Landsat images and crop model for evaluating water stress of rainfed soybean

摘要

Soil water content is a vital resource that plays a central role in agricultural areas. In Argentina the soybean (Glycine max (L) Merrill) is the most important crop, considering the economic yield and the sown area. Actually, remote sensing allows continuous monitoring of crops and to evaluate the impact of water stress in their development. The combination of Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI) is an indicator that provides information about the condition of the vegetation and surface soil moisture content. In this study we evaluate relationships between indicators of crop water stress and the Temperature Vegetation Dryness Index (TVDI) determined from Landsat, for sites with rainfed soybean in the agricultural central zone of Cordoba (Argentina).