Bibliografías temáticas / Vegetation series

Literatura académica sobre el tema "Vegetation series"

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Publicado: 6 de julio de 2024

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  2. Tesis
  3. Libros
  4. Capítulos de libros
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Artículos de revistas sobre el tema "Vegetation series":

1

Simoniello, T., M. Lanfredi, M. Liberti, R. Coppola y M. Macchiato. "Estimation of vegetation cover resilience from satellite time series". Hydrology and Earth System Sciences Discussions 5, n.º 1 (28 de febrero de 2008): 511–46. http://dx.doi.org/10.5194/hessd-5-511-2008.

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Abstract. Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity. In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis methodologies, 8 km AVHRR-NDVI data could be useful for capturing details on vegetation cover activity at local scale even in complex territories such as that of the Italian peninsula.
2

Simoniello, T., M. Lanfredi, M. Liberti, R. Coppola y M. Macchiato. "Estimation of vegetation cover resilience from satellite time series". Hydrology and Earth System Sciences 12, n.º 4 (30 de julio de 2008): 1053–64. http://dx.doi.org/10.5194/hess-12-1053-2008.

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Abstract. Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation activity. In order to characterize resilience, we analyzed the time series 1982–2003 of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence probability of negative and positive trends was estimated according to the vegetation cover class, altitude, and climate. Generally, mean recovery times from negative trends were shorter than those estimated for positive trends, as expected for vegetation of healthy status. Some signatures of inefficient resilience were found in high-level mountainous areas and in the Mediterranean sub-tropical ones. This analysis was refined by aggregating pixels according to phenology. This multitemporal clustering synthesized information on vegetation cover, climate, and orography rather well. The consequent persistence estimations confirmed and detailed hints obtained from the previous analyses. Under the same climatic regime, different vegetation resilience levels were found. In particular, within the Mediterranean sub-tropical climate, clustering was able to identify features with different persistence levels in areas that are liable to different levels of anthropic pressure. Moreover, it was capable of enhancing reduced vegetation resilience also in the southern areas under Warm Temperate sub-continental climate. The general consistency of the obtained results showed that, with the help of suited analysis methodologies, 8 km AVHRR-NDVI data could be useful for capturing details on vegetation cover activity at local scale even in complex territories such as that of the Italian peninsula.
3

Khan, Asim, Warda Asim, Anwaar Ulhaq y Randall W. Robinson. "A deep semantic vegetation health monitoring platform for citizen science imaging data". PLOS ONE 17, n.º 7 (27 de julio de 2022): e0270625. http://dx.doi.org/10.1371/journal.pone.0270625.

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Automated monitoring of vegetation health in a landscape is often attributed to calculating values of various vegetation indexes over a period of time. However, such approaches suffer from an inaccurate estimation of vegetational change due to the over-reliance of index values on vegetation’s colour attributes and the availability of multi-spectral bands. One common observation is the sensitivity of colour attributes to seasonal variations and imaging devices, thus leading to false and inaccurate change detection and monitoring. In addition, these are very strong assumptions in a citizen science project. In this article, we build upon our previous work on developing a Semantic Vegetation Index (SVI) and expand it to introduce a semantic vegetation health monitoring platform to monitor vegetation health in a large landscape. However, unlike our previous work, we use RGB images of the Australian landscape for a quarterly series of images over six years (2015–2020). This Semantic Vegetation Index (SVI) is based on deep semantic segmentation to integrate it with a citizen science project (Fluker Post) for automated environmental monitoring. It has collected thousands of vegetation images shared by various visitors from around 168 different points located in Australian regions over six years. This paper first uses a deep learning-based semantic segmentation model to classify vegetation in repeated photographs. A semantic vegetation index is then calculated and plotted in a time series to reflect seasonal variations and environmental impacts. The results show variational trends of vegetation cover for each year, and the semantic segmentation model performed well in calculating vegetation cover based on semantic pixels (overall accuracy = 97.7%). This work has solved a number of problems related to changes in viewpoint, scale, zoom, and seasonal changes in order to normalise RGB image data collected from different image devices.
4

Dobremez, J. F. "Vegetation classification and vegetation mapping in the Himalayas". Geobotanical mapping, n.º 1994-1995 (1996): 45–50. http://dx.doi.org/10.31111/geobotmap/1994-1995.45.

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In the introduction the history of botanical exploration of the Himalayas is considered starting from the late XVIIIth century up to present time. The next part of the article is devoted to the history of vegetation mapping proper. Vegetation maps relating to the Himalayas as a whole and to its different parts are enumerated including the vegetation map of Nepal in 8 sheets at scale 1 : 2 500 000 by the author (1971 to 1985) and his two large-scale maps (1 : 50 000) covering small areas in Eastern and Central Nepal (1974 and 1977). The above vegetation maps have been constructed using the basic concepts of vegetation level and vegetation series by Gaussen and Ozenda along with the biogeographic concept taking into account the diversity of flora and vegetation. The concept of vegetation level reflects the altitudinal zonation of vegetation, 11 vegetation levels being distinguished in Central Himalayas. The other basic concept is that of vegetation series depicting the dynamics of vegetation cover with respect to human activity. One series includes all the vegetation types which terminate, by natural evolution, in one climax vegetation type (potential vegetation). For Nepal about 100 vegetation series have been described and mapped.
5

Patel, J. H. y 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 de noviembre de 2014): 869–73. http://dx.doi.org/10.5194/isprsarchives-xl-8-869-2014.

