future? Research shows that a high percentage of small and medium-sized enterprises are vulnerable to cyberattacks. It also shows that these companies have the lowest cybersecurity. "It wouldn't happen to us" is dangerous but, sadly, a typical mindset throughout the S&M companies. It's primarily because of this S&M's are more exposed than larger companies. The future of VPN's has become more important than ever before, and it's something that during Covid-19 has risen in use all over the world, the research and development of VPNs has accelerated. The research objectives of this project are of high interest to many other organizations in the same position, and the presented work has helped answer the question: "Where will we stand in a few years regarding secure remote work, cybersecurity andencrypted networks?"
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Amaral, Bruno Ferraz do. « Classificação semissupervisionada de séries temporais extraídas de imagens de satélite ». Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-18112016-105621/.
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Nas últimas décadas, com o crescimento acelerado na geração e armazenamento de dados, houve um aumento na necessidade de criação e gerenciamento de grandes bases de dados. Logo, a utilização de técnicas de mineração de dados adequadas para descoberta de padrões e informações úteis em bases de dados é uma tarefa de interesse. Em especial, bases de séries temporais têm sido alvo de pesquisas em áreas como medicina, economia e agrometeorologia. Em mineração de dados, uma das tarefas mais exploradas é a classificação. Entretanto, é comum em bases de séries temporais, a quantidade e complexidade de dados extrapolarem a capacidade humana de análise manual dos dados, o que torna o processo de supervisão dos dados custoso. Como consequência disso, são produzidos poucos dados rotulados, em comparação a um grande volume de dados não rotulados disponíveis. Nesse cenário, uma abordagem adequada para análise desses dados é a classificação semissupervisionada, que considera dados rotulados e não rotulados para o treinamento do classificador. Nesse contexto, este trabalho de mestrado propõe 1) uma metodologia de análise de dados obtidos a partir de séries temporais de imagens de satélite (SITS) usando tarefas de mineração de dados e 2) uma técnica baseada em grafos para classificação semissupervisionada de séries temporais extraídas de imagens de satélite. A metodologia e a técnica de classificação desenvolvidas são aplicadas na análise de séries temporais de índices de vegetação obtidas a partir de SITS, visando a identificação de áreas de plantio de cana-de-açúcar. Os resultados obtidos em análise experimental, realizada com apoio de especialistas no domínio de aplicação, indicam que a metodologia proposta é adequada para auxiliar pesquisas em agricultura. Além disso, os resultados do estudo comparativo mostram que a técnica de classificação semissupervisionada desenvolvida supera métodos de classificação supervisionada consolidados na literatura e métodos correlatos de classificação semissupervisionada.The amount of digital data generated and stored as well as the need of creation and management of large databases has increased significantly, in the last decades. The possibility of finding valid and potentially useful patterns and information in large databases has attracted the attention of many scientific areas. Time series databases have been explored using data mining methods in serveral domains of application, such as economics, medicine and agrometeorology. Due to the large volume and complexity of some time series databases, the process of labeling data for supervised tasks, such as classification, can be very expensive. To overcome the problem of scarcity of labeled data, semi-supervised classification, which benefits from both labeled and unlabeled data available, can be applied to classify data from large time series databases. In this Master dissertation, we propose 1) a framework for the analysis of data extracted from satellite image time series (SITS) using data mining tasks and 2) a graph-based semi-supervised classification method, developed to classify temporal data obtained from satellite images. According to experts in agrometeorology, the use of the proposed method and framework provides an automatic way of analyzing data extracted from SITS, which is very useful for supporting research in this domain of application. We apply the framework and the proposed semi-supervised classification method in the analysis of vegetation index time series, aiming at identifying sugarcane crop fields, in Brazil. Experimental results indicate that our proposed framework is useful for supporting researches in agriculture, according to experts in the domain of application. We also show that our method is more accurate than traditional supervised methods and related semi-supervised methods.
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Ratana, Piyachat. « Spatial and Temporal Amazon Vegetation Dynamics and Phenology Using Time Series Satellite Data ». Diss., The University of Arizona, 2006. http://hdl.handle.net/10150/194427.
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Improved knowledge of landscape seasonal variations and phenology at the regional scale is needed for carbon and water flux studies, and biogeochemical, hydrological, and climate models. Amazon vegetation mechanisms and dynamics controlling biosphere-atmosphere interactions are not entirely understood. To better understand these processes, vegetation photosynthetic activity and canopy water and temperature dynamics were analyzed over various types of vegetation in Amazon using satellite data from the Terra-Moderate Resolution Imaging Spectroradiometer (MODIS). The objectives of this dissertation were to 1) assess the spatial and temporal variations of satellite data over the Amazon as a function of vegetation physiognomies for monitoring and discrimination, 2) investigate seasonal vegetation photosynthetic activity and phenology across the forest-cerrado ecotone and conversion areas, and 3) investigate seasonal variations of satellite-based canopy water and land surface temperature in relation to photosynthetic activity over the Amazon basin.The results of this study showed the highly diverse and complex cerrado biome and associated cerrado conversions could be monitored and analyzed with MODIS vegetation index (VI) time series data. The MODIS enhanced vegetation index (EVI) seasonal profiles were found useful in characterizing the spatial and temporal variability in landscape phenology across a climatic gradient of rainfall and sunlight conditions through the rainforest-cerrado ecotone. Significant trends in landscape phenology were observed across the different biomes with strong seasonal shifts resulting from differences in vegetation physiognomic responses to rainfall and sunlight. We also found unique seasonal and temporal patterns of the land surface water index (LSWI) and land surface temperature (LST), which in combination with the EVI provided improved information for monitoring the seasonal ecosystem dynamics of the Amazon rainforest, cerrado, ecotone, and conversion areas. In conclusion, satellite-based, regional scale studies were found to aid in understanding land surface processes and mechanisms at the ecosystem level, providing a "big picture" of landscape dynamics. Coupling this with ground, in-situ measurements, such as from flux towers, can greatly improve the estimation of carbon and water fluxes, and our understanding of the biogeochemistry and climate in very dynamic and changing landscapes.
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Maus, Victor Wegner. « Land use and land cover monitoring using remote sensing image time series ». Instituto Nacional de Pesquisas Espaciais (INPE), 2016. http://urlib.net/sid.inpe.br/mtc-m21b/2016/06.01.14.07.
