Pixel class probabilities investigations data
Description
# Pixel class probabilities investigations data These data are associated with the manuscript: Land cover pixel class probabilities create customizable layers for forested and urban landscapes Daniel T. Myers1* (ORCID 0000-0002-1932-5775), Diana Oviedo-Vargas1, Melinda Daniels1, Yog Aryal2 1 Stroud Water Research Center, 970 Spencer Road, Avondale, Pennsylvania 19311, USA 2 Department of Geography, Indiana University Bloomington, Student Building 120, 701 E. Kirkwood Avenue, Bloomington, IN 47405, USA * Corresponding author (dmyers@stroudcenter.org) They can be analyzed using the following scripts: https://github.com/Danmyers901/Calibration/tree/master/Pixel_class_probabilities Our data includes water quality measurements from the United States National Park Service, and remotely sensed landcover images from Dynamic World. Water quality data were downloaded from the Water Quality Portal at https://www.waterqualitydata.us/ using the Project ID search term “NCRNWQ01”. Brown, C. F. et al. Dynamic World, Near real-time global 10 m land use land cover mapping. Scientific Data 2022 9:1 9, 1–17 (2022). Norris, M., Pieper, J., Watts, T. & Cattani, A. National Capital Region Network Inventory and Monitoring Program Water Chemistry and Quantity Monitoring Protocol Version 2.0 Water chemistry, nutrient dynamics, and surface water dynamics vital signs. Natural Resource Report NPS/NCRN/NRR—2011/423 (2011). References for other data sources and packages we used for model development and analyses are below: III, K. G. R. et al. StreamStats, version 4. Fact Sheet (2017) doi:10.3133/FS20173046. Jin, S. et al. Overall Methodology Design for the United States National Land Cover Database 2016 Products. Remote Sensing 2019, Vol. 11, Page 2971 11, 2971 (2019). Lindsay, J. B. The Whitebox Geospatial Analysis Tools Project and Open-Access GIS. (2022). United States Department of Agriculture. National Agriculture Imagery Program (NAIP) - Catalog. https://catalog.data.gov/dataset/national-agriculture-imagery-program-naip. For more information contact: Dan Myers, PhD Postdoctoral Associate Stroud Water Research Center 970 Spencer Road, Avondale, PA 19311 610-268-2153 ext. 1274 dmyers@stroudcenter.org www.stroudcenter.org
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Steps to reproduce
Google Earth Engine (GEE) and R scripts are available on GitHub to reproduce the analyses: https://github.com/Danmyers901/Calibration/tree/master/Pixel_class_probabilities