Remote sensing-based site suitability assessment and selection of Rabi crop cultivation areas following flood events

• Published in: Geocarto international Vol. 39; no. 1
• Main Authors: Bormudoi, Arnob, Nagai, Masahiko, Hinge, Gilbert, Katiyar, Vaibhav, Ichikawa, Dorj, Eguchi, Tsuyoshi, Hamouda, Mohamed A.
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 01.01.2024
• Subjects: Crop resilience; flood impact analysis; food security; Pakistan; rabi crop
• ISSN: 1010-6049; 1752-0762
• DOI: 10.1080/10106049.2024.2356841

AbstractAssessing 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.