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Land system change has a wide range of impacts on Earth system components. Tropical forests in particular have been identified as crucial ecosystems for climate regulation, global biodiversity, and hydrological cycling. The Brazilian Amazon has experienced a high rate of deforestation in the last decade and it is the main source of Brazils anthropogenic CO$_{2}$ emissions. The growing global population will further increase the demand for food and therefore increase the pressure on agricultural systems. High quality, fine resolution, and near-real time land use and land cover monitoring systems play a crucial role in generating information to advance our understanding of human impact on land cover. Earth Observation satellites are the only source that provides a continuous and consistent set of information about the Earth${'}$s land. The current large-scale classification systems such as MODIS Land Cover and GLC 2000 have limitations and their accuracy is not sufficient for land change modeling. Therefore, new techniques for improving land system products are urgently needed. The contribution of this thesis to Earth System Science is threefold. Firstly, the thesis presents a new method for analysis of remote-sensed image time series that improves spatio-temporal land cover data sets and has a substantial potential for contributing to land system change modeling. The developed Time- Weighted Dynamic Time Warping (TWDTW) method is a time-constraint variation of the well-known Dynamic Time Warping (DTW) method, which has in the extensive literature proved to be a robust time series data mining. Secondly, this thesis contributed to open and reproducible science by making the algorithms available for larger audience. TWDTW is implemented in an open source R package called dtwSat available in the Comprehensive R Archive Network (CRAN). Thirdly, this thesis presents an analysis of land cover changes in the Amazon, focusing on the Brazilian state of Mato Grosso that has gone through high rate of deforestation and cropland expansion in the last decade. This study identified and estimated the land cover change using MODIS image time series, contributing to better understand the land dynamics in the Brazilian Amazon. In the study area the pasture is the dominant land use after deforestation, whereas most of the single cropping area comes from pasture, and the cropping system is undergoing intensification from single to double cropping. Moreover, the regenerative secondary forest comes mainly from pasture. The study showed the potential of the TWDTW method for large-scale remote sensing data analysis, which could be extended to other Brazilian biomes to help understand land change in the whole Brazilian territory.Mudanças na superfície da terra têm uma ampla gama de impactos sobre o sistema terrestre. Florestas tropicais, em particular, são ecossistemas cruciais para regulação climática, manutenção da biodiversidade, a ciclo hidrológico. Na última década a Amazônia brasileira tem experimentado uma alta taxa de desmatamento, sendo a principal fonte de emissões antropogênicas de CO$_{2}$ no Brasil. O crescimento da população mundial vai aumentar ainda mais a demanda por alimentos e, portanto, aumentar a pressão sobre agrícultura e pecuária. Dados com alta qualidade, melhor resolução espacial e temporal, e o desenvolvimento de sistemas de monitoramento desempenham um papel crucial na geração de informações para avançar nossa compreensão sobre os impactos humanos na cobertura da terra. Os satélites de observação da Terra são a única fonte que fornece um conjunto contínuo e consistente de informações sobre nosso planeta. Sistemas de classificação em grande escala, como MODIS Land Cover e GLC 2000 têm limitações e sua acurácia não é suficiente para a modelagem de mudanças de use da terra. Portanto, são necessárias novas técnicas para melhoramento dos dados de use e cobertura da terra. Esta tese traz três contribuições para a Ciência do Sistema Terrestre. Primeiramente, esta tese apresenta um novo método para análise de séries temporais de imagens satélite que melhora a classificação de cobertura da terra. O método tem grande potencial para contribuir para a modelagem de mudanças do sistema terrestre. O método desenvolvido, Time-Weigted Dynamic Time Warping (TWDTW), é uma adaptação ponderada por tempo do método clássico Dynamic Time Warping (DTW), que tem em uma extensa literatura provando ser um método robusto para mineração de dados em séries temporais. Em segundo lugar, esta tese contribuiu para a ciência aberta e reprodutível, tornando algoritmos disponíveis para o público. TWDTW está implementado em um pacote R de código aberto chamado dtwSat disponível no Comprehensive R Archive Network (CRAN). Em terceiro lugar, esta tese apresenta uma análise as mudanças do uso e cobertura da terra na Amazônia, com foco no estado do Mato Grosso, que passou por alta taxa de desmatamento e expansão agrícola na última década. Este estudo identificou e estimou mudanças de cobertura da terra com séries temporais de imagens MODIS, contribuindo para melhor compreender a dinâmica de ocupação da terra na Amazônia brasileira. Na área de estudo, a pastagem é o uso dominante após o desmatamento, ao passo que a maior parte da área de cultivo com um ciclo anual provem da área de pasto, com o sistema de cultivo passando por intensificação, mudando de cultivo simples para cultivo duplo. Além disso, áreas de regeneração vêm, principalmente, de áreas de pastagem. O estudo mostrou o potencial do método de TWDTW para análise de dados de sensoriamento remoto em grande escala, que poderia ser estendido a outros biomas brasileiros para ajudar a entender as mudanças da terra em todo o território brasileiro.
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Jeong, Seongsu. « Time Series Reconstruction of Surface Flow Velocity on Marine-terminating Outlet Glaciers ». The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437602064.
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Gong, Mengyi. « Statistical methods for sparse image time series of remote-sensing lake environmental measurements ». Thesis, University of Glasgow, 2017. http://theses.gla.ac.uk/8608/.
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Remote-sensing technology is widely used in Earth observation, from everyday weather forecasting to long-term monitoring of the air, sea and land. The remarkable coverage and resolution of remote sensing data are extremely beneficial to the investigation of environmental problems, such as the state and function of lakes under climate change. However, the attractive features of remote-sensing data bring new challenges to statistical analysis. The wide coverage and high resolution means that data are usually of large volume. The orbit track of the satellite and the occasional obscuring of the instruments due to atmospheric factors could result in substantial missing observations. Applying conventional statistical methods to this type of data can be ineffective and computationally intensive due to its volume and dimensionality. Modifications to existing methods are often required in order to incorporate the missingness. There is a great need of novel statistical approaches to tackle these challenges. This thesis aims to investigate and develop statistical approaches that can be used in the analysis of the sparse remote-sensing image time series of environmental data. Specifically, three aspects of the data are considered, (a) the high dimensionality, which is associated with the volume and the dimension of data, (b) the sparsity, in the sense of high missing percentages and (c) the spatial/temporal structures, including the patterns and the correlations. Initially, methods for temporal and spatial modelling are explored and implemented with care, e.g. harmonic regression and bivariate spline regression with residual correlation structures. In recognizing the drawbacks of these methods, functional data analysis is employed as a general approach in this thesis. Specifically, functional principal component analysis (FPCA) is used to achieve the goal of dimension reduction. Bivariate basis functions are proposed to transform the satellite image data, which typically consists of thousands/millions of pixels, into functional data with low dimensional representations. This approach has the advantage of identifying spatial variation patterns through the principal component (PC) loadings, i.e. eigenfunctions. To overcome the high missing percentages that might invalidate the standard implementation of the FPCA, the mixed model FPCA (MM-FPCA) was investigated in Chapter 3. Through estimating the PCs using a mixed effect model, the influence of sparsity could be accounted for appropriately. Data imputation can be obtained from the fitted model using the (truncated) Karhunen-Loeve expansion. The method's applicability to sparse image series is examined through a simulation study. To incorporate the temporal dependence into the MM-FPCA, a novel spatio-temporal model consisting of a state space component and a FPCA component is proposed in Chapter 4. The model, referred to as SS-FPCA in the thesis, is developed based on the dynamic spatio-temporal model framework. The SS-FPCA exploits a flexible hierarchical design with (a) a data model consisting of a time varying mean function and random component for the common spatial variation patterns formulated as the FPCA, (b) a process model specifying the type of temporal dynamic of the mean function and (c) a parameter model ensuring the identifiability of the model components. A 2-cycle alternating expectation - conditional maximization (AECM) algorithm is proposed to estimate the SS-FPCA model. The AECM algorithm allows different data augmentations and parameter combinations in various cycles within an iteration, which in this case results in analytical solutions for all the MLEs of model parameters. The algorithm uses the Kalman filter/smoother to update the system states according to the data model and the process model. Model investigations are carried out in Chapter 5, including a simulation study on a 1-dimensional space to assess the performance of the model and the algorithm. This is accompanied by a brief summary of the asymptotic results of the EM-type algorithm, some of which can be used to approximate the standard errors of model estimates. Applications of the MM-FPCA and SS-FPCA to the remote-sensing lake surface water temperature and Chlorophyll data of Lake Victoria (obtained from the European Space Agency's Envisat mission) are presented at the end of Chapter 3 and 5. Remarks on the implications and limitations of these two methods are provided in Chapter 6, along with the potential future extensions of both methods. The Appendices provide some additional theorems, computation and derivation details of the methods investigated in the thesis.
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Kolář, Jakub. « Návrh mobilní aplikace pro správu serveru ». Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-202096.
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Thesis deals with remote servers specifically those for the Minecraft. These servers are divided into groups. The work examines the possibility of remote access to these servers on network protocols level, which are described briefly, and also at the level of the game itself. Describes the game options that can be influenced via remote management. Then analyzes the applications that are intended for this remote access, and identifies problems associated with them. Based on the issues that implied from this analysis, application that solves these problems is designed. The first chapter contains a brief description of the network protocols that can be used to remotely manage servers for the Minecraft and identifies the most appropriate protocol. The next chapter describes the Minecraft, and specifically those of its regions which can be influenced via remote management. The next chapter analyzes the applications that can be used to remotely manage Minecraft servers and based on the problems that this analysis identifies, an application that solves these problems is designed. The designed application is then implemented. The last part contains user documentation of created application.
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Jazdi, Nasser. « Universelle Fernservice-Infrastruktur für eingebettete Systeme ». Aachen : Shaker, 2003. http://deposit.d-nb.de/cgi-bin/dokserv?idn=969068980.
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Hlaváč, Štěpán. « Virtualizace aplikací v architektuře C/S ». Master's thesis, Česká zemědělská univerzita v Praze, 2016. http://www.nusl.cz/ntk/nusl-257073.
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The diploma thesis deals with the possibilities of using application virtualization in the Windows environment. The theoretical part describes the operating principle of application virtualization. Furthermore, there are specified the individual characteristics and the reasons for the move to application virtualization. The author provides the basic overview and comparison of the specific ways of virtualization. The appropriate solution of the practical part was based on the Saaty method. In the practical part, the author describes in detail how to implement and use the chosen technology. Based on practical experience, he assesses functioning of the solution. The final part of the thesis includes both general and specific recommendations for the use of application virtualization.
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Liu, Zhao. « Exploration and application of MISR high resolution Rahman Pinty-Verstraete time series ». Thesis, Cape Peninsula University of Technology, 2017. http://hdl.handle.net/20.500.11838/2711.
Texte intégralRésumé :
Thesis (Doctor of Engineering in Electrical Engineering)--Cape Peninsula University of Technology, 2017.Remote sensing provides a way of frequently observing broad land surfaces. The availability of various earth observation data and their potential exploitation in a wide range of socioeconomic applications stimulated the rapid development of remote sensing technology. Much of the research and most of the publications dealing with remote sensing in the solar spectral domain focus on analysing and interpreting the spectral, spatial and temporal signatures of the observed areas. However, the angular signatures of the reflectance field, known as surface anisotropy, also merit attention. The current research took an exploratory approach to the land surface anisotropy described by the RPV model parameters derived from the MISR-HR processing system (denoted as MISR-HR anisotropy data or MISR-HR RPV data), over a period of 14+ years, for three typical terrestrial surfaces in the Western Cape Province of South Africa: a semi-desert area, a wheat field and a vineyard area. The objectives of this study were to explore (1) to what extent spectral and directional signatures of the MISR-HR RPV data may vary in time and space over the different targets (landscapes), and (2) whether the observed variations in anisotropy might be useful in classifying different land surfaces or as a supplementary method to the traditional land cover classification method. The objectives were achieved by exploring the statistics of the MISR-HR RPV data in each spectral band over the different land surfaces, as well as seasonality and trend in these data. The MISR-HR RPV products were affected by outliers and missing values, both of which influenced the statistics, seasonality and trend of the examined time series. This research proposes a new outlier detection method, based on the cost function derived from the RPV model inversion process. Removed outliers and missing values leave gaps in a MISR-HR RPV time series; to avoid introducing extra biases in the statistics of the anisotropy data, this research kept the gaps and relied on gap-resilient trend and seasonality detection methods, such as the Mann-Kendal trend detection and Lomb-Scargle periodogram methods. The exploration of the statistics of the anisotropy data showed that RPV parameter rho exhibited distinctive over the different study sites; NIR band parameter k exhibits prominent high values for the vineyard area; red band parameter Theta data are not that distinctive over different study sites; variance is important in describing all three RPV parameters. The explorations on trends also demonstrated interesting findings: the downward trend in green band parameter rho data for the semi-desert and vineyard areas; and the upward trend in blue band parameters k and Theta data for all the three study sites. The investigation on seasonality showed that all the RPV parameters had seasonal variations which differed over spectral bands and land covers; the results confirmed expectations in previous literature that parameter varies regularly along the observation time, and also revealed seasonal variations in the parameter rho and Theta data. The explorations on the statistics and seasonality of the MISR-HR anisotropy data show that these data are potentially useful for classifying different landscapes. Finally, the classification results demonstrated that both red band parameter rho data and NIR band parameter k data could successfully separate the three different land surfaces in this research, which fulfilled the second primary objective of this study. This research also demonstrated a classification method using multiple RPV parameters as the classification signatures to discriminate different terrestrial surfaces; significant separation results were obtained by this method.
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Igugu, Onajite Johnson. « LAPSync : a Location-Aware Protocol for Remote File Synchronization ». Thesis, Högskolan Väst, Institutionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-4460.
Texte intégralRésumé :
Commercial provisioning of file synchronization services (FSS) relies entirely on protocols that utilize a remote central server that is often located in the cloud to host important files. Updates at user computers are propagated to the central server and from the central server to other sources in need of such updates. Therefore, a synchronization operation between two computers located on the same network often results in file data transmission to and from this local network at least twice. This introduces an unnecessary bandwidth usage on a user’s local network and has become an issue, especially since there is an increase in the demands for internet resources. This thesis work presents a new file synchronization protocol towards FSS known as LAPSync (location-aware protocol for remote file synchronization). This paper also proposes a hierarchical synchronization mechanism by utilizing LAPSync. Our proposed solution relies on the ability of LAPSync clients to acquire knowledge about the location of clients participating in the synchronization operation to construct a hierarchical synchronization path. Finally, we implement our protocol into a prototype and conduct experiments to compare with drop-box (a popular file synchronization service). The results obtained show that LAPSync offers a reduction in bandwidth usage when the files to be synchronized exist on the same local network
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Wheeler, Brandon Myles. « Evaluating time-series smoothing algorithms for multi-temporal land cover classification ». Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/74313.
Texte intégralRésumé :
In this study we applied the asymmetric Gaussian, double-logistic, and Savitzky-Golay filters to
MODIS time-series NDVI data to compare the capability of smoothing algorithms in noise
reduction for improving land cover classification in the Great Lakes Basin, and providing
groundwork to support cyanobacteria and cyanotoxin monitoring efforts. We used inter-class
separability and intra-class variability, at varying levels of pixel homogeneity, to evaluate the
effectiveness of three smoothing algorithms. Based on these initial tests, the algorithm which
returned the best results was used to analyze how image stratification by ecoregion can affect
filter performance.
MODIS 16-day 250m NDVI imagery of the Great Lakes Basin from 2001-2013 were used in
conjunction with National Land Cover Database (NLCD) 2006 and 2011 data, and Cropland Data
Layers (CDL) from 2008 to 2013 to conduct these evaluations. Inter-class separability was
measured by Jeffries-Matusita (JM) distances between selected land cover classes (both general classes and specific crops), and intra-class variability was measured by calculating simple
Euclidean distance for samples within a land cover class. Within the study area, it was found that the application of a smoothing algorithm can significantly reduce image noise, improving both inter-class separability and intra-class variability when compared to the raw data. Of the three
filters examined, the asymmetric Gaussian filter consistently returned the highest values of interclass separability, while all three filters performed very similarly for within-class variability. The ecoregion analysis based on the asymmetric Gaussian dataset indicated that the scale of study area can heavily impact within-class separability. The criteria we established have potential for furthering our understanding of the strengths and weaknesses of different smoothing algorithms, thereby improving pre-processing decisions for land cover classification using time-series data.Master of Science
30
Fulat, Alper Ihsan. « Investigating Time Series Shoreline Changes By Integration Of Remote Sensing And Geographical Information Systems ». Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606912/index.pdf.
Texte intégralRésumé :
Spatial analyses of shoreline recession and accretion, and future shoreline position predictions in coastal countries have considerable importance due to engineering, planning, management and environmental concerns. In spite of this importance, there are only a few studies in Turkey.
The aim of this thesis are to determine the shoreline rate-of-change of Büyü
k Menderes Delta, by geographical information systems for the last fifty-year period, in order to approximate future shoreline position of Bü
yü
k Menderes Delta shoreline, and to evaluate appropriate models while predicting the future shoreline position. To achieve the purpose of the study time series shoreline position data is extracted from three sets of topographic maps belonging to 1954-1957, 1977-1978 and 1993 aerial photographs and two sets of high resolution satellite imageries (January 2002 Ikonos, August 2004 QuickBird). Then Coastal script of TNTMips, which uses some statistical shoreline analyses methods, that are End Point Rate (EPR), Average of Rates (AOR), Linear Regression (LR) and Jackknifing (JK) is edited so that it can locate the future shoreline positions on the map. Suitable baselines are created and appropriate transect intervals are decided to analyze the shoreline. Finally, some additional analyses that are Backward Analysis and Oscillation Analysis are done to obtain most suitable future shoreline position with rate-of-changes. The results showed that, shorelines having different geomorphologic characteristics needed to be analyzed separately and the linear methods to model the future shoreline position differ from one geomorphologic region to another.
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Qader, Sarchil Hama. « Monitoring decadal land cover and crop production in Iraq using time series remote sensing data ». Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/411281/.
Texte intégral
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Casady, Grant M. « Examining Drivers of Post-Wildfire Vegetation Dynamics Across Multiple Scales Using Time-Series Remote Sensing ». Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/195408.
