Chignell, Stephen, authorAnderson, Ryan, authorWakie, Tewodros, author2017-01-122017-01-122014http://hdl.handle.net/10217/179305Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration.The Bale Mountains of south-central Ethiopia comprise one of Africa's least-studied massifs, and are home to the world-renowned Bale Mountain National Park. A designated Biodiversity Hotspot, the area also serves as the headwaters for five major rivers that flow out of the mountains, supporting 12 million people in the arid lowlands to the east. In recent years, development in the surrounding area has forced many agro-pastoralists into the highlands, and approximately 40,000 people now live within the park boundaries. Mapping the location and extent of the region's water resources has been identified as a key research need for local park officials and conservation groups as they work to sustainably accommodate this massive influx of people and livestock. Of particular concern are the region's numerous alpine lakes and wetlands, as they are essential for wildlife habitat, water quality, and discharge timing for both upstream and downstream users throughout the dry season. This study used environmental indices derived from Landsat 8 Operational Land Imager/Thermal Infrared data, topographic variables, and species distribution models to map all perennial alpine lakes and wetlands in the Bale Mountains. Resulting models of wetlands and lakes had classification accuracies of 97% and 100%, respectively. These represent the first comprehensive maps of their kind in Bale, and will facilitate the targeting of conservation and research efforts in the region. Additionally, the methodology is applicable in other remote areas around the world where field data is sparse and regular monitoring is needed.born digitalPresentation slidesengGISremote sensingLandsatmaximum entropy modelingwetlandheadwatersTextThis article is open access and distributed under the terms and conditions of the Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).