Description: High resolution Land Use/Land Cover (LULC) dataset for Denver, CO. Nine land cover classes were mapped: (1) structures, (2) impervious surfaces, (3) water, (4) grassland/prairie, (5) tree canopy, (6) irrigated lands/turf, (7) barren/rock, (8) cropland, and (9) shrubland/scrubland. The primary sources used to derive this land cover layer were 2020 orthophotos, 2020 LiDAR data, and 2019 NAIP imagery. Ancillary data sources included GIS data provided by Denver, CO via Sanborn map company or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping, a detailed manual review of the dataset was carried out at a scale of 1:4000 and all observable errors were corrected. The overall accuracy of the dataset in 97%