Texte intégralRésumé :
Ecosystem response to disturbance is a function of environmental factors interacting at a number of spatio-temporal scales. This research explored ecosystem response to wildfire as a function of local and broad-scale environmental factors using satellite based time-series remote sensing data. This topic was explored as a series of three independent but related studies. The first study focused on the evaluation of techniques for the analysis of time-series satellite data for describing post-fire vegetation trends at sites in the US, Spain, and Israel. Time-series data effectively described post-fire trends, and reference sites were valuable for differentiating between post-fire effects and other environmental factors. The use of phenological indicators derived from the time-series shows promise as a monitoring tool, but requires further investigation. The next study evaluated the influence of broad-scale climate factors on rates of post-fire vegetation regeneration across the western US. Rates of post-fire regeneration were higher with increased precipitation and higher minimum temperatures. Changes in climate are likely to result in shifts in post-fire vegetation dynamics, leading to important feedbacks into the climate system. The use of time-series data was a valuable tool in measuring trends in post-fire vegetation across a large area and over an extended period. The final study used time-series vegetation data to measure variations in post-fire vegetation response across an extensive 2002 wildfire. Regression tree analysis related post-fire regeneration to local environmental factors such as burn severity, soil properties, vegetation, and topography. Residuals from modeled rates of post-fire regeneration were evaluated in the context of management activities and site characteristics using expert knowledge. Post-fire rates of regeneration were a function of water availability, pre-burn vegetation, and burn severity. Management activities, soil differences, and shifts in vegetation community composition resulted in deviations from the modeled post-fire regeneration rates. The results of these three research studies indicate that remotely sensed time-series vegetation data provide a useful tool for measuring post-fire vegetation dynamics. Both broad-scale and local environmental factors play important roles in defining post-fire vegetation response, and the use of remote sensing and geospatial data sets can be useful in integrating these factors and enhancing management decisions.
33
Yin, He. « Understanding land use and land cover change in Inner Mongolia using remote sensing time series ». Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2014. http://dx.doi.org/10.18452/17081.
Texte intégralRésumé :
Mittels umweltpolitischer Programme von weltweit einzigartigem Ausmaß versucht China sowohl den menschlichen Druck auf die Landbedeckung zu mindern als auch eine nachhaltige Landnutzung zu fördern. Als Hotspot globaler Umweltveränderungen wurden insbesondere für die Innere Mongolei erhebliche Investitionen zur Renaturierung von Landoberflächen von der chinesischen Zentralregierung getätigt. Die Fernerkundung ist ein effektiver Ansatz für ein flächendeckendes Monitoring des Landnutzungswandels. Jedoch erschweren die limitierte Datenverfügbarkeit und das Fehlen verfügbarer Veränderungsanalysemethoden die Anwendung fernerkundlicher Techniken zum Monitoring von Landnutzung und ihrer Veränderungen. Um den Landnutzungswandel in der Inneren Mongolei verlässlich zu kartieren, wurden daher in einem ersten Schritt Möglichkeiten und Grenzen von Zeitreihen räumlich grob aufgelöster Fernerkundungsdaten für das Monitoring von Langzeitveränderungen der Landbedeckung untersucht. Im zweiten Schritt wurde ein Ansatz zur Erfassung von jährlichen Veränderungen zwischen mehreren Landnutzungsklassen entwickelt und angewandt. Die Ergebnisse zeigen, dass die chinesische Landnutzungspolitik seit dem Jahr 2000 wirksam zum Erhalt und zur Regenerierung von Waldökosystemen in der Inneren Mongolei beiträgt. Abnehmende Entwaldung und ein Zuwachs von Waldflächen sind insbesondere in jenen Regionen zu finden, in welchen die landnutzungspolitischen Maßnahmen umgesetzt wurden. Die Konvertierung von Ackerland zu Grasland wurde zumeist innerhalb anfälliger, klimatisch und topographisch ungeeigneter Gebiete beobachtet. Die vorliegende Dissertation veranschaulicht sowohl den Einfluss politischer Maßnahmen und zugrunde liegender sozio-ökonomischer Treiber auf die Landoberfläche als auch die Bedeutung von grob aufgelösten Fernerkundungsdaten und Zeitreihenanalysen für das Monitoring des Landnutzungswandels in großräumigen Gebieten.Monitoring land use and land cover change (LULCC) support better interpretation about how land surfaces are impacted by human decisions. The overall aim of this thesis is to gain a better understanding about LULCC in Inner Mongolia using remote sensing under consideration of China’s land use policies. With the largest scale land restoration programs in the world, China aims to reduce human pressure on lands and promote sustainable land use. As a hot-spot of environmental change, Inner Mongolia received the heaviest investment from the central government for land restoration. Yet the effectiveness and consequences of China’s land use policies in Inner Mongolia remain unclear. Remote sensing is an effective tool for monitoring land use and land cover change across broad scales, yet data limitations and a lack of available change detection methods hampers the capacity of researchers to apply remote sensing techniques for LULCC monitoring. To reliably map LULCC in Inner Mongolia, the opportunities and limitations of using coarse resolution imagery time series for monitoring long-term land changes was first examined. Second, an approach detecting annual changes between multiple land categories was developed and applied in Inner Mongolia. Results indicate that China’s land use policies effectively preserved and recovered forest ecosystems in Inner Mongolia after the year 2000. The decreasing trends of deforestation and forest gain are obvious in the regions that implement China’s land use policies, which reflect the positive influence of the policy. Cropland retirement was mostly found in ecologically fragile areas where climate and topographic conditions are unsuitable for cultivation. This thesis reveals how political factors and other underlying social-economic drivers impact a country''s land surface, and highlights the values of using coarse resolution imagery and time series analysis for LULCC monitoring across large areas.
34
González, Garcia Isabel. « Influência do clima nas variações estacionais e interanuais do indice de vegetação de diferença normalizada (NDVI) no montado português ». Master's thesis, ISA/UTL, 2012. http://hdl.handle.net/10400.5/5467.
Texte intégralRésumé :
Mestrado em Engenharia do Ambiente - Instituto Superior de AgronomiaNowadays the climate change makes more necessary the study of ecosystem dynamics. The Portuguese montado is an ecosystem with very particular characteristics, because is a combined system with pastures and forest, managed by men, and depends on this manage to continue. More than economic value, montado is very important system with a big biodiversity and landscape quality. For this study was propose to study about the seasonal variation of montado, since 2000 to 2012, using remote sensing and vegetation index as tools to analyze the response of montado to different environmental factors, as the precipitation, temperature and relative humidity. The chosen vegetation index was the NDVI (Normalized Difference Vegetation Index), because of all the advantages, and was calculated using MODIS sensor data. To find the relation between our vegetation index vegetation data, and the meteorological variables, was make a time series analysis, and a correlation study of each variable with the vegetation index. The results was satisfactory and was agree with the initial hypotheses. We find that the precipitation is the variable that influences NDVI the most, and this correlation is bigger when we use the accumulative inter-annual and seasonal data instead the original data. The results show the effects of the big drought of 2004 and 2005 too. The remote sensing appears as a very important and critical tool for this study area future and show that this study could be extend with new directions and new research hypotheses
35
Coladello, Leandro Fernandes. « Integration of heterogeneous data in time series : a study of the evolution of aquatic macrophytes in eutrophic reservoirs based on multispectral images and meteorological data / ». Presidente Prudente, 2020. http://hdl.handle.net/11449/192672.
Texte intégralRésumé :
Orientador: Maria de Lourdes Bueno Trindade GaloResumo: O represamento de rios para a produção de energia elétrica usualmente provoca atividades antrópicas que impactam um ecossistema aquático fortemente. Uma das consequências de se instalar pequenos reservatórios em regiões sujeitas à intensos processos de urbanização e industrialização é a abundância de macrófitas, resultante do despejo de nutrientes em grandes concentrações no ecossistema aquático. Recentemente, o grande volume de images multitemporais de sensoriamento remoto disponíveis em bancos de dados gratuitos, bem como a alta performance computacional que permite a mineração de grandes volumes de dados, fazem com que o monitoramento de fenômenos ambientais seja um objeto de estudo recorrente. O propósito desse estudo é desenvolver uma metodologia baseada na integração de dados heterogêneos, fornecidos por séries temporais de coleções de imagens multiespectrais e multitemporais Landsat e coleções de dados climáticos históricos, para investigar a evolução e comportamento espacial de macrófitas aquáticas em lagos e reservatórios eutrofizados. A extensa coleção temporal de imagens de superfície de reflectância Landsat disponível e também dados de variáveis ambientais permitiram a construção e análise de séries temporais para investigar a recorrente abundância de macrófitas no reservatório de Salto Grande, localizado na região metropolitana de Campinas, São Paulo, Brasil. Inicialmente, foi encontrado que as imagens Landsat possuem a qualidade radiométrica necessária para se r... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: River damming for electric power production usually triggers anthropic activities that strongly impact on aquatic ecosystem. One of the consequences of installing small reservoirs in regions subject to an intense process of urbanization and industrialization is the overabundance of macrophytes, resulting from the input of nutrients in high concentration into the aquatic ecosystem. Currently, the large volume of multitemporal remote sensing images available in open data sources, as well as the high computational performance that allow the mining of large volumes of data has made the monitoring of environmental phenomena a recurrent object of analysis. The aim of this study is to develop a methodology based on the integration of heterogeneous data, provided by time series of multispectral and multitemporal Landsat images and collections of historical climatic data, to investigate the evolution and spatial behavior of aquatic macrophytes in lakes and eutrophic reservoirs. So, the extensive temporal collection of the Landsat surface reflectance images made available as well as environmental variables data permitted the construction and analysis of time series to investigate the recurrent over-abundance of macrophytes in Salto Grande reservoir, located in the metropolitan region of Campinas, São Paulo, Brazil. Initially, it was found that the the Landsat images have the necessary radiometric quality to perform the time series analyses, through an assessment based on information ab... (Complete abstract click electronic access below)
Doutor
36
Gonçalves, Renata Ribeiro do Valle 1981. « Relação entre a resposta espectral da cana-de-açucar, registrada nas imagens dos satelites AVHRR/NOAA, em São Paulo, e dados agroclimaticos, no periodo de 2001 a 2008 ». [s.n.], 2008. http://repositorio.unicamp.br/jspui/handle/REPOSIP/257013.
