Landcover map for the central region of the Yukon-Kuskokwim Delta, Alaska ...

• Main Authors: Ludwig, Sarah, Natali, Susan M., Schade, John D., Powell, Margaret, Fiske, Greg, Commane, Roisin
• Format: Dataset
• Language: English
• Published: Dryad 2022
• Subjects: FOS Earth and related environmental sciences; Arctic; landcover; vegetation; Tundra; waterbody; Lake; Yukon; Climate change; Kuskokwim; permafrost; Alaska
• Online Access: https://dx.doi.org/10.5061/dryad.bnzs7h4fn; https://datadryad.org/stash/dataset/doi:10.5061/dryad.bnzs7h4fn

Climate change is causing an intensification in tundra fires across the Arctic, including the unprecedented 2015 fires in the Yukon-Kuskokwim (YK) Delta. The YK Delta contains extensive surface waters (∼33% cover) and significant quantities of organic carbon, much of which is stored in vulnerable permafrost. Inland aquatic ecosystems act as hot-spots for landscape CO2 and CH4 emissions and likely represent a significant component of the Arctic carbon balance, yet aquatic fluxes of CO2 and CH4 are also some of the most uncertain. We measured dissolved CH4 and CO2 concentrations (n = 364), in surface waters from different types of waterbodies during summers from 2016 to 2019. We used Sentinel-2 multispectral imagery to classify landcover types and area burned in contributing watersheds. We develop a model using machine learning to assess how waterbody properties (size, shape, and landscape properties), environmental conditions (O2, temperature), and surface water chemistry (dissolved organic carbon ... : This landcover classification was created for the purposes of determining watershed landcover as potential drivers of downstream waterbody CH4 and CO2 concentrations. The region of interest is a watershed in the central portion of the Yukon-Kuskokwim Delta, Alaska, where field observations were based. The landcover map has been clipped to the watershed extent, and included as a shapefile. We created a 10-m resolution landcover map for the region of interest to determine the presence and abundance of various terrestrial, wetland, surface waterbodies, and disturbed areas in sample watersheds. We used an unsupervised k-means algorithm (Google Earth Engine, “wekaKMeans”) with the surface reflectance raw bands, derived bands (NDWI, NDVI), slope, and elevation as inputs for the classification. The Alaska Interagency Coordination Center historical wildfire database was used for wildfire delineations. Wildfires in the region of interest included fire scars from the 1970s, 1990s, and early 2000s, collectively ...