Letteratura scientifica selezionata sul tema "Vegetation series"
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Articoli di riviste sul tema "Vegetation series":
Simoniello, T., M. Lanfredi, M. Liberti, R. Coppola e M. Macchiato. "Estimation of vegetation cover resilience from satellite time series". Hydrology and Earth System Sciences Discussions 5, n. 1 (28 febbraio 2008): 511–46. http://dx.doi.org/10.5194/hessd-5-511-2008.
Simoniello, T., M. Lanfredi, M. Liberti, R. Coppola e M. Macchiato. "Estimation of vegetation cover resilience from satellite time series". Hydrology and Earth System Sciences 12, n. 4 (30 luglio 2008): 1053–64. http://dx.doi.org/10.5194/hess-12-1053-2008.
Khan, Asim, Warda Asim, Anwaar Ulhaq e Randall W. Robinson. "A deep semantic vegetation health monitoring platform for citizen science imaging data". PLOS ONE 17, n. 7 (27 luglio 2022): e0270625. http://dx.doi.org/10.1371/journal.pone.0270625.
Dobremez, J. F. "Vegetation classification and vegetation mapping in the Himalayas". Geobotanical mapping, n. 1994-1995 (1996): 45–50. http://dx.doi.org/10.31111/geobotmap/1994-1995.45.
Patel, J. H., e M. P. Oza. "Deriving crop calendar using NDVI time-series". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (28 novembre 2014): 869–73. http://dx.doi.org/10.5194/isprsarchives-xl-8-869-2014.
Rivas-Martínez, S., e D. Sánchez-Mata. "Boreal vegetation series of North America". Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology 145, sup1 (settembre 2011): 208–19. http://dx.doi.org/10.1080/11263504.2011.602742.
Liu, Gui Xiang, Zhuo Yi, Feng Ming Yu e Chun Long Jiang. "Study on Effect of Drought Based on Time Series on Grassland Vegetation in Eastern Inner Mongolia". Advanced Materials Research 518-523 (maggio 2012): 5306–15. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5306.
Sun, Chao, Jialin Li, Luodan Cao, Yongchao Liu, Song Jin e Bingxue Zhao. "Evaluation of Vegetation Index-Based Curve Fitting Models for Accurate Classification of Salt Marsh Vegetation Using Sentinel-2 Time-Series". Sensors 20, n. 19 (28 settembre 2020): 5551. http://dx.doi.org/10.3390/s20195551.
Osipov, S. V., e V. P. Verkholat. "The large-scale vegetation maps of the western coast of Peter the Great Bay (Far East, the Sea of Japan)". Geobotanical mapping, n. 1998-2000 (2000): 50–61. http://dx.doi.org/10.31111/geobotmap/1998-2000.50.
Najafi, Z., P. Fatehi e A. A. Darvishsefat. "VEGETATION DYNAMICS TREND USING SATELLITE TIME SERIES IMAGERY". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (18 ottobre 2019): 783–88. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-783-2019.
Tesi sul tema "Vegetation series":
Wahrman, Spencer A. "Time Series Analysis of Vegetation Change using Hyperspectral and Multispectral Data". Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17473.
Grand Lake, Colorado has experienced a severe mountain pine beetle outbreak over the past twenty years. The aim of this study was to map lodgepole pine mortality and health decline due to mountain pine beetle. Multispectral data spanning a five-year period from 2006 to 2011 were used to assess the progression from live, green trees to dead, gray-brown trees. IKONOS data from 2011 were corrected to reflectance and validated against an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral dataset, also collected during 2011. These data were used along with additional reflectance-corrected multispectral datasets (IKONOS from 2007 and QuickBird from 2006 and 2009) to create vegetation classification maps using both library spectra and regions of interest. Two sets of classification maps were produced using Mixture-Tuned Matched Filtering. The results were assessed visually and mathematically. Through visual inspection of the classification maps, increasing lodgepole pine mortality over time was observed. The results were quantified using confusion matrices comparing the classification results of the AVIRIS classified data and the IKONOS and QuickBird classified data. The comparison showed that change could be seen over time, but due to the short time period of the data the change was not as significant as expected.
Julien, Yves. "Vegetation monitoring through retrieval of NDVI and LST time series from historical databases". Doctoral thesis, Universitat de València, 2008. http://hdl.handle.net/10803/10343.
