Monitoring Forest Dynamics in Rwanda

By Langley Rwanda Eco Forecasting Team , posted on August 13th, 2012 in DEVELOP Virtual Poster Session

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An NDVI image using MODIS Terra data of the Gishwati Forest in the Western Province of Rwanda. This image depicts the mean vegetation index across the dry seasons from 2001-2011.

NDVI using MODIS Terra of the Gishwati Forest in the Western Province of Rwanda. This image depicts the mean vegetation index across the dry seasons from 2001-2011.

Team Location: Langley Research Center

Authors: Quinten Geddes, University of Montana; Kevin Butler, Clark University; Lara Janse van Vuuren, University of Virginia; Talia Fox, Harvard University; Faith Mwiza, California Baptist University; Joshua Abe, Virginia Tech; Andy Li, Marriotts Ridge; Aditi Sharma, University of Miami.

Advisors/Mentors: Dr. Kenton Ross

Other Acknowledgements: Madeleine Nyiratuza, Gishwati Area Conservation Program; Adrie Mukashema, National University of Rwanda

Abstract: As the most densely populated country in Africa, Rwanda relies heavily on a limited supply of natural resources to sustain its agrarian economy. Population pressures, economic volatility, and the aftermath of genocide have placed particular stress on the Gishwati Forest in Rwanda’s Western Province. Deforestation for food and fuel production has disrupted the local climate, soil structure, and topography, leading to increased erosion, landslides and flooding. Once 280 square kilometers, by 1995 the Gishwati Forest was only 6 square kilometers. The Rwandan government and international non-governmental organizations have taken initiatives to reverse the degradation, which would benefit from more accurate evaluation using remote sensing technology. This study filled the gaps in the history of the Gishwati Forest since 1982, using NASA’s Earth Observing System, specifically Landsat 5 and AVHRR. In collaboration with partner organizations, we developed a robust, yet simple-to-use, forest monitoring tool employing MODIS NDVI products that provides annual estimates of the forest’s health.

Summer VPS > Ecological Forecasting

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