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Agricultural intensification is defined in terms as cropping intensity, which is the numbers of crops (single, double and triple) per year in a unit cropland area. Information about crop calendar (i.e. number of crops in a parcel of land and their planting & harvesting dates and date of peak vegetative stage) is essential for proper management of agriculture. Remote sensing sensors provide a regular, consistent and reliable measurement of vegetation response at various growth stages of crop. Therefore it is ideally suited for monitoring purpose. The spectral response of vegetation, as measured by the Normalized Difference Vegetation Index (NDVI) and its profiles, can provide a new dimension for describing vegetation growth cycle. The analysis based on values of NDVI at regular time interval provides useful information about various crop growth stages and performance of crop in a season. However, the NDVI data series has considerable amount of local fluctuation in time domain and needs to be smoothed so that dominant seasonal behavior is enhanced. Based on temporal analysis of smoothed NDVI series, it is possible to extract number of crop cycles per year and their crop calendar. <br><br> In the present study, a methodology is developed to extract key elements of crop growth cycle (i.e. number of crops per year and their planting – peak - harvesting dates). This is illustrated by analysing MODIS-NDVI data series of one agricultural year (from June 2012 to May 2013) over Gujarat. Such an analysis is very useful for analysing dynamics of kharif and rabi crops.
6

Rivas-Martínez, S. y D. Sánchez-Mata. "Boreal vegetation series of North America". Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology 145, sup1 (septiembre de 2011): 208–19. http://dx.doi.org/10.1080/11263504.2011.602742.

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7

Liu, Gui Xiang, Zhuo Yi, Feng Ming Yu y Chun Long Jiang. "Study on Effect of Drought Based on Time Series on Grassland Vegetation in Eastern Inner Mongolia". Advanced Materials Research 518-523 (mayo de 2012): 5306–15. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.5306.

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This paper, based on the long sequence meteorological data and the MODIS remote sensing data, calculates the every-ten-day NDVI index and SPI index of the grassland vegetation in the Eastern Inner Mongolia between 2006 and 2010. It applies the SPI index to indicate the degree of drought and the NDVI index to represent the growth status of the grassland vegetation. This paper analyzes the relationship between the NDVI index and the SPI index by the Time Series Spectrum Analysis Method, leading to the conclusion that the vegetations are sensitive to the drought in the green-turning and yellowing period, but relatively not that sensitive in the budding and maturation period, and that, the vegetations in meadow grassland, typical grassland and desert grassland vary in the responses to the drought.
8

Sun, Chao, Jialin Li, Luodan Cao, Yongchao Liu, Song Jin y 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.º 19 (28 de septiembre de 2020): 5551. http://dx.doi.org/10.3390/s20195551.

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The successful launch of the Sentinel-2 constellation satellite, along with advanced cloud detection algorithms, has enabled the generation of continuous time series at high spatial and temporal resolutions, which is in turn expected to enable the classification of salt marsh vegetation over larger spatiotemporal scales. This study presents a critical comparison of vegetation index (VI) and curve fitting methods—two key factors for time series construction that potentially influence vegetation classification performance. To accomplish this objective, the stability of five different VI time series, namely Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Enhanced Vegetation Index (EVI), Green Normalized Difference Vegetation Index (GNDVI), and Water-Adjusted Vegetation Index (WAVI), was compared empirically; the suitability between three curve fitting methods, namely Asymmetric Gaussian (AG), Double Logistic (DL), and Two-term Fourier (TF), and VI time series was measured using the coefficient of determination, and the salt marsh vegetation separability among different combinations of VI time series and curve fitting methods (i.e., VI time series-based curve fitting model) was quantified using overall the Jeffries–Matusita distance. Six common types of salt marsh vegetation from three typical coastal sites in China were used to validate these findings, which demonstrate: (1) the SAVI performed best in terms of time series stability, while the EVI exhibited relatively poor time series stability with conspicuous outliers induced by the sensitivity to omitted clouds and shadows; (2) the DL method commonly resulted in the most accurate classification of different salt marsh vegetation types, especially when combined with the EVI time series, followed by the TF method; and (3) the SAVI/NDVI-based DL/TF model demonstrated comparable efficiency for classifying salt marsh vegetation. Notably, the SAVI/NDVI-based DL model performed most strongly for high latitude regions with a continental climate, whilst the SAVI/NDVI-based TF model appears to be better suited to mid- to low latitude regions dominated by a monsoonal climate.
9

Osipov, S. V. y 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.º 1998-2000 (2000): 50–61. http://dx.doi.org/10.31111/geobotmap/1998-2000.50.