El trabajo de tesis doctoral aquí presentado consiste en el uso extensivo de bases de datos históricas de imágenes de satélite para el seguimiento de la vegetación terrestre, a través de dos parámetros; la temperatura de la superficie terrestre (LST por sus siglas en inglés) y el índice de vegetación NDVI.El primer capítulo de la memoria introduce las nociones de NDVI y LST desde una perspectiva teórica, así como sus principales limitaciones y sus vínculos con la fisiología vegetal. Un estudio bibliográfico permite poner el acento sobre las lagunas en el uso de las bases de datos históricas.El segundo capítulo describe los datos utilizados en este trabajo, proporcionados en su mayoría por el instrumento AVHRR (Advanced Very High Resolution Radiometer) a bordo de la serie de satélites de la NOAA (National Oceanic and Atmospheric Administration) a través de las bases de datos PAL (Pathfinder AVHRR Land) y GIMMS (Global Inventory Modeling and Mapping Studies). También se presentan datos adicionales que se usaron puntualmente. El tercer capítulo describe el proceso para obtener las series temporales de NDVI y LST, las cuales están contaminadas por la deriva orbital de los satélites NOAA. Hemos propuesto una técnica propia para su corrección, validada por comparación directa con datos obtenidos por satélites geoestacionarios.En el cuarto capítulo se introducen diferentes métodos utilizados para el análisis temporal de los datos. Se obtuvieron tendencias acerca de parámetros vinculados a la evolución anual de NDVI para la mayor parte del globo, validadas por comparación con estudios previos.En el quinto capítulo se presenta un análisis conjunto del NDVI y de la LST, seguido por la elaboración de indicadores de la evolución anual de estos dos parámetros. A continuación se presenta un análisis armónico del NDVI y de la LST para Europa. El uso de los indicadores desarrollados para el seguimiento simultáneo del NDVI y de la LST revela resultados prometedores.Por último se presentan las conclusiones más relevantes del trabajo realizado, así como planes de trabajo para un futuro próximo.
Julien, Yves Rodriguez Sobrino José Antonio Nerry Françoise. "Vegetation monitoring through retrieval of NDVI and LST time series from historical databases". Strasbourg : Université Louis Pasteur, 2008. http://eprints-scd-ulp.u-strasbg.fr:8080/1021/01/JULIEN_Yves_2008.pdf.
Thèse soutenue sur un ensemble de travaux. Thèse soutenue en co-tutelle. Titre provenant de l'écran-titre. Bibliogr. 34 p.
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.
Gebrehiwot, Worku Zewdie. "Climate, land use and vegetation trends". Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-209668.
Tomás, Ana Raquel Dias. "Application of empirical mode decomposition (EMD) to chronological series of active fires from MODIS satellite". Master's thesis, ISA/UTL, 2011. http://hdl.handle.net/10400.5/4481.
Fire is a global phenomenon, acting as an important disturbance process. Africa is one of the continents that has higher fire density, particularly in savanna regions, making it the subject of innumerous studies about fire regime and behavior. Here, a new method of time series analysis called Empirical Mode Decomposition (EMD) was applied to monthly fire counts time series from MODIS Terra/Aqua sensors. The goals were to analyze the differences between the time series from the two instruments (MODIS Terra and Aqua), the differences in the behavior of the active fire time series from the north and south parts of Africa and they‟re relationships with climatic modes (ENSO and IOD). For most of the time series, the application of the EMD resulted in four IMF‟s and a residue. Although there is always an IMF related with seasonality, the physical meaning of the other isn‟t clear. This may be due to various reasons, some related with intrinsic problems of the method, other with the applicability of the method to this type of series.
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.
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.
Nowadays 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
Wessollek, Christine, Babatunde Osunmadewa e Pierre Karrasch. "Introducing a rain-adjusted vegetation index (RAVI) for improvement of long-term trend analyses in vegetation dynamics". SPIE, 2015. https://tud.qucosa.de/id/qucosa%3A35057.
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.
Dissertação (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
Libri sul tema "Vegetation series":
United States. Forest Service. Pacific Northwest Region., a cura di. The grand fir series of northeastern Oregon and Southeastern Washington: Successional stages and management guide. [Portland, Or.?]: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Region, Wallowa-Whitman National Forest, 1993.
United States. Forest Service. Pacific Northwest Region., a cura di. The grand fir series of northeastern Oregon and Southeastern Washington: Successional stages and management guide. [Portland, Or.?]: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Region, Wallowa-Whitman National Forest, 1993.
United States. National Aeronautics and Space Administration., a cura di. Study of atmospheric and bidirectional effects on surface reflectance and vegetation index time series: Application to NOAA AVHRR and preparation for future space missions : final report. [Washington, DC: National Aeronautics and Space Administration, 1993.
