Abstract
In the present study, a regression-based approach was adopted for retrieval of leaf-area index (LAI) and chlorophyll-content index (CCI) using Resourcesat-2 AWiFS data. Multi-temporal satellite data were utilised to generate cotton and rice crop masks. Three vegetation indices (VIs) were computed from AWiFS data, which were further regressed with ground-measured LAI and CCI values to generate empirical models along with their regression parameters. The best-fit models were adopted for inversion to generate crop-specific spatial maps of biophysical parameters for both cotton and rice crops. The geo-spatial products of crop biophysical parameters were further validated using in-situ observations.
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Acknowledgements
We express our sincere thanks to Dr. V.K. Dadhwal, Director, NRSC, and Dr. Dibyendu Dutta, General Manager, RRSC-East, NRSC, for their constant encouragement and suggestions. We are also thankful to Dr. Karun Kumar Chaudhary, NRSC, for his support during the ground-based data collection. We also duly acknowledge the anonymous reviewers for their kind suggestions.