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Two territories on the western coast of Peter the Great Bay were mapped in the large scale. The geobotanical mapping means revealing and displaying the essential regularities of vegetation cover. Both the spatial and temporal regularities of vegetation under natural and anthropogenic influences are well pronounced in the territory under consideration. The concept of the vegetation spatial unit (vegetation complexes) was applied as a basis for mapping. The maps and their legend were worked out as a system of vegetation combination types (vegetation combination is a spatial unit of the supracoenotic level). Such categories, as vegetation of tops and slopes, lowlands and river valleys, sea coasts reflect maximal contrasts in vegetation cover, so they are the highest level divisions of the map legend. Types of succession series and stages of series are developed for construction of the second and third levels of the legend. Communities, similar in ecotope, total species composition, saplings and some other characteristics, are referred to one type of series. 5 types of series have been distinguished: dry, fresh, moist, very moist, wet. The main factor of dynamics in considered territory is fire and the series are mainly pyrogeneous. Series are presented as sequences of vegetation stages. The vegetation stages for tops and slopes are: closed low forest — open low woodland — shrub thicket with saplings — meadow with saplings, for lowlands and river valleys they are: open low woodland — thicket of saplings — meadow or mire with saplings.
10

Najafi, Z., P. Fatehi y 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 de octubre de 2019): 783–88. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-783-2019.

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Abstract. In this study, the trend of vegetation dynamics in Kermanshah city assessed using NDVI MOD13Q1 product over the time period of 2000–2017. Based on time series imagery the pick of vegetation phenology stage (maximum NDVI) identified, then the trend of vegetation dynamic was investigated using the Ordinary Least Square regression and the Theil-Sen approaches. To generate a pixel-wise trend map, a pixel-based vegetation dynamics was also implemented. A non-parametric Mann-Kendall statistics approach was used to examine a statistically significant trend analysis. The mean maximum NDVI observed for the first half or second half of April. Trend analysis using regression and Theil-Sen methods indicated a no-trend in vegetation fractions. The pixel-based trend assessment using regression showed that a 50% of the study area faced a positive trend and reaming part faced a negative trend. The Theil-Sen method revealed the no-trend for a large majority of area. The Mann-Kendall test indicated that only 20 percent of the area shows a statistically significant trend.
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Artículos de revistas Tesis Libros

Tesis sobre el tema "Vegetation series":

1

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.

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Approved for public release; distribution is unlimited
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.
2

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.

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The PhD dissertation presented here falls into the Earth Observation field, specifically vegetation monitoring. This work consists in the extensive exploitation of historical databases of satellite images for vegetation monitoring through two parameters, which are the land surface temperature (LST) and a vegetation index (NDVI). Up to now, vegetation monitoring has been limited to the use of vegetation indices, so the addition of the land surface temperature parameter represents the main innovative character of this PhD study.This dissertation is divided into 5 chapters. The first chapter begins by introducing the theoretical aspects of NDVI and LST parameters, addressing the means for retrieving them from remotely sensed observations, as well as their main limitations. Then, an introduction to vegetal physiology is developed, which allows for understanding how NDVI and LST parameters are linked to plants. A bibliographical study is then presented, which stresses out the gaps in the exploitation of historical databases.The second describes the data used in this PhD. The instrument providing most of these data is embarked on the NOAA (National Oceanic and Atmospheric Administration) satellite series. This instrument is the AVHRR (Advanced Very High Resolution Radiometer). The AVHRR databases used in this work are the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) databases. Additional data used punctually are also described briefly.The third chapter describes the operations applied to the data to prepare their temporal analysis. These operations start with the calculations of vegetation index and land surface temperature parameters. The AVHRR data used in this work are contaminated by the orbital drift of NOAA satellites, so an important part of this doctorate consisted in developing a technique for correcting this effect. We chose to develop our own technique, which we validated by direct comparison with data retrieved by geostationary satellites.In the fourth chapter, the different methods used for data temporal analysis are presented. Those methods consist of trend detection, harmonic analysis, and fitting the temporal series to annual NDVI evolution curves. Then, a phenological analysis is presented, which allows for retrieval of trends in spring and autumn dates for most of the globe. These trends are validated by comparison with previous studies. The trend analysis for spring dates is then extended to the 1948-2006 period using air temperature data. The long-term observation of different NDVI indicators also allows for the detection of land vegetation changes, even in our case of coarse spatial resolution. Finally, two methods for NDVI temporal analysis are compared.In the fifth chapter, a quick presentation of simultaneous study of NDVI and LST is developed through a revision of previous results, followed by the observations carried out from the orbital drift corrected data. These observations allowed for the determination of indicators of NDVI and LST, thus enabling for the characterization of the vegetation at global scale. A harmonic analysis of NDVI and LST at European scale is also presented. The application of the developed indicators for simultaneous monitoring of NDVI and LST shows promising results.As a conclusion, the main results described above are summarized, and plans for a close future are presented. This PhD has also demonstrated that such work could be carried out in a small structure with limited resources.
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.
3

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.