Texte intégralRésumé :
Orientador: Jurandir Zullo JuniorDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
Made available in DSpace on 2018-08-11T15:26:15Z (GMT). No. of bitstreams: 1 Goncalves_RenataRibeirodoValle_M.pdf: 10756803 bytes, checksum: 9486cabb4eecf44b43d00069814c7126 (MD5) Previous issue date: 2008
Resumo: O Brasil, maior produtor de cana-de-açúcar do mundo, conta com uma posição privilegiada para atender as necessidades mundiais de açúcar e álcool anidro. O país possui regiões produtoras, sendo o estado de São Paulo a maior delas, com safras alternadas que podem garantir a presença do produto nos mercados local e mundial. Isto requer, cada vez mais, a existência de sistemas operacionais que permitam acompanhar o desenvolvimento da cultura ao longo da safra em escala regional. Por outro lado, há um aumento crescente na disponibilidade de dados de sensores remoto que podem ser aplicados no monitoramento da vegetação agrícola, especialmente das que ocupam áreas mais extensas, como é o caso da cana-de-açúcar. Dentro deste contexto, o trabalho teve o objetivo principal de avaliar a correlação existente entre um índice agroclimático (ISNA) e a resposta espectral (NDVI) da cana-de-açúcar registrada nas imagens do satélite AVHRR/NOAA, em regiões produtoras do estado de São Paulo, de 2001 a 2008. As imagens utilizadas foram processadas automaticamente pelo Sistema NAVPRO que gerou imagens corrigidas radiométrica e geometricamente. Com as imagens corrigidas, gerou-se imagens composições de valor máximo de NDVI mensais e perfis temporais de NDVI mensais. As condições agroclimáticas, ao longo do período de análise, foram descritas pelo índice ISNA (Índice de Satisfação das Necessidades de Água). Para calculá-lo, fez-se o balanço hídrico e calculou-se as evapotranspirações real e máxima, em períodos decendiais, quinzenais e mensais. A análise de correlação cruzada entre os dados procurou identificar como as variações climáticas ocorridas de 2001 a 2007 influenciaram a resposta espectral da cana-de-açúcar registrada nas imagens do AVHRR/NOAA. Estas análises identificaram correlações significativas entre o ISNA e o NDVI. Os modelos gerados pelas análises de séries temporais multivariadas foram bem ajustados. Para todos os modelos, o ISNA antecede o NDVI, isto é, o NDVI depende do ISNA em todos os municípios e as previsões feitas ficaram dentro do intervalo de confiança, tornando, assim, os resultados satisfatórios. Os modelos de previsão desenvolvidos permitem utilizar os resultados de safras passadas como base para a estimativa dos parâmetros espectral e agroclimático de safras futuras
Abstract: O Brasil, maior produtor de cana-de-açúcar do mundo, conta com uma posição privilegiada para atender as necessidades mundiais de açúcar e álcool anidro. O país possui regiões produtoras, sendo o estado de São Paulo a maior delas, com safras alternadas que podem garantir a presença do produto nos mercados local e mundial. Isto requer, cada vez mais, a existência de sistemas operacionais que permitam acompanhar o desenvolvimento da cultura ao longo da safra em escala regional. Por outro lado, há um aumento crescente na disponibilidade de dados de sensores remoto que podem ser aplicados no monitoramento da vegetação agrícola, especialmente das que ocupam áreas mais extensas, como é o caso da cana-de-açúcar. Dentro deste contexto, o trabalho teve o objetivo principal de avaliar a correlação existente entre um índice agroclimático (ISNA) e a resposta espectral (NDVI) da cana-de-açúcar registrada nas imagens do satélite AVHRR/NOAA, em regiões produtoras do estado de São Paulo, de 2001 a 2008. As imagens utilizadas foram processadas automaticamente pelo Sistema NAVPRO que gerou imagens corrigidas radiométrica e geometricamente. Com as imagens corrigidas, gerou-se imagens composições de valor máximo de NDVI mensais e perfis temporais de NDVI mensais. As condições agroclimáticas, ao longo do período de análise, foram descritas pelo índice ISNA (Índice de Satisfação das Necessidades de Água). Para calculá-lo, fez-se o balanço hídrico e calculou-se as evapotranspirações real e máxima, em períodos decendiais, quinzenais e mensais. A análise de correlação cruzada entre os dados procurou identificar como as variações climáticas ocorridas de 2001 a 2007 influenciaram a resposta espectral da cana-de-açúcar registrada nas imagens do AVHRR/NOAA. Estas análises identificaram correlações significativas entre o ISNA e o NDVI. Os modelos gerados pelas análises de séries temporais multivariadas foram bem ajustados. Para todos os modelos, o ISNA antecede o NDVI, isto é, o NDVI depende do ISNA em todos os municípios e as previsões feitas ficaram dentro do intervalo de confiança, tornando, assim, os resultados satisfatórios. Os modelos de previsão desenvolvidos permitem utilizar os resultados de safras passadas como base para a estimativa dos parâmetros espectral e agroclimático de safras futuras
Mestrado
Planejamento e Desenvolvimento Rural Sustentável
Mestre em Engenharia Agrícola
37
Ibrahim, Sa’ad. « Remote sensing of tree/grass fractional cover using phenological signal decomposition of MODIS time series data ». Thesis, University of Leicester, 2018. http://hdl.handle.net/2381/42519.
Texte intégralRésumé :
Reliable assessments of tree/grass fractional cover in savanna using remote sensing are challenging due to the heterogeneous mixture of the two plant functional types (PFTs) and soil backgrounds. This thesis reduces this knowledge gap in the remote sensing of tree/grass fractional cover. Tree/grass dynamics in heterogeneous savanna ecosystems are assessed using time-series decomposition of MODIS data acquired from 2002 to 2015. The decomposition method follows a harmonic analysis and tests the harmonic terms for significance. Several scales of spatial and temporal variability are considered for these PFTs (for each field plot against 14 years dataset as well as for the whole study area). In most harmonic cycles, the tree greening-up period started earlier than grasses. While changes in tree cover are more gradual, grasses have high variability over time. The phase (R2 = 0.60, slope = 1, RMSE = 12.52%), cycles (R2 = 0.44, slope = 1.2, RMSE = 17.64%) and amplitude (R2 = 0.36, slope = 0.83, RMSE = 16.28%) of the strongest harmonic terms show good estimate of tree cover. The estimates of tree cover from the simple linear regression of field data and dry season NDVIpixel/SAVIpixel images had good performance. The tree cover estimated using soil determining methods had an improved slope for NDVI and SAVI but yield slightly a high RMSE. A comparison of tree cover using Pearson’s correlation indicated strong agreement with LiDAR/SAR and Bucini woody cover maps. The errors, uncertainties and the challenges in discriminating and estimating trees and grasses using signal decomposition methods are discussed. Tree cover maps will be helpful for vegetation monitoring, climate change impact assessment and vegetation model validation. Finally, the techniques employed for the assessment of tree-grass mixtures in this study would be useful for earth observation especially where end-members of the woody-herbaceous continuum are being considered.
38
Penasa, Luca. « LASERSCANNER CYCLOSTRATIGRAPHY. A REMOTE SENSING APPROACH FOR THE EXTRACTION OF LONG TIME SERIES FROM LARGE OUTCROPS ». Doctoral thesis, Università degli studi di Padova, 2015. http://hdl.handle.net/11577/3424103.
