@inproceedings{e316c5c34e844c70af3479b4ba9f7b07,
title = "MAPPING SURFACE WATER EXTENT IN MAINLAND ALASKA USING VIIRS SURFACE REFLECTANCE",
abstract = "Surface water is crucial to ecosystems in Alaska. Precisely mapping the dynamic surface water extent in this region is required by a wide range of environmental studies. However, most existing inundation products cannot reveal the distribution of surface water in mainland Alaska at high spatiotemporal scales. To bridge this gap, this study developed a framework to generate subpixel surface water fraction (SWF) maps from the 8-day VIIRS surface reflectance composites at the 1 km resolution through a random forest regression. Assessment of map accuracy resulted in an r2 value of 0.839 and a root mean square error (RMSE) of 12.17\%. With the adoption of a proper terrain shadow preprocessing procedure and more training samples in rugged terrain, the developed framework can be easily extended to produce accurate time-series SWF maps over the entire Arctic-Boreal region on a weekly basis, particularly during the summer season.",
keywords = "Alaska, SWF, VIIRS, random forest, surface reflectance",
author = "Wenlong Feng and Huiran Jin",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; Conference date: 12-07-2021 Through 16-07-2021",
year = "2021",
doi = "10.1109/IGARSS47720.2021.9554155",
language = "English (US)",
series = "International Geoscience and Remote Sensing Symposium (IGARSS) ",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6120--6123",
booktitle = "IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings",
address = "United States",
}