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Thèse de doctorat : Electronique, électrotechnique, automatique : Strasbourg 1 : 2008. Tesis doctoral : Electrónica, electrotécnica, automático : Universitat de València : 2008.
Thèse soutenue sur un ensemble de travaux. Thèse soutenue en co-tutelle. Titre provenant de l'écran-titre. Bibliogr. 34 p.
4

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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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.

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Land use / land cover (LULC) change assessment is getting more consideration by global environmental change studies as land use change is exposing dryland environments for transitions and higher rates of resource depletion. The semiarid regions of northwestern Ethiopia are not different as land use transition is the major problem of the region. However, there is no satisfactory study to quantify the change process of the region up to now. Hence, spatiotemporal change analysis is vital for understanding and identification of major threats and solicit solutions for sustainable management of the ecosystem. LULC change studies focus on understanding the patterns, processes and dynamics of land use transitions and driving forces of change. The change processes in dryland ecosystems can be either seasonal, gradual or abrupt changes of random or systematic change processes that result in a pattern or permanent transition in land use. Identification of these processes of change and their type supports adoption of monitoring options and indicate possible measures to be taken to safeguard this dynamic ecosystem. This study examines the spatiotemporal patterns of LULC change, temporal trends in climate variables and the insights of the communities on change patterns of ecosystems. Landsat imagery, MODIS NDVI, CRU temperature, TAMSAT rainfall and socio-ecological field data were used in order to identify change processes. LULC transformation was monitored using support vector machine (SVM) algorithm. A cross-tabulation matrix assessment was implemented in order to assess the total change of land use categories based on net change and swap change. In addition, the pattern of change was identified based on expected gain and loss under a random process of gain and loss, respectively. Breaks For Additive Seasonal and Trend (BFAST) analysis was employed for determining the time, direction and magnitude of seasonal, abrupt and trend changes within the time series datasets. In addition, Man Kendall test statistic and Sen’s slope estimator were used for assessing long term trends on detrended time series data components. Distributed lag (DL) model was also adopted in order to determine the time lag response of vegetation to the current and past rainfall distribution. Over the study period of 1972- 2014, there is a significant change in LULC as evidenced by a significant increase in size of cropland of about 53% and a net loss of over 61% of woodland area. The period 2000-2014 has shown a sharp increase of cropland and a sharp decline of woodland areas. Proximate causes include agricultural expansion and excessive wood harvesting; and underlying causes of demographic factor, economic factors and policy contributed the most to an overuse of existing natural resources. In both the observed and expected proportion of random process of change and of systematic changes, woodland has shown the highest loss compared to other land use types. The observed transition and expected transition under random process of gain of woodland to cropland is 1.7%, implies that cropland systematically gains to replace woodland. The comparison of the difference between observed and expected loss under random process of loss also showed that when woodland loses cropland systematically replaces it. The assessment of magnitude and time of breakpoints on climate data and NDVI showed different results. Accordingly, NDVI analysis demonstrated the existence of breakpoints that are statistically significant on the seasonal and long term trends. There is a positive trend, but no breakpoints on the long term precipitation data during the study period. The maximum temperature also showed a positive trend with two breakpoints which are not statistically significant. On the other hand, there is no seasonal and trend breakpoints in minimum temperature, though there is an overall positive trend along the study period. The Man-Kendall test statistic for long term average Tmin and Tmax showed significant variation where as there is no significant trend within the long term rainfall distribution. The lag regression between NDVI and precipitation indicated a lag of up to forty days. This proves that the vegetation growth in this area is not primarily determined by the current precipitation rather with the previous forty days rainfall. The combined analysis showed declining vegetation productivity and a loss of vegetation cover that contributed for an easy movement of dust clouds during the dry period of the year. This affects the land condition of the region, resulting in long term degradation of the environment
6

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.

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Mestrado em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia
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.
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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.

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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.
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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.

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Mestrado em Engenharia do Ambiente - Instituto Superior de Agronomia
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
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Wessollek, Christine, Babatunde Osunmadewa y 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.

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It seems to be obvious that precipitation has a major impact on greening during the rainy season in semi-arid regions. First results1 imply a strong dependence of NDVI on rainfall. Therefore it will be necessary to consider specific rainfall events besides the known ordinary annual cycle. Based on this fundamental idea, the paper will introduce the development of a rain adjusted vegetation index (RAVI). The index is based on the enhancement of the well-known normalized difference vegetation index (NDVI2) by means of TAMSAT rainfall data and includes a 3-step procedure of determining RAVI. Within the first step both time series were analysed over a period of 29 years to find best cross correlation values between TAMSAT rainfall and NDVI signal itself. The results indicate the strongest correlation for a weighted mean rainfall for a period of three months before the corresponding NDVI value. Based on these results different mathematical models (linear, logarithmic, square root, etc.) are tested to find a functional relation between the NDVI value and the 3-months rainfall period before (0.8). Finally, the resulting NDVI-Rain-Model can be used to determine a spatially individual correction factor to transform every NDVI value into an appropriate rain adjusted vegetation index (RAVI).
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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.

