Mapping mountain peatlands and wet meadows using multi-date, multi-Sensor remote sensing in the Cordillera Blanca, Peru

Rodney Chimner, Michigan Technological University
Laura Bourgeau-Chavez, Michigan Technological University
Sarah L. Grelik, Michigan Technological University
John A. Hribljan, Michigan Technological University
Ana Maria Planas Clarke, Michigan Technological University
Molly Polk, University of Texas at Austin
Erik Lilleskov, USDA Forest Service
Beatriz Fuentealba, The Mountain Institute

© US Government 2019. Publisher's version of record:


Wetlands (called bofedales in the Andes of Peru) are abundant and important components of many mountain ecosystems across the globe. They provide many benefits including water storage, high quality habitat, pasture, nutrient sinks and transformations, and carbon storage. The remote and rugged setting of mountain wetlands creates challenges for mapping, typically leading to misclassification and underestimates of wetland extent. We used multi-date, multi-sensor radar and optical imagery (Landsat TM/PALSAR/RADARSAT-1/SRTM DEM-TPI) combined with ground truthing for mapping wetlands in Huascarán National Park, Peru. We mapped bofedales into major wetland types: 1) cushion plant peatlands, 2) cushion plant wet meadows, and 3) graminoid wet meadows with an overall accuracy of 92%. A fourth wetland type was found (graminoid peatlands) but was too rare to map accurately, thus it was combined with cushion peatland to form a single peatland class. Total wetland area mapped in the National Park is 38,444 ha, which is 11% of the park area. Peatlands were the most abundant wetland type occupying 6.3% of the park, followed by graminoid wet meadows (3.5%) and cushion wet meadows (1.3%). These maps will serve as the foundation for improved management, including restoration, and estimates of landscape carbon stocks.