Texte intégralRésumé :
Terrestrial Laser Scanners (TLSs) permit to capture three dimensional models of
outcrops in the form of point clouds. Each point of a point cloud is the result of
a sampling operation on the outcrop’s surface, made trough a laser beam. This
operation records the 3D coordinates of the point and the backscattered laser
energy as an intensity value. Potentially, the intensity can be converted into a
reflectance and used to discriminate different materials.
When series composed of limestone and marl alternations are considered,
TLS intensity can be used as a proxy for the lithology and converted into
intensity-logs which were demonstrated to be a promising source of time series
for cyclostratigraphic analysis.
This thesis started from that result and had the main goal of exploiting
that method to produce long time series, which are essential to the study of
long period (> 1 Myr) Milankovitch cycles in sediments. In this perspective
the following themes were investigated: a) The effect exerted on measured
intensities by shales and chert. Limestone, clay (shales) and chert make most
of many deep water sedimentary successions. b) The identification of a simple
method to normalize the intensities, to minimize the effects of distance from
the outcrop and of the incidence angle of the laser beam. c) The creation of a
software package, composed by a C++ library and a Graphical User Interface
(GUI) for simplifying the user interaction with the data that is needed for
generating the time series.
Three case studies from the Central-Italy Apennines have been considered:
I) The Smirra section (Scaglia Rossa Fm. and Scaglia Variegata Fm. ), composed
of pelagic calcareous homogenites was the playgroud to compare TLS
intensities to calcimetric analyses carried out on samples taken from the
outcrop. Results demonstrate that TLS can be used as a proxy for CaCO 3
content even in series characterized by minimal lithological variations.
II) The Mulini section (Maiolica Fm.). TLS sensitivity to chert was investigated
by comparing laboratory-measured reflectance spectra to TLS intensity. It
is shown that the low-reflectance of chert can be exploited to distinguish
it from limestone. A method based on a Support Vector Machine (SVM)
classifier was thus implemented to recognize chert semi-automatically on
TLS point clouds.
III) The Vispi Quarry (Maiolica Fm., Marne a Fucoidi Fm., Scaglia Bianca Fm.). In
this outcrop an almost continuous 200m-thick stratigraphic succession is
exposed spanning from the upper Maiolica Fm. to the Bonarelli level, and
representing ca. 20 Myrs. This outcrop was ideal to tackle the problem
of retrieving long time series for cyclostratigraphic analysis. An original
method and dedicated software were developed to achieve this task. With
these original tools, it was possible to produce a 150m-long time series
with resolution down to the centimeter, starting from ∼ 30 point clouds.
The methods and algorithms introduced to cope with the long time series
creation from point clouds have been implemented in a C++ library, names
SPC . Easy access to the data structures and methods defined in SPC is instead
provided by a GUI, in the form of a toolbar for the CloudCompare software.
The proposed toolkit is available over the internet at https://github.com/
luca-penasa .I Terrestrial Laser Scanners (TLSs) permettono di creare modelli tridimensionali di affioramenti, nella forma di nuvole di punti. Ogni punto di una nuvola di punti è il risultato di un’operazione di campionamento sulla superficie dell’affioramento, fatta usando un raggio laser. Questa operazione registra le coordinate 3D del punto e l’energia retroriflessa del laser, detta intensità. Potenzialmente, l’intensità può essere convertita in una riflettanza ed essere usata per discriminare matteriali differenti. Quando si considera una serie composta da alternanze di calcari e marne, l’intensità può essere usata come proxy per la litologia e venir convertita in log di intensità, questi si sono dimostrate essere promettenti serie temporali per l’analisi ciclostratigrafica. Questa tesi prende il via da questo risultato, ed ha avuto l’obiettivo principale di esplorare i metodi necessari a produrre serie temporali lunghe, che sono essenziali per studiare cicli Milankoviani di lungo periodo (> 1 Myr) nei sedimenti. In questa prospettiva le seguenti tematiche sono state sviluppate: a) L’effetto di argilliti e selci sull’intensità misurata. Calcare, argilla e selce formano infatti la maggior parte dei sedimenti nelle successioni di acqua pro- fonda. b) L’identificazione di un metodo semplificato per la normalizzazione delle intensità, per minimizzare gli effetti della distanza dall’affioramento e dell’angolo di incidenza del raggio laser. c) La creazione di un pacchetto soft- ware, composto da una libreria C++ e da una Graphical User Interface (GUI) per semplificare l’interazione dell’utente con i dati, che è necessaria per generare le serie temporali. Tre casi studio dagli Appennini dell’Italia Centrale sono stati considerati: I) La sezione di Smirra (Scaglia Rossa Fm. e Scaglia Variegata Fm. ), composta da una omogenite calcarea pelagica, questo caso è stato usato per comparare le intensità del TLS a calcimetrie ottenute da campioni dell’affioramento. I risultati dimostrano che il TLS puó essere usato come proxy per il contenuto in CaCO 3 , anche quando la serie è caratterizzata da variazioni litologiche minime. II) La sezioni dei Mulini (Maiolica Fm.). La sensitività alla selce è stata in- vestigata, comparando misure di riflettanza ottenute in laboratorio con l’intensità del TLS. Si dimostra che la bassa riflettanza della selce può essere impiegata per distiguerla dal calcare. Un metodo basato su un classificatore Support Vector Machine (SVM) è stato implementato per permettere il riconoscimento semi automatico della selce sulle nuvole di punti da TLS. III) La Cava Vispi (Maiolica Fm., Marne a Fucoidi Fm., Scaglia Bianca Fm.). In questo affiormanento è esposta una sezione stratigrafica continua di quasi 200m in spessore, che va dalla parte superiore della Maiolica Fm. fino al Livello Bonarelli, e rappresenta ca. 20 Myrs. Questo affioramento ha fornito il caso ideale per affrontare il problema di ottenere serie temporali lunghe per le analisi ciclostratigrafiche. Una metodologia originale e un software dedicato sono stati sviluppati per questo compito. Con questi strumenti è stato possibile produrre una serie di 150m a risoluzione centimetrica, partendo da ∼ 30 nuvole di punti. I metodi e gli algoritmi introdotti per l’estrazione di serie temporali da nuvole di punti sono stati implementati in una libreria C++ , detta SPC . Un accesso facilitato alle strutture dati e ai metodi definiti in SPC viene invece fornito da una GUI, sottoforma di una toolbar per il software CloudCompare. Il toolkit proposto è disponibile in internet all’indirizzo https://github.com/luca-penasa .
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Johansson, A. Malin. « Remote sensing of supra-glacial lakes on the west Greenland Ice Sheet ». Doctoral thesis, Stockholms universitet, Institutionen för naturgeografi och kvartärgeologi (INK), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-74509.
Texte intégralRésumé :
The Greenland Ice Sheet is the largest ice sheet in the northern hemisphere. Ongoing melting of the ice sheet, resulting in increased mass loss relative to the longer term trend, has raised concerns about the stability of the ice sheet. Melt water generated at the surface is temporarily stored in supra-glacial lakes on the ice sheet. Connections between melt water generation, storage and ice sheet dynamics highlight the importance of the surface hydrological system. In this thesis different methods are used that improve our ability to observe the supra-glacial lake system on the west Greenland Ice Sheet. This region of the Greenland Ice Sheet has the most extensive supra-glacial hydrological system with a dense network of streams connecting lakes that can exceed several square kilometres in area. Synthetic Aperture Radar (SAR) and visible-near infrared (VNIR) images are used to explore the potential of different sensor systems for regular observations of the supra-glacial lakes. SAR imagery is found to be a useful complement to VNIR data. VNIR data from moderate resolution sensors are preferred as these provide high temporal resolution data, ameliorating problems with cloud cover. The dynamic nature of the lakes makes automated classification difficult and manual mapping has been widely used. Here a new method is proposed that improves on existing methods by automating the identification and classification of lakes, and by introducing a flexible system that can capture the full range of lake forms. Applying our new method we are better able to analyse the evolution of lakes over a number of melt seasons. We find that lakes initiate after approximately 40 positive degree days. Most lakes exist for less than 20 days before draining, or later in the season, and less often, freezing over. Using the automated method developed in this thesis lakes have been mapped in imagery from 2001–2010 at approximately five day intervals.At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript. Paper 5: Manuscript.
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Williams, Danielle M. « Time series analysis of vegetation dynamics and burn scar mapping at Smoky Hill Air National Guard Range, Kansas using moderate resolution satellite imagery ». Thesis, Kansas State University, 2016. http://hdl.handle.net/2097/34462.
Texte intégralRésumé :
Master of ArtsDepartment of Geography
J. M. Shawn Hutchinson
Military installations are important assets for the proper training of armed forces. To ensure the continued viability of training lands, management practices need to be implemented to sustain the necessary environmental conditions for safe and effective training. For this study two analyses were done, a contemporary burn history and a time series analysis. The study area is Smoky Hill Air National Guard Range (ANGR), an Impact Area (within the range) and a non-military Comparison Site. Landsat 5 TM / 7 ETM+ imagery was used to create an 11 year composite burn history image. NDVI values were derived from MODIS imagery for the time series analysis using the statistical package BFAST. Results from both studies were combined to make conclusions about training impacts at Smoky Hill ANGR and determine if BFAST is a viable environmental management tool. Based on this study the training within Smoky Hill ANGR does not seem to be having a negative effect on the overall vegetation condition. It was also discovered that BFAST was able to accurately detect known vegetation disturbances. BFAST is a viable environmental management tool if the limitations are understood.
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Seaton, Dylan St Leger. « The use of remote sensing data to monitor pools along non-perennial rivers in the Western Cape, South Africa ». University of the Western Cape, 2019. http://hdl.handle.net/11394/7057.
Texte intégralRésumé :
>Magister Scientiae - MScThe lack of monitoring of non-perennial rivers is a major problem for water resources management, despite their significance in satisfying agricultural, economic and recreational needs. Pools in non-perennial rivers are not monitored, due to their remoteness. Remote sensing offers a promising alternative for the monitoring of changes in water storage in these pools. This study aims to assess the extent to which remotely-sensed datasets can be used to monitor the spatio-temporal changes of water storage of pools along non-perennial rivers in the Western Cape. The objectives of this study are: (1) to determine a suitable image preprocessing and classification technique for detecting and monitoring surface water along nonperennial rivers, and (2) to describe the spatial and temporal changes of water availability of pools along non-perennial rivers, using remotely sensed datasets. The Normalised Difference Water Index (NDWI), Modified NDWI (MNDWI), Normalised Difference Vegetation Index (NDVI), Automated Water Extraction Index for shadowed (AWEIsh) and non-shadowed regions (AWEInsh) and the Multi-Band Water Index (MBWI) classification techniques were investigated in this study, using the Sentinel-2 and Landsat 8 datasets. In-situ measurements were used to validate the satellite-derived datasets, while the use of high resolution aerial photography and Digital-Globe WorldView imagery were further compared to the results. The results suggested that the NDWI is the most suitable classification technique for identifying water in pools along non-perennial rivers throughout the Western Cape. The NDWI applied to the Sentinel-2 Top-of-Atmosphere (TOA) reflectance dataset had the highest overall accuracy of 85%, when compared to the Sentinel-2 Dark Object Subtraction 1 (DOS1) atmospheric correction, Sentinel-2 Sen2Cor atmospheric correction, Landsat 8 TOA reflectance and Landsat 8 DOS1 atmospheric correction datasets. The incorporation of atmospheric correction was shown to eliminate surface water pixels in many of the smaller pools.
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Wessollek, Christine, et Pierre Karrasch. « Monitoring of vegetation dynamics on the former military training area Königsbrücker Heide using remote sensing time series ». SPIE, 2016. https://tud.qucosa.de/id/qucosa%3A35117.
Texte intégralRésumé :
In 1989 about 1.5 million soldiers were stationed in Germany. With the political changes in the early 1990s a substantial decline of the staff occurred on currently 200,000 employees in the armed forces and less than 60,000 soldiers of foreign forces. These processes entailed conversions of large areas not longer used for military purposes, especially in the new federal states in the eastern part of Germany. One of these conversion areas is the former military training area Königsbrück in Saxony. For the analysis of vegetation and its development over time, the Normalized Difference Vegetation Index (NDVI) has established as one of the most important indicators. In this context, the questions arise whether MODIS NDVI products are suitable to determine conversion processes on former military territories like military training areas and what development processes occurred in the 'Königsbrücker Heide' in the past 15 years. First, a decomposition of each series in its trend component, seasonality and the remaining residuals is performed. For the trend component different regression models are tested. Statistical analysis of these trends can reveal different developments, for example in nature development zones (without human impact) and zones of controlled succession. The presented work ow is intended to show the opportunity to support a high temporal resolution monitoring of conversion areas such as former military training areas.
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Adjei, Zola Yaa. « Using Remote Sensing to Explore the Time History of Emergent Vegetation at Malheur Lake, Oregon ». BYU ScholarsArchive, 2015. https://scholarsarchive.byu.edu/etd/5647.
Texte intégralRésumé :
The growth patterns of emergent vegetation can be a useful indicator for factors affecting lake health. However, field data to characterize emergent vegetation at many reservoirs may not be available or may be limited to small, isolated areas. We present a case study using remotely sensed data from the Landsat satellite to generate data to represent emergent vegetation in the near-shoreline and tributary delta areas of Malheur Lake, Oregon. We selected late June images for this study as vegetation is relatively mature in late June and visible, but has not completely grown-in providing a better indication of vegetation coverage in satellite images. We investigated the correlation of vegetation coverage (an indicator of emergent vegetation) with lake area on the day of the satellite collection, average daily maximum temperatures for April, May, June, and July, and average daily precipitation in June, all parameters that could affect vegetation. To estimate historic emergent vegetation extent, we computed the Normalized Difference Vegetation Index (NDVI) for 30 years of Landsat satellite images from 1984 to 2013. Around Malheur Lake we identified eight regions-of-interest (ROI): three inlet areas, three wet-shore areas (swampy areas), and two dry-shore areas (less swampy areas). For each ROI we generated time-series data to quantify the emergent vegetation as determined by the percent of area covered by pixels with NDVI values greater than 0.2. We measured lake area by computing the Modified Normalized Difference Water Index (MNDWI) and computing the area by summing the pixels that indicated water. We compared NDVI time-series values with the time series for lake area, June precipitation, and maximum daily temperatures for April, May, June, and July to determine if these parameters were correlated. Correlation would imply that emergent vegetation was influenced by the parameter. We found that correlations of vegetative extent in any of the eight ROIs with the selected parameters were minimal, indicating that there are other factors besides the ones chosen that drive emergent vegetation levels in Malheur Lake. This study demonstrates that Landsat data have sufficient spatial and temporal detail for quantification and description of ecosystem changes and thus offer a good source of information to understand historic trends in reservoir health. We expect that future work will explore other potential drivers for emergent vegetation extent, such as carp populations in Malheur Lake which are known to affect emergent vegetation. Carp were not considered in this study as we did not have access to data that reflect carp numbers over this 30 year period.
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Zucato, Fábio Labegalini. « Rede ZigBee gerenciada por sistema de monitoramento remoto utilizando TCP/IP e GPRS ». Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/18/18155/tde-03022010-095135/.
Texte intégralRésumé :
Este trabalho propõe a integração de técnicas de sensoriamento dinâmico, redes de dados sem fio e internet. A implementação dos nós da rede visa permitir o monitoramento de objetos que se movem tanto numa rede interna, limitada a uma edificação, quanto numa rede externa, através de coordenadas GPSs (Global Position Systems). A rede sem fio, que utiliza o protocolo ZigBee, é composta por sensores, atuadores e lâmpadas e é dotada de mobilidade através de controles remotos1. A rede ZigBee é integrada, através de um gateway, a uma rede TCP/IP para permitir o monitoramento e a atuação remota sobre ela, via um servidor HTTP e/ou uma rede de dados celular (GPRS), que, quando fora do alcance dos nós da rede ZigBee interna, torna-se responsável pelo envio de coordenadas GPS na rede externa, garantindo a onipresença do monitoramento. Além das adaptações na pilha TCP/IP e o desenvolvimento de um software que utiliza a rede GPRS para envio de coordenadas GPS, destacam-se, como contribuições originais desta tese: (i) a solução de problemas da pilha ZigBee original no tocante a endereçamento, que impossibilitava a mobilidade na rede - desta forma, uma nova técnica de endereçamento seqüencial foi implementada com sucesso; (ii) novo código que simulou o AES (Advanced Encryption Standard), tanto para encriptação quanto para desencriptação dos dados. Testes para validação dos protótipos desenvolvidos são apresentadosThis MSc Thesis proposes the integration of dynamic sensing techniques, wireless data network and Internet. The implementation of network nodes aims to allow monitoring of moving objects, either inside an internal network, limited to one area, or in an external network, through GPS\'s (Global Position Systems). The wireless network, which uses the ZigBee protocol, is composed of sensors, actuators and lamps, and is endowed with mobility through remote controls. Thus, it is integrated, through a gateway, to a TCP / IP network to allow remote monitoring and acting on it via an HTTP server and / or a mobile data network (GPRS), responsible for sending the GPS coordinates on the external network, ensuring the ubiquity of monitoring. Further to adaptations in the TCP/IP stack and the development of a software that uses GPRS protocol to send GPS coordinates, the main contributions of this work are: (i) proposal of a new addressing technique, based on a sequential numbering of nodes, instead of the standard one, thus solving problems related to mobility in the network; (ii) proposal of a new security code to emulate AES (Advanced Encryption Standard), either for data encryption or decryption. Tests for validation of the developed prototypes will be presented
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Braget, Austin Ray. « Time series analysis of phenometrics and long-term vegetation trends for the Flint Hills ecoregion using moderate resolution satellite imagery ». Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/35553.