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Orientadores: Jansle Vieira Rocha, Rubens Augusto Camargo Lamparelli
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agricola
Made available in DSpace on 2018-08-14T11:30:01Z (GMT). No. of bitstreams: 1 Fernandes_JefersonLobato_M.pdf: 2074887 bytes, checksum: af58e53746d7d186e6f1331527b3c3e8 (MD5) Previous issue date: 2009
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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Libros sobre el tema "Vegetation series":

1

United States. Forest Service. Pacific Northwest Region., ed. 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.

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United States. Forest Service. Pacific Northwest Region., ed. 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.

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United States. National Aeronautics and Space Administration., ed. 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.

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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.

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F, Hessburg Paul y Pacific Northwest Research Station (Portland, Or.), eds. 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.

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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.

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Don, Scott A. y Langley Research Center, eds. 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.

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US DEPARTMENT OF AGRICULTURE. 'Ruby' redosier dogwood. [Washington, D.C.]: U.S. Dept. of Agriculture, 1989.

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Austin, M. Vegetation Analysis (Population & Community Biology Series). Kluwer Academic Publishers, 1994.

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Reitsma, J. M. Vegetation Forestiere Du Gabon / Forest Vegetation of Gabon (Tropenbos Technical Series). Tropenbos International, 1988.

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Capítulos de libros sobre el tema "Vegetation series":

1

Matteucci, Silvia D., Andrea F. Rodríguez y Mariana E. Silva. "Vegetation". En World Soils Book Series, 49–62. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76853-3_4.

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Pavlović, Pavle, Nikola Kostić, Branko Karadžić y Miroslava Mitrović. "Vegetation". En World Soils Book Series, 41–54. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-017-8660-7_4.

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Atalay, İbrahim. "Vegetation". En World Soils Book Series, 15–24. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64392-2_2.

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De Graff, Jerome V. "Vegetation Cover". En Encyclopedia of Earth Sciences Series, 923–24. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73568-9_288.

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Arnalds, Olafur. "Vegetation and Ecosystems". En World Soils Book Series, 35–46. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9621-7_4.

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Giordano, Andrea. "Vegetation and Land Use". En World Soils Book Series, 57–91. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5642-7_4.

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Farzaneh, Ali y Morteza Ebrahimi Rastaghi. "Vegetation and Land Cover". En World Soils Book Series, 57–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69048-3_5.

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Imamul Huq, S. M. y Jalal Uddin Md. Shoaib. "Land Use and Vegetation". En World Soils Book Series, 113–20. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-1128-0_11.

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Defila, Claudio. "Do Phytophenological Series Contribute to Vegetation Monitoring?" En Tasks for vegetation science, 97–105. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9686-2_6.

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Hiemstra, Christopher A. y Glen E. Liston. "Snow and Vegetation Interaction". En Encyclopedia of Earth Sciences Series, 1067–70. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-2642-2_527.

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Actas de conferencias sobre el tema "Vegetation series":

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Lhermitte, Stefaan, Jan Verbesselt, Willem W. Verstraeten y Pol Coppin. "Assessing Vegetation Regrowth after Fire Based on Time Series of SPOT-VEGETATION Data". En 2007 International Workshop on the Analysis of Multi-temporal Remote Sensing Images. IEEE, 2007. http://dx.doi.org/10.1109/multitemp.2007.4293050.

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Liu, Yaokai, Xihan Mu, Yonggang Qian, Lingli Tang y Chuanrong Li. "A vegetation phenology model for fractional vegetation cover retrieval using time series data". En IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2012. http://dx.doi.org/10.1109/igarss.2012.6350588.

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Yang, Wei y Shuwen Zhang. "Monitoring Vegetation Phenology Using MODIS Time-Series Data". En 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2012. http://dx.doi.org/10.1109/rsete.2012.6260634.

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Cai, Cai, Peijun Li y Zhongkui Shi. "Vegetation Phenology Extraction and Analysis in Urban Area using Landsat Vegetation Fraction Time Series". En 2018 Fifth International Workshop on Earth Observation and Remote Sensing Applications (EORSA). IEEE, 2018. http://dx.doi.org/10.1109/eorsa.2018.8598629.

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Wan, Hongxiu, Zhandong Sun y Yongming Xu. "Monitoring vegetation dynamics with SPOT-VEGETATION NDVI time-series data in Tarim Basin, Xinjiang, China". En SPIE Europe Remote Sensing, editado por Ulrich Michel y Daniel L. Civco. SPIE, 2009. http://dx.doi.org/10.1117/12.830276.

