Abstract

Availability of remote sensed data provides powerful access to the spatial and temporal information of the earth surface Real-time earth observation data acquired during a cropping season can assist in assessing crop growth and development performance As remote sensed data is generally available at large scale rather than at field-plot level use of this information would help to improve crop management at broad-scale Utilizing the Landsat TM ETM ISODATA clustering algorithm and MODIS Terra the normalized difference vegetation index NDVI and enhanced vegetation index EVI datasets allowed the capturing of relevant rice cropping differences In this study we tried to analyze the MODIS Terra EVI NDVI February 2000 to February 2013 datasets for rice fractional yield estimation in Narowal Punjab province of Pakistan For large scale applications time integrated series of EVI NDVI 250-m spatial resolution offer a practical approach to measure crop production as they relate to the overall plant vigor and photosynthetic activity during the growing season The required data preparation for the integration of MODIS data into GIS is described with a focus on the projection from the MODIS Sinusoidal to the national coordinate systems However its low spatial resolution has been an impediment to researchers pursuing more accurate classification results and will support environmental planning to develop sustainable land-use practices These results have important implications for parameterization of land surface process models using biophysical variables estimated from remotely sensed data and assist for forthcoming rice fractional yield assessment