Self-Organizing Map for surface characterization in time series

Monitoring changes in the vegetation cover during the intercrop season is of a special interest in intensive agricultural regions. The presence of bare soils leads to detrimental environmental effects such as soil erosion or water quality degradation. To identify and monitor winter land cover at a regional scale in the Brittany region in France, data from the moderate resolution imaging spectroradiometer (MODIS) low resolution time series were used. This study examines the self-organizing map (SOM) for classifying winter land cover with MODIS time series in agricultural and fragmented landscapes. Field data and high resolution images have been used to generate two sets of pixels for training and validation. A comparison between the suggested method and NDVI thresholding is presented.