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Lhermitte, S., M. Tips, J. Verbesselt, I. Jonckheere, J. Van Aardt y Pol Coppin. "Development of indicators of vegetation recovery based on time series analysis of SPOT Vegetation data". En Remote Sensing, editado por Manfred Owe y Guido D'Urso. SPIE, 2005. http://dx.doi.org/10.1117/12.627625.

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Sun, Xiaofang. "Vegetation Change Detection Based on Fractal and Spectral Slope Characteristics of Time Series Vegetation Indice". En 2021 6th International Symposium on Computer and Information Processing Technology (ISCIPT). IEEE, 2021. http://dx.doi.org/10.1109/iscipt53667.2021.00027.

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Genong Yu, Liping Di, Zhengwei Yang, Yonglin Shen, Zeqiang Chen y Bei Zhang. "Corn growth stage estimation using time series vegetation index". En 2012 First International Conference on Agro-Geoinformatics. IEEE, 2012. http://dx.doi.org/10.1109/agro-geoinformatics.2012.6311631.

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Törmä, Markus, Mikko Kervinen y Saku Anttila. "Estimating vegetation phenological trends using MODIS NDVI time series". En SPIE Remote Sensing, editado por Ulrich Michel y Daniel L. Civco. SPIE, 2011. http://dx.doi.org/10.1117/12.898062.

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Liu, Xinkai, Changmin Jiang, Yiming Ma, Song Hao y Ka Lok Chan. "Daily MODIS 250m two-band enhanced vegetation index (EVI2) time series computation based on autoencoders". En 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.

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High-quality vegetation index time series are crucial for timely and accurate phenological mapping. However, vegetation index time series with high temporal resolution (such as daily resolution), can be influenced by cloudiness, shadows, and atmospheric effect and affects the interpretation of vegetation growth. We proposed a method for computing a daily 250m two-band enhanced vegetation index (EVI2) time series using MOD09GQ surface reflectance products through a self-supervised neural network autoencoders model. We tested the consistency of EVI2 with conventional three-band EVI, its temporal stability, and sensitivity to aerosol. The results indicated this method is suitable to be applied to areas where atmospheric effects are not prominent. (tel: +86 15229367141, e-mail: rsliuxk@whu.edu.cn).

Informes sobre el tema "Vegetation series":

1

Melrose, Rachel, Jeff Kingwell, Leo Lymburner y 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.

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Roessler, Sebastian, Andreas Dietz y Samuel Schilling. Time series analysis of remotely sensed snow cover data: revealing permafrost thermal state and vegetation dynamics. International Permafrost Association (IPA), junio de 2024. http://dx.doi.org/10.52381/icop2024.158.1.

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Sekoni, Tosin, Mark Eberle, Matthew Balazik, Monica Chasten, Bob Collins, Brian Durham, Darrell Evans y 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.), septiembre de 2023. http://dx.doi.org/10.21079/11681/47581.

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This technical note is the fourth in a series about using native plant communities to achieve engineering and ecological purposes such as shoreline stabilization, structural enhancements, habitat creation, and ecosystem development. In this series, we demonstrate the utility of natural materials (specifically, native vegetation, oyster reefs, and coir logs) in living shoreline projects. Plant species and plant communities play critical roles in wave attenuation and sediment accretion in coastal areas. The application of vegetation in the coastal areas, especially on the East and Gulf Coasts, has focused heavily on the creation of living shorelines—serving both environmental and engineering purposes. This technical note documents the workshop conducted by the US Army Engineering Research and Development Center (ERDC) and hosted by the US Army Corps of Engineers’ (USACE) Philadelphia District (NAP) and Center for the Inland Bays. The goals of this technical note are (1) to demonstrate the application of native plant communities, oyster shells, and coir (coconut) materials and their installation techniques along shorelines to the engineering community; (2) to demonstrate how targeted vegetation establishment can facilitate ecosystem development along shorelines to improve engineering and environmental outcomes; and (3) to provide native vegetation installation techniques for living shorelines projects’ purposes.
4

Harris, Brian, Kathleen Harris, Navid Jafari, Jasmine Bekkaye, Elizabeth Murray y 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.), septiembre de 2023. http://dx.doi.org/10.21079/11681/47579.

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The development of regional restoration trajectories of marsh creation and nourishment projects is key to improved design, management, and implementation of adaptive management principles. Synthesizing information from multiple marsh creation projects constructed at various times but with consistent site characteristics and borrow material sources, helps elucidate restoration success in a specific region. Specifically, this technical note (TN) documents the process of determining a suitable study area, construction methods, and the current state of establishing sites in the Louisiana Gulf Coast that could be used for restoration trajectory development. This investigation compiled information from the construction phases, Landset 8 satellite imagery, and the most recent digital elevation model (DEM) to investigate elevation and vegetation establishment within these sites.
5

Mudge, Christopher y 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.), septiembre de 2021. http://dx.doi.org/10.21079/11681/42061.

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Herbicide selection is key to efficiently managing nuisance vegetation in our nation’s waterways. After selecting the active ingredient, there still remains multiple proprietary and generic products to choose from. Recent small-scale research has been conducted to compare the efficacy of these herbicides against floating and emergent species. Therefore, a series of mesocosm and growth chamber trials were conducted to evaluate subsurface applications of the following herbicides against submersed plants: diquat versus coontail (Ceratophyllum demersum L.), hydrilla (Hydrilla verticillata L.f. Royle), southern naiad (Najas guadalupensis (Sprengel) Magnus), and Eurasian watermilfoil (Myriophyllum spicatum L.); flumioxazin versus coontail, hydrilla, and Eurasian watermilfoil; and triclopyr against Eurasian watermilfoil. All active ingredients were applied at concentrations commonly used to manage these species in public waters. Visually, all herbicides within a particular active ingredient performed similarly with regard to the onset and severity of injury symptoms throughout the trials. All trials, except diquat versus Eurasian watermilfoil, resulted in no differences in efficacy among the 14 proprietary and generic herbicides tested, and all herbicides provided 43%–100% control, regardless of active ingredient and trial. Under mesocosm and growth chamber conditions, the majority of the generic and proprietary herbicides evaluated against submersed plants provided similar control.
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Swanson, David y Celia Hampton-Miller. Drained lakes in Bering Land Bridge National Preserve: Vegetation succession and impacts on loon habitat. National Park Service, enero de 2023. http://dx.doi.org/10.36967/2296593.

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The northern coastal plain of Bering Land Bridge National Preserve (BELA) lost lakes at an alarming rate over the first two decades of this century, including four lakes over 100 ha in size in 2018-2019 alone. To understand the effects of these lake drainages, we sampled vegetation of these lakes in 2019 (a reconnaissance visit) and 2021 (for the installation of permanent vegetation monitoring plots). We used these data to summarize the changes that occurred in the first three years after drainage, and to create vegetation maps from 3-m resolution satellite images coinciding with the visit dates. We used time series of these satellite images to study the rate of drainage and vegetation colonization on the lakes. We analyzed our existing data from older drained lake basins (estimated to be more than 200 years since drainage) and reviewed the literature on vegetation change in drained lakes to understand the vegetation changes that are likely in the future. Finally, we used a model of lake occupancy by loons developed by Mizel et al. (2021) to predict the effect of the 2018-2019 lake drainages on available loon habitat, using both our detailed maps of the four sampled drained lakes, and also data on all drained lakes over most of northern BELA derived from Landsat satellite images. Our results show that the four study lakes drained early in the summer, before the end of June, in 2018 (3 lakes) and 2019 (one lake). A combination of record warm weather and heavy snowfall made 2018 and 2019 especially favorable for lake drainage: thaw subsidence probably enlarged existing drainage outlet channels from the lakes, and large amounts of spring snowmelt runoff deepened the outlet channels by thermal erosion (the combination of thaw and erosion). Drainage exposed moist loamy sediment on the lake bottoms that was rapidly colonized by plants. Substantial vegetation cover developed by late summer in the same year as lake drainage in one lake, in the first post-drainage summer in a second lake, and during the 2nd year after drainage in the remaining two lakes. The first vegetation communities to develop consisted of just one or two dominant species, notably Eleocharis acicularis (spike rush), Equisetum arvense (horsetail), and/or Tephroseris palustris (mastodon flower). Other important early species were Arctophila fulva (pendant grass) and Rorippa palustris (yellow cress). By year 3, the communities had become more diverse, with significant cover by taller wetland graminoid species, including A. fulva, Eriophorum scheuchzeri, and Carex aquatilis. Frozen soil was observed in most locations on the lakes in July of 2021, suggesting that permafrost was forming on the lake bottoms. Comparison of the three-year trends in vegetation change with data from older lake basins suggest that ultimately most lake basins will develop wet tundra communities dominated by Carex aquatilis and mosses, with various low shrub species on acid, peat-dominated soils and permafrost; however, this process should take several centuries. The loon habitat model suggests that drainage essentially eliminated the potential habitat for Yellow-billed Loons on the four study lakes, because the residuals ponds were too small for Yellow-billed Loons to take flight from. A total of 17 lakes drained in northern BELA in 2018-2019. As a result, the potential Yellow-billed Loon nesting habitat in northern BELA probably decreased by approximately 2%, while habitat for Pacific Loons decreased less, by about 0.6%. Habitat for the more abundant Red-throated Loons probably increased slightly as a result of lake drainage, because of their ability to use the small residual ponds created by lake drainage.
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Herman, Brook, Paula Whitfield, Jenny Davis, Amanda Tritinger, Becky Raves, S. Dillon, Danielle Szimanski, Todd Swannack, Joseph Gailani y Jeffery King. Swan Island resilience model development; Phase I : conceptual model. Engineer Research and Development Center (U.S.), enero de 2023. http://dx.doi.org/10.21079/11681/46402.

