An early assessment of national crop development conditions while the plants are still in the fields is highly needed to calculate correctly projections for decision-making and policies related to government planning and food security. The aim of this study was to evaluate the suitability of NOAA /AVHRR (National Oceanic and Atmospheric Administration / Advanced Very High Resolution Radiometer) to detect changes in vegetation conditions, due to water stress during soybean crop, by means a combination of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI). Both LST and NDVI data were combined and compared in a pixel basis over a soybean crop area in Rio Grande do Sul State. The predicted theoretical inverse relationship for the combination of LST and NDVI was detected. An average increase of LST was observed in a normal crop cycle ( from 301.02 K to 308.36 K) compared to a crop cycle under water stress condition. An average reduction in NDVI was observed for normal crop cycle development (from 0.65 to 0.53) compared to a crop cycle under drought-induced effects. It was observed a higher correlation of municipality yield with LST (R2=0.78) than NDVI (R2=0.59). Results obtained indicate that the aggregation of AVHRR images, from different institutions, provides the appropriate combination of spatial and temporal data LST and NDVI in order to detect the occurrence of drought stress, as well as its intensity, characterizing the conditions of the crop cycle development of soybean.
sensing; drought; land surface temperature; vegetation index
