Application of remote sensing and crop modeling for rice in Andhra Pradesh, India

Document Type

Conference Proceeding

Publication Date

1-1-2020

Abstract

The Satellite based Rice Monitoring System for Andhra Pradesh (APSRMS) project aims to support capacity development by establishing and maintaining a rice monitoring system that provides regular crop condition updates to the state government and rapid damage assessment in the event of extreme climate conditions to support intervention by government and relevant stakeholders. The project utilizes freely available Synthetic Aperture Radar (SAR) from Sentinel-1A (C-band, vv and vh polarization SAR with 20 m spatial resolution and 12 days temporal resolution) and Sentinel-2 (multispectral optical data with 10 m spatial resolution and 5 days temporal resolution) from the Copernicus Programme of European Space Agency (ESA), and LANDSAT-8 (multispectral optical data with 30 m spatial resolution and 16 days temporal resolution) from the National Aeronautics and Space Administration (NASA) for rice area and start of season estimation and ORYZA crop growth model for yield estimation. MAPscape-RICE, a fully automated software for generation of rice area, start of season, and leaf area index (LAI) estimates from multi-temporal SAR and optical data was used in conjunction with Rice-YES, a software linking remote sensing derived information with ORYZA crop growth model. The project started in two districts (Nellore and West Godavari) in 2016/17 Rabi (dry) season, followed by expansion of monitoring activities to four districts (East Godavari, West Godavari, Guntur, and Krishna) in 2017 Kharif (rainy) season, and to seven districts (East Godavari, West Godavari, Nellore, Chitoor, Kadapa, Prakasam, and Kurnool) in 2017/18 Rabi season, and to the entire 13 districts of Andhra Pradesh by 2018 Kharif season. The project involved a rigorous rice classification validation exercise through physical field verification visits to ensure rice area products at district, block, and village granularity were at acceptable accuracy of 85% or more. Rice area and yield estimates were also compared against values obtained from government source. Mitigating rice farmers' production loss thru implementation of crop insurance is a key area of use case of this Satellite based rice monitoring system with the goal of timely rice production provision to be used by crop insurance companies to validate farmer's claims for insurance payouts in case of loss triggered by drought, floods, or cyclones. This study demonstrates the utility of remote sensing and crop modeling technologies to support the government of Andhra Pradesh, India in near-real time rice production monitoring and conducting damage assessment in case of unfavorable climate events such as drought, floods, or cyclones affecting small-holder rice farmers. Likewise, it demonstrates the importance of regular and timely rice area monitoring and pre-harvest yield forecast as critical requirements to prepare for extreme climate events with a case study involving damage assessment from cyclone Titli that affected rice production in Srikakulam district during 2018 Kharif season.

Publication Source (Journal or Book title)

40th Asian Conference on Remote Sensing, ACRS 2019: Progress of Remote Sensing Technology for Smart Future

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