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This report documents the development of an integrated hydrodynamic and ecological model to test assumptions about island resilience. Swan Island, a 25-acre island in Chesapeake Bay, Maryland, was used as a case study. An interagency, interdisciplinary team of scientists and engineers came together in a series of workshops to develop a simplified resilience model to examine the ability of islands to reduce waves and erosion and the impacts to nearby habitats and shorelines. This report describes the model development process and the results from this first key step: model conceptualization. The final conceptual model identifies four main components: vegetative biomass, island elevation, waves/currents, and sediment supply. These components interact to form and support specific habitat types occurring on the island: coastal dunes, high marsh, low marsh, and submerged aquatic vegetation. The pre-and post-construction field data, coupled with hydrodynamic ecological models, will provide predictive capabilities of island resilience and evaluations of accrued benefits for future island creation and restoration projects. The process and methods described can be applied to island projects in a variety of regions and geographic scales.
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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, julio de 2022. http://dx.doi.org/10.36967/2293951.

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National Park Service (NPS) managers face growing challenges resulting from the effects of climate change. In particular, as temperatures rise in coming decades, natural resource management in the western United States must cope with expectations for elevated severity and frequency of droughts. These challenges are particularly pronounced for vegetation managers in dryland environments. Developing adaptive strategies requires specific information about the expected magnitude of change in climate and drought conditions as well as insights into how those changes will affect important vegetation resources. This report describes research focused on Southeast Utah Group (SEUG) park units designed to provide information about exposure and sensitivity of perennial grasses to aridification. Analyses at larger regional scales are also reported for context and comparison. This report is a product of an ongoing climate adaptation collaboration between the U.S. Geological Survey (USGS), NPS, and Northern Arizona University. The study it summarizes contributes quantitative ingredients for vulnerability assessments that are needed in the Climate-Smart Conservation framework. As such, the results informed a series of climate adaptation workshops conducted between 2018 and 2021 for Colorado Plateau scientists and managers. This is a giant step forward in science-informed management. The information in this report can be used to craft management strategies that can be implemented at the right place and time for individual species of concern.
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Sartain, Bradley, Damian Walter y 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.), junio de 2024. http://dx.doi.org/10.21079/11681/48732.

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A series of 10 water-exchange studies were conducted from 2019 to 2021 at two sites, Clover Island and Osprey Point, within the McNary Pool of the Columbia River on the Oregon-Washington border. Six of the studies incorporated a barrier curtain or bubble curtain, whereas the other four studies did not include any device to mitigate water exchange. Once annually, diquat aquatic herbicide was applied concurrently with rhodamine water tracing (RWT) dye at the Osprey Point site (2019–2021) to control flowering rush. An additional plot, Clover Island Reference, served as the nontreated control to the Osprey Point treatment plot. Pre- and posttreatment vegetation surveys were conducted in 2019, 2020, and 2021 to determine flowering rush control, treatment impacts to water quality, and nontarget species response. This study sought to (1) document the use of barrier curtains and bubble curtains as potential methods for reducing water exchange and increasing herbicide concentration exposure times within potential flowering rush treatment areas, (2) evaluate bulk water exchange and selective control of flowering rush under varying reservoir operations, and (3) use the results from these studies to provide guidance for managing submersed flowering rush infestations on the McNary Pool, Columbia River, and similar run-of-the-river impoundments.
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Sekoni, Tosin, Mark Eberle, Brian Durham y 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.), septiembre de 2023. http://dx.doi.org/10.21079/11681/47588.

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This technical note is the third in a series about using native plant communities to enhance dredge material placement areas (DMPAs), confined disposal facilities (CDFs), and projects where dredged sediments are used for various engineering purposes. DMPAs and CDFs occur in numerous locations spanning different geographic locations nationwide. Oftentimes, these containment dikes are constructed using earthen materials. The materials are either barged in from an off-site location or obtained on-site from new or virgin materials, consisting of heavy clay particles and sediments removed from the nearby channel. In the Gulf Coast region of the United States, new or virgin materials are obtained during channel deepening activities using mechanical or hydraulic dredging methods. Examples of these dredging methods include hopper dredge, pipeline dredge, and excavator or bucket dredge. When materials are considered suitable for beneficial use purposes, and following environmental compliance, the materials are often used to construct containment dikes in DMPAs and CDFs. The project site used in this study—Beneficial Use Site 4A (BUS 4A)—used dredged material during its construction and has periodically received dredged material to maintain its target elevation of 2 ft (0.67 m) above the mean lower low water; hence, this site presents an opportunity for use as a demonstration study. Project goals include (1) demonstrating the use of native plant communities to provide structural stability, (2) introducing targeted vegetation establishment on DMPAs and CDFs as a management strategy to improve engineering and environmental outcomes, and (3) providing technology transfer to the U.S. Army Corps of Engineers (USACE) districts through hands-on planting techniques and installation of natural material (in this demonstration, coir logs).

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