Project Team: Appalachia Energy Team
Team Location: Wise County Clerk of Court’s Office, Wise, Virginia
Changes in NDVI observed between 2004 and 2014 in the Central Appalachian region. Image
Credit: Appalachia Energy Team.
Authors:
Dieudonne Dusenge, Project Lead (Mountain Empire Community College)
Andrew Foxx (Radford University)
Asongayi Venard (East Tennessee State University)
Jessica Huff (Mountain Empire Community College)
Rohini Swaminathan (Mountain Empire Community College)
Mentors/Advisors:
Dr. Kenton Ross (NASA DEVELOP, National Science Advisor)
Abstract:
The Appalachian Mountains are known for their natural forests. However, these forests are under pressure from human activities such as residential development, agriculture and logging. The forests also are increasingly affected by forest fires, invasions of pests such as the gypsy moth, and other natural factors. In addition, biomass energy production destroys a large amount of healthy trees. During the last 20 years, tens of thousands of acres of natural forest have been logged, many of them replanted as pine tree plantations. As a result of these threats, ecosystems are collapsing and species are being rendered extinct. This project utilized data from Landsat 8’s Operational Land Imager (OLI) for forest monitoring to derive indices like Normalized Differential Vegetation Index (NDVI) and Relative Differenced Normalized Burn Ratio (RdNBR) to identify unhealthy forests. Pan-sharpened Landsat 8 imagery provided targeted higher resolution analyses for areas demonstrated by Aqua and Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) to have the potential for harvest. MODIS and VIIRS provided vegetation dynamics and phenology products, along with fire-related datasets like fire occurrences and scarring. Partnering with Virginia’s County of Wise and the Virginia Department of Agriculture and Forestry, this project facilitated the use of NASA Earth observations to identify unhealthy forests in this region.