L, Kovalchik Bernard. Classification and management of aquatic, riparian and wetland sites on the national forests of Eastern Washington : series descriptions. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2004.
F, Hessburg Paul, e Pacific Northwest Research Station (Portland, Or.), a cura di. Classifying plant series-level forest potential vegetation types: Methods for subbasins sampled in the midscale assessment of the interior Columbia Basin. Portland, Or: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2000.
L, Kovalchik Bernard. Classification and management of aquatic, riparian and wetland sites on the national forests of eastern Washington: Series description. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2004.
Don, Scott A., e Langley Research Center, a cura di. Compendium of NASA data base for the Global Tropospheric Experiment's Transport and Atmospheric Chemistry near the Equator - Atlantic (Trace-A). Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.
US DEPARTMENT OF AGRICULTURE. 'Ruby' redosier dogwood. [Washington, D.C.]: U.S. Dept. of Agriculture, 1989.
Austin, M. Vegetation Analysis (Population & Community Biology Series). Kluwer Academic Publishers, 1994.
Reitsma, J. M. Vegetation Forestiere Du Gabon / Forest Vegetation of Gabon (Tropenbos Technical Series). Tropenbos International, 1988.
Capitoli di libri sul tema "Vegetation series":
Matteucci, Silvia D., Andrea F. Rodríguez e Mariana E. Silva. "Vegetation". In World Soils Book Series, 49–62. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76853-3_4.
Pavlović, Pavle, Nikola Kostić, Branko Karadžić e Miroslava Mitrović. "Vegetation". In World Soils Book Series, 41–54. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-017-8660-7_4.
Atalay, İbrahim. "Vegetation". In World Soils Book Series, 15–24. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64392-2_2.
De Graff, Jerome V. "Vegetation Cover". In Encyclopedia of Earth Sciences Series, 923–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73568-9_288.
Arnalds, Olafur. "Vegetation and Ecosystems". In World Soils Book Series, 35–46. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9621-7_4.
Giordano, Andrea. "Vegetation and Land Use". In World Soils Book Series, 57–91. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5642-7_4.
Farzaneh, Ali, e Morteza Ebrahimi Rastaghi. "Vegetation and Land Cover". In World Soils Book Series, 57–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69048-3_5.
Imamul Huq, S. M., e Jalal Uddin Md. Shoaib. "Land Use and Vegetation". In World Soils Book Series, 113–20. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-1128-0_11.
Defila, Claudio. "Do Phytophenological Series Contribute to Vegetation Monitoring?" In Tasks for vegetation science, 97–105. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9686-2_6.
Hiemstra, Christopher A., e Glen E. Liston. "Snow and Vegetation Interaction". In Encyclopedia of Earth Sciences Series, 1067–70. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-2642-2_527.
Atti di convegni sul tema "Vegetation series":
Lhermitte, Stefaan, Jan Verbesselt, Willem W. Verstraeten e Pol Coppin. "Assessing Vegetation Regrowth after Fire Based on Time Series of SPOT-VEGETATION Data". In 2007 International Workshop on the Analysis of Multi-temporal Remote Sensing Images. IEEE, 2007. http://dx.doi.org/10.1109/multitemp.2007.4293050.
Liu, Yaokai, Xihan Mu, Yonggang Qian, Lingli Tang e Chuanrong Li. "A vegetation phenology model for fractional vegetation cover retrieval using time series data". In IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6350588.
Yang, Wei, e Shuwen Zhang. "Monitoring Vegetation Phenology Using MODIS Time-Series Data". In 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2012. http://dx.doi.org/10.1109/rsete.2012.6260634.
Cai, Cai, Peijun Li e Zhongkui Shi. "Vegetation Phenology Extraction and Analysis in Urban Area using Landsat Vegetation Fraction Time Series". In 2018 Fifth International Workshop on Earth Observation and Remote Sensing Applications (EORSA). IEEE, 2018. http://dx.doi.org/10.1109/eorsa.2018.8598629.
Wan, Hongxiu, Zhandong Sun e Yongming Xu. "Monitoring vegetation dynamics with SPOT-VEGETATION NDVI time-series data in Tarim Basin, Xinjiang, China". In SPIE Europe Remote Sensing, a cura di Ulrich Michel e Daniel L. Civco. SPIE, 2009. http://dx.doi.org/10.1117/12.830276.
Lhermitte, S., M. Tips, J. Verbesselt, I. Jonckheere, J. Van Aardt e Pol Coppin. "Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data". In Remote Sensing, a cura di Manfred Owe e Guido D'Urso. SPIE, 2005. http://dx.doi.org/10.1117/12.627625.
