Revolutionizing Rwandan Agriculture by Utilizing NASA Earth Observations

EarthzineDEVELOP Summer 2014 VPS, DEVELOP Virtual Poster Session, Original

Project Team: Rwanda Agriculture Team
Team Location: Wise County Clerk of Court’s Office, Wise, Virginia

Landsat images used to derive Modified Normalized Difference Water Index (MNDWI) to enhance the identification of regions transformed from marshlands to rice fields. Image Credit: Rwanda Agriculture Team.

Landsat images used to derive Modified Normalized Difference Water Index (MNDWI) to enhance the identification of regions transformed from marshlands to rice fields. Image Credit: Rwanda Agriculture Team.

Authors:
Daria Blach, Project Lead (The University of Virginia’s College at Wise)
Faith Mwiza (Mountain Empire Community College)
Roger Manzi Dusabimana (California Baptist University)
Emmanuel Muzungu (Mountain Empire Community College)

Mentors/Advisors:
Dr. Kenton Ross (NASA DEVELOP, National Science Advisor)
Dr. DeWayne Cecil (Global Science and Technology, Inc.)

Past/Other Contributors:
Merna Saad (Christopher Newport University)
Zachary Tate (The University of Virginia’s College at Wise)

Abstract:
Agriculture is the backbone of Rwanda’s economy, accounting for a third of the country’s Gross Domestic Product (GDP). Agriculture also constitutes the main economic activity for rural households, acting as the main source of income. The sector meets 90 percent of the national food needs and generates more than 70 percent of the country’s export revenues. In an effort to reduce poverty and grow the economy, the government has outlined a number of programs which include the Rural Sector Support Program (RSSP), and National Rice Policy (NRP). The goal of the NRP is attaining self-reliance and competitiveness in rice production whereas the RSSP’s purpose is the development of marshlands to rice fields in order to increase rice cultivation and yields.

In this project, NASA Earth observations, such as Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI), were used to monitor rice fields. Crop production models from Decision Support Systems for Agrotechnology Transfer (DSSAT) were used to estimate rice yields in identified RSSP sites. In addition, modern practices have been implemented at the Land Husbandry, Water Harvesting, and Hillside Irrigation (LWH) developmental sites. Soil erosion susceptibility maps were created at the LWH sites across Rwanda before and after the implementation of modern practices. Partnering with the Rwanda Ministry of Agriculture and Animal Resources and the World Bank, the team derived meaningful maps to monitor agriculture and provide information to policy decision-makers.

 

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