Scholars Bulletin (SB)
Volume-8 | Issue-11 | 300-311
Subject Category: Geography
Advance Remote Sensing Applications for Agricultural Damage Assessment: A Case Study of Boone County, Iowa
Ismail Alatise, Adriana Chamorro
Published : Dec. 14, 2022
Abstract
Derecho windstorms are extreme weather events capable of causing catastrophic damage to agricultural systems across the U.S. Midwest. Using methodologies relevant to Indigo Agriculture's precision farming approach, this case study applies advanced remote sensing techniques to examine the significant impacts of the August 2020 Derecho windstorm on agricultural fields in Boone County, Iowa, using Sentinel-1 Synthetic Aperture Radar (SAR) data. The research quantifies damage extent across crop types with particular focus on corn and soybean fields, analyzes damage severity patterns, and investigates spatial variability of impacts. SAR imagery acquired 5 days post-windstorm revealed detectable changes in backscatter values attributable to structural damage in crops, allowing for comprehensive damage assessment across the study area. Results demonstrate variable damage patterns both within and between crop types, with corn exhibiting greater susceptibility to wind damage than soybeans due to structural differences. The analysis identified 1-10% backscatter variations in control points, while damaged areas displayed more significant deviations. While multiple factors potentially influence backscatter values, including soil moisture conditions, vegetation maturity, crop growth stage, and environmental changes, the temporal proximity of image acquisition to the windstorm event supports the attribution of observed changes to wind damage. This research demonstrates approaches applicable to Indigo Agriculture's precision agriculture services and contributes valuable insights for agricultural risk assessment and disaster management while showing the efficacy of SAR data for rapid post-windstorm crop damage evaluation. The methodology presented can inform future applications of remote sensing in monitoring agricultural disaster impacts, supporting more targeted response and recovery efforts in affected farming communities, and enhancing agricultural technology companies' damage assessment capabilities.