About

About UrbanWatch

UrbanWatch is a 1-meter resolution, open-access land cover and land use (LCLU) database for major cities across the conterminous United States. It was initially developed in 2021 by the Laboratory for Remote Sensing and Environmental Change (LRSEC), directed by Dr. Gang Chen at the University of North Carolina at Charlotte. UrbanWatch currently covers 23 cities and contains 9 LCLU classes, i.e., building, road, parking lot, tree canopy, grass/shrub, water, agriculture, barren, and others, with an overall accuracy of 91.52% and Kappa statistic of 0.844.

The database was produced by a novel Fine-resolution, Large-area Urban Thematic information Extraction (FLUTE) framework, which builds upon state-of-the-art semi-supervised learning and deep learning architectures and has been trained with a new benchmark database containing 52.43 million labeled pixels to capture diverse LCLU types and spatial patterns. FLUTE addresses several challenges that frequently occur in large-area, high-resolution urban mapping, including the view-angle effect, high intraclass and low interclass variation, and multiscale land cover.