Texte intégralRésumé :
Master of ArtsDepartment of Geography
J. M. Shawn Hutchinson
Grasslands of the Flint Hills are often burned as a land management practice. Remote sensing can be used to help better manage prairie landscapes by providing useful information about the long-term trends in grassland vegetation greenness and helping to quantify regional differences in vegetation development. Using MODIS 16-day NDVI composite imagery between the years 2001-10 for the entire Flint Hills ecoregion, BFAST was used to determine trend, seasonal, and noise components of the image time series. To explain the trend, 4 factors were considered including hydrologic soil group, burn frequency, and precipitation deviation from the 30 year normal. In addition, the time series data was processed using TIMESAT to extract eight different phenometrics: Growing season length, start of season, end of season, middle of season, maximum value, small integral, left derivative, and right derivative. Phenometrics were produced for each year of the study and an ANOVA was performed on the means of all eight phenometrics to assess if significant differences existed across the study area. A K-means cluster analysis was also performed by aggregating pixel-level phenometrics at the county level to identify administrative divisions exhibiting similar vegetation development. For the study period, the area of negatively and positively trending grassland were similar (41-43%). Logistic regression showed that the log odds of a pixel experiencing a negative trend were higher in sites with clay soils and higher burning frequencies and lower for pixels having higher than normal precipitation and loam soils. Significant differences existed for all phenometrics when considering the ecoregion as a whole. On a phenometric-by-phenometric basis, unexpected groupings of counties often showed statistically similar values. Similarly, when considering all phenometrics at the same time, counties clustered in surprising patterns. Results suggest that long-term trends in grassland conditions warrant further attention and may rival other sources of grassland change (e.g., conversion, transition to savannah) in importance. Analyses of phenometrics indicates that factors other than natural gradients in temperature and precipitation play a significant role in the annual cycle of grassland vegetation development. Unanticipated, and sometimes geographically disparate, groups of counties were shown to be similar in the context of specific phenology metrics and this may prove useful in future implementations of smoke management plans within the Flint Hills.
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Wang, Zhihao. « Land Cover Classification on Satellite Image Time Series Using Deep Learning Models ». The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu159559249009195.
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Mian, Ammar. « Contributions to SAR Image Time Series Analysis ». Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC074/document.
Texte intégralRésumé :
La télédétection par Radar à Synthèse d’Ouverture (RSO) offre une opportunité unique d’enregistrer, d’analyser et de prédire l’évolution de la surface de la Terre. La dernière décennie a permis l’avènement de nombreuses missions spatiales équipées de capteurs RSO (Sentinel-1, UAVSAR, TerraSAR X, etc.), ce qui a engendré une rapide amélioration des capacités d’acquisition d’images de la surface de la Terre. Le nombre croissant d’observations permet maintenant de construire des bases de données caractérisant l’évolution temporelle d’images, augmentant considérablement l’intérêt de l’analyse de séries temporelles pour caractériser des changements qui ont lieu à une échelle globale. Cependant, le développement de nouveaux algorithmes pour traiter ces données très volumineuses est un défi qui reste à relever. Dans ce contexte, l’objectif de cette thèse consiste ainsi à proposer et à développer des méthodologies relatives à la détection de changements dans les séries d’images ROS à très haute résolution spatiale.Le traitement de ces séries pose deux problèmes notables. En premier lieu, les méthodes d’analyse statistique performantes se basent souvent sur des données multivariées caractérisant, dans le cas des images RSO, une diversité polarimétrique, interférométrique, par exemple. Lorsque cette diversité n’est pas disponible et que les images RSO sont monocanal, de nouvelles méthodologies basées sur la décomposition en ondelettes ont été développées. Celles-ci permettent d’ajouter une diversité supplémentaire spectrale et angulaire représentant le comportement physique de rétrodiffusion des diffuseurs présents la scène de l’image. Dans un second temps, l’amélioration de la résolution spatiale sur les dernières générations de capteurs engendre une augmentation de l’hétérogénéité des données obtenues. Dans ce cas, l’hypothèse gaussienne, traditionnellement considérée pour développer les méthodologies standards de détection de changements, n’est plus valide. En conséquence, des méthodologies d’estimation robuste basée sur la famille des distributions elliptiques, mieux adaptée aux données, ont été développées.L’association de ces deux aspects a montré des résultats prometteurs pour la détection de changements.Le traitement de ces séries pose deux problèmes notables. En premier lieu, les méthodes d’analyse statistique performantes se basent souvent sur des données multivariées caractérisant, dans le cas des images RSO, une diversité polarimétrique ou interférométrique, par exemple. Lorsque cette diversité n’est pas disponible et que les images RSO sont monocanal, de nouvelles méthodologies basées sur la décomposition en ondelettes ont été développées. Celles-ci permettent d’ajouter une diversité spectrale et angulaire supplémentaire représentant le comportement physique de rétrodiffusion des diffuseurs présents la scène de l’image. Dans un second temps, l’amélioration de la résolution spatiale sur les dernières générations de capteurs engendre une augmentation de l’hétérogénéité des données obtenues. Dans ce cas, l’hypothèse gaussienne, traditionnellement considérée pour développer les méthodologies standards de détection de changements, n’est plus valide. En conséquence, des méthodologies d’estimation robuste basée sur la famille des distributions elliptiques, mieux adaptée aux données, ont été développées.L’association de ces deux aspects a montré des résultats prometteurs pour la détection de changementsRemote sensing data from Synthetic Aperture Radar (SAR) sensors offer a unique opportunity to record, to analyze, and to predict the evolution of the Earth. In the last decade, numerous satellite remote sensing missions have been launched (Sentinel-1, UAVSAR, TerraSAR X, etc.). This resulted in a dramatic improvement in the Earth image acquisition capability and accessibility. The growing number of observation systems allows now to build high temporal/spatial-resolution Earth surface images data-sets. This new scenario significantly raises the interest in time-series processing to monitor changes occurring over large areas. However, developing new algorithms to process such a huge volume of data represents a current challenge. In this context, the present thesis aims at developing methodologies for change detection in high-resolution SAR image time series.These series raise two notable challenges that have to be overcome:On the one hand, standard statistical methods rely on multivariate data to infer a result which is often superior to a monovariate approach. Such multivariate data is however not always available when it concerns SAR images. To tackle this issue, new methodologies based on wavelet decomposition theory have been developed to fetch information based on the physical behavior of the scatterers present in the scene.On the other hand, the improvement in resolution obtained from the latest generation of sensors comes with an increased heterogeneity of the data obtained. For this setup, the standard Gaussian assumption used to develop classic change detection methodologies is no longer valid. As a consequence, new robust methodologies have been developed considering the family of elliptical distributions which have been shown to better fit the observed data.The association of both aspects has shown promising results in change detection applications
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Pajgrt, Ondřej. « Distribuovaný informační systém malé firmy ». Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237251.
Texte intégralRésumé :
This thesis deals with implementation of distributed information systém for a small construction engineering firm all the way from design to deployment. We will be introduced to distributed applications problems and technologies involved either throught direct relevance or as a support tool for the implementation of the project. In addition, this work will guide us throught complete design and implementation of a final product.
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Matoušek, Vojtěch. « Vzdálené získávání dat z digitálního tachografu ». Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413277.
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Thesis deals with device firmware design located in lorry, which provides remote access to vehicle digital tachograph data according to valid EU legislation. The result of this work is a system, which downloads digital data from digital tachograph and save them on remote server. The system for remote data downloading from automotive digital tachograph consists of three kinds of applications: server application, user application and firmware for communication device. Communication between applications uses encrypted TCP connection and own special designed messages.
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Kliza, Deborah Anne. « An evaluation of trace metal sources in a series of remote lakes in southeastern Ontario, geochemical and paleontological evidence ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ27051.pdf.
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