Remote sensing-based site suitability assessment and selection of Rabi crop cultivation areas following flood events - Arnob Bormudoi; Masahiko Nagai; Gilbert Hinge; Vaibhav Katiyar; Dorj Ichikawa; Tsuyoshi Eguchi; Mohamed A. Hamouda (Geocarto International)
Assessing the impact of floods on crop cultivation is critical for ensuring food security and resilience in flood-prone regions. This study relied on cloud-free imagery from Landsat to construct six vegetation indices. These indices were used to conduct a comparative analysis of the flood disaster of 2022 in Pakistan. A random forest classifier was employed on pre-flood images to identify agricultural zones. A model was developed using two indices, Brightness (DBSI) and Wetness (TCW), along with the vegetative index of crop vigor (MSAVI), during the pre-flood months of 2021. The model’s accuracy was validated and exhibited an RMSE of 0.03 in predicting MSAVI values. The model was used to forecast MSAVI during post-flood periods. Spatial analysis identified approximately 30-47% of the study area as ‘Suitable’ and 46-64% as 'Highly suitable’ for early recultivation of Rabi Crops. The approach helps in planning for fast agricultural recovery in the aftermath of floods.