International audienceSatellite images allow the acquisition of large-scale ground vegetation. Images are available along several years with a high acquisition rate. Such data are called satellite image time series (SITS). We present a method to analyse an SITS through the characterization of the evolution of a vegetation index (NDVI) at two scales: annual and multi-annual. We evaluate our method on SITS of the Senegal from 2001 to 2008 and we compare our method to a clustering of long time series. The results show that our method better discriminates regions in the median zone of Senegal and locates fine interesting areas
Up-to-date land cover maps are important for biodiversity monitoring as they are central to habitat ...
The use of satellite image time series analysis and machine learning methods brings new opportunitie...
International audienceThe aim of this study is to assess the potential of satellite image time serie...
International audienceSatellite images allow the acquisition of large-scale ground vegetation. Image...
Satellite images time series have been used to study land surface, such as identification of forest,...
Current earth observation data repositories enable us to extract observations of the same geographic...
Satellite images time series have been used to study land surface, such as identification of forest,...
International audienceThis paper presents a segmentation method of satellite images time series (SIT...
International audienceThe expansion of satellite technologies makes remote sensing data abundantly a...
International audienceNowadays, satellite images are widely exploited in many fields including agric...
Can satellite imagery in conjunction with a meta population model provide further relevant parameter...
Abstract This thesis aims to advance the analysis of nonlinear trends in time series of vegetation d...
Thanks to the freely availability of several Satellite Image Time Series (SITS) covering the Earth, ...
AbstractThe vegetation index is considered a good indicator of vegetation behavior and can contribut...
International audienceDuring the last decades, satellites have acquired incessantly high resolution ...
Up-to-date land cover maps are important for biodiversity monitoring as they are central to habitat ...
The use of satellite image time series analysis and machine learning methods brings new opportunitie...
International audienceThe aim of this study is to assess the potential of satellite image time serie...
International audienceSatellite images allow the acquisition of large-scale ground vegetation. Image...
Satellite images time series have been used to study land surface, such as identification of forest,...
Current earth observation data repositories enable us to extract observations of the same geographic...
Satellite images time series have been used to study land surface, such as identification of forest,...
International audienceThis paper presents a segmentation method of satellite images time series (SIT...
International audienceThe expansion of satellite technologies makes remote sensing data abundantly a...
International audienceNowadays, satellite images are widely exploited in many fields including agric...
Can satellite imagery in conjunction with a meta population model provide further relevant parameter...
Abstract This thesis aims to advance the analysis of nonlinear trends in time series of vegetation d...
Thanks to the freely availability of several Satellite Image Time Series (SITS) covering the Earth, ...
AbstractThe vegetation index is considered a good indicator of vegetation behavior and can contribut...
International audienceDuring the last decades, satellites have acquired incessantly high resolution ...
Up-to-date land cover maps are important for biodiversity monitoring as they are central to habitat ...
The use of satellite image time series analysis and machine learning methods brings new opportunitie...
International audienceThe aim of this study is to assess the potential of satellite image time serie...