Sun, Xiaofang. "Vegetation Change Detection Based on Fractal and Spectral Slope Characteristics of Time Series Vegetation Indice". In 2021 6th International Symposium on Computer and Information Processing Technology (ISCIPT). IEEE, 2021. http://dx.doi.org/10.1109/iscipt53667.2021.00027.
Genong Yu, Liping Di, Zhengwei Yang, Yonglin Shen, Zeqiang Chen e Bei Zhang. "Corn growth stage estimation using time series vegetation index". In 2012 First International Conference on Agro-Geoinformatics. IEEE, 2012. http://dx.doi.org/10.1109/agro-geoinformatics.2012.6311631.
Törmä, Markus, Mikko Kervinen e Saku Anttila. "Estimating vegetation phenological trends using MODIS NDVI time series". In SPIE Remote Sensing, a cura di Ulrich Michel e Daniel L. Civco. SPIE, 2011. http://dx.doi.org/10.1117/12.898062.
Liu, Xinkai, Changmin Jiang, Yiming Ma, Song Hao e Ka Lok Chan. "Daily MODIS 250m two-band enhanced vegetation index (EVI2) time series computation based on autoencoders". In Hyperspectral/Multispectral Imaging and Sounding of the Environment. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/hmise.2023.hm1c.6.
Rapporti di organizzazioni sul tema "Vegetation series":
Melrose, Rachel, Jeff Kingwell, Leo Lymburner e Rohan Coghlan. Murray-Darling Basin vegetation monitoring project : using time series Landsat Satellite data for the assessment of vegetation control. Geoscience Australia, 2013. http://dx.doi.org/10.11636/record.2013.037.
Roessler, Sebastian, Andreas Dietz e Samuel Schilling. Time series analysis of remotely sensed snow cover data: revealing permafrost thermal state and vegetation dynamics. International Permafrost Association (IPA), giugno 2024. http://dx.doi.org/10.52381/icop2024.158.1.
Sekoni, Tosin, Mark Eberle, Matthew Balazik, Monica Chasten, Bob Collins, Brian Durham, Darrell Evans e Kevin Philley. The use of native vegetation and natural materials in shoreline stabilization : a case study of Bubble Gum Beach, Rehoboth Beach, Delaware. Engineer Research and Development Center (U.S.), settembre 2023. http://dx.doi.org/10.21079/11681/47581.
Harris, Brian, Kathleen Harris, Navid Jafari, Jasmine Bekkaye, Elizabeth Murray e Safra Altman. Selection of a time series of beneficial use wetland creation sites in the Sabine National Wildlife Refuge for use in restoration trajectory development. Engineer Research and Development Center (U.S.), settembre 2023. http://dx.doi.org/10.21079/11681/47579.
Mudge, Christopher, e Kurt Getsinger. Comparison of generic and proprietary aquatic herbicides for control of invasive vegetation; part 3 : submersed plants. Engineer Research and Development Center (U.S.), settembre 2021. http://dx.doi.org/10.21079/11681/42061.
Swanson, David, e Celia Hampton-Miller. Drained lakes in Bering Land Bridge National Preserve: Vegetation succession and impacts on loon habitat. National Park Service, gennaio 2023. http://dx.doi.org/10.36967/2296593.
Herman, Brook, Paula Whitfield, Jenny Davis, Amanda Tritinger, Becky Raves, S. Dillon, Danielle Szimanski, Todd Swannack, Joseph Gailani e Jeffery King. Swan Island resilience model development; Phase I : conceptual model. Engineer Research and Development Center (U.S.), gennaio 2023. http://dx.doi.org/10.21079/11681/46402.
Bradford, John, Caroline Havrilla, Jessica Hartsell, Daniel Schlaepfer, Molly McCormick, Seth Munson, Charles Yackulic et al. Southeast Utah Group climate and drought adaptation report: Exposure and perennial grass sensitivity. National Park Service, luglio 2022. http://dx.doi.org/10.36967/2293951.
Sartain, Bradley, Damian Walter e Kurt Getsinger. Flowering rush control in hydrodynamic systems : part 2 : field demonstrations for chemical control of flowering rush. Engineer Research and Development Center (U.S.), giugno 2024. http://dx.doi.org/10.21079/11681/48732.
Sekoni, Tosin, Mark Eberle, Brian Durham e Matthew Balazik. The use of native vegetation for structural stability in dredged material placement areas : a case study of Beneficial Use Site 4A, Chocolate Bayou, Brazoria County, Texas. Engineer Research and Development Center (U.S.), settembre 2023. http://dx.doi.org/10.21079/11681/47588.