RF-CLASS: A Remote-sensing-based Interoperable Web service system for Flood Crop Loss Assessment
Abstract
Flood is one of the worst natural disasters in the world. Flooding often causes significant crop loss over large agricultural areas in the United States. Two USDA agencies, the National Agricultural Statistics Service (NASS) and Risk Management Agency (RMA), make decisions on flood statistics, crop insurance policy, and recovery management by collecting, analyzing, reporting, and utilizing flooded crop acreage and crop loss information. NASS has the mandate to report crop loss after all flood events. RMA manages crop insurance policy and uses crop loss information to guide the creation of the crop insurance policy and the aftermath compensation. Many studies have been conducted in the recent years on monitoring floods and assessing the crop loss due to floods with remote sensing and geographic information technologies. The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS), being developed with NASA and USDA support, aims to significantly improve the post-flood agricultural decision-making supports in USDA by integrating and advancing the recently developed technologies. RF-CLASS will operationally provide information to support USDA decision making activities on collecting and archiving flood acreage and duration, recording annual crop loss due to flood, assessing the crop insurance rating areas, investigating crop policy compliance, and spot checking of crop loss claims. This presentation will discuss the remote sensing and GIS based methods for deriving the needed information to support the decision making, the RF-CLASS cybersystem architecture, the standards and interoperability arrangements in the system, and the current and planned capabilities of the system.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2014
- Bibcode:
- 2014AGUFMNH11B3700D
- Keywords:
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- 4331 Disaster relief;
- 4335 Disaster management;
- 4337 Remote sensing and disasters;
- 4339 Disaster mitigation