Risky Business: Using NASA EOS to Determine Areas Most at Risk of Soil Erosion

EarthzineDEVELOP Summer 2013 VPS, DEVELOP Virtual Poster Session, Original

Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band data (black and white gradient) compared to settlement locations derived from Landsat 8 (green) for Rwanda (blue outline).

Team Location: Langley Research Center, Hampton, Virginia; and Wise County Clerk of Court’s Office, Wise, Virginia


Dieudonne Dusenge (Oklahoma Christian University)

Abednego Mayon (East Tennessee State University)

Emmanuel Muzungu (Oklahoma Christian University)

Martine Nezerwa (Oklahoma Christian University)

Nirav Patel (University of Florida)

Merna Saad (Christopher Newport University)

Angela Unrein (University of Kansas)

Past/Other Contributors:

Rwanda Ecological Forecasting Team Summer 2012

Rwanda Agriculture Team Summer 2012

Rwanda Ecological Forecasting & Agriculture Team Fall 2012

Rwanda Ecological Forecasting & Agriculture II Team Spring 2013


Kenton Ross, Ph.D. (NASA, DEVELOP National Science Advisor)

Dewayne Cecil, Ph.D. (Global Science and Technology Inc., National Climatic Data Center)


Climate and topography present a continuing challenge to the Republic of Rwanda’s citizens, many of whom engage in subsistence agriculture. A combination of high seasonal rainfall and the population-driven expansion of cultivation onto steeply graded lands have led to severe soil degradation. Erosion has decreased crop yields, forcing further expansion of cultivation and hampering efforts to protect and restore scarce forest lands. Overgrazing and deforestation also contribute to soil nutrient depletion and erosion.åÊ Over 90 percent of the household energy in the Central Africa Great Lakes Region, which includes Rwanda, is derived from biomass, contributing to rapid deforestation. The Western Province of Rwanda is a hilly and mountainous area with high seasonal rainfall, high natural soil erodibility, and has been heavily deforested. Because of this, it is estimated that Rwanda loses 14 million tons of soil each year. This severe volume of soil erosion, coupled with the lack of forest ecosystems returning nutrients to the soil, has dramatically lowered soil productivity and caused flooding throughout the country.

Considering these environmental issues which pose a high risk to Rwandans, this study focused on using NASA’s Earth observations to identify areas more susceptible to soil erosion based on hydrology, geographic analysis and land cover.åÊ Soil erosion risk was assessed using the Revised Universal Soil Loss Equation (RUSLE), which is dependent on the following factors: erosivity, soil erodibility, slope length and slope steepness, and cover management. The geographic data was acquired from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor on the Terra satellite using the Digital Elevation Model (DEM). A land cover classification map of Rwanda completed by previous DEVELOP teams was used to analyze land cover management.åÊ A soil type map was used to derive the soil erodibility data.åÊ Finally, rainfall data was acquired from the Modern Era Retrospective-Analysis for Research and Application (MERRA) to derive erosivity data.åÊ All factors were then processed and analyzed in ArcGIS to create a final map of the Western Province in Rwanda to show susceptibility to soil erosion.

The government of Rwanda has passed a policy which prohibits any agricultural practices above a certain slope. However, because there are no strong strategies in place for monitoring human settlement changes over time, the government has not been successful in enforcing this law. Therefore, the second part of this project was to locate human settlements using night light data. The day/night band from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) satellite was acquired and integrated into the AfriPop land cover data (Dr. Andrew Tatem, University of Florida) to identify human settlements. The VIIRS data adds to the settlements mapped by the AfriPop project, which derived its settlements from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. The AfriPop Project’s mapping method was then applied to create accurate and precise population density estimates. The study seeks to enhance government of Rwanda decision-making through the use of NASA satellites remote sensing data.

Return to the Summer 2013 VPS page.