2022 High resolution land cover dataset for State of Vermont. Eight land cover classes were mapped: (1) tree canopy, (2) grass/shrubs, (3) bare soil, (4) water, (5) buildings, (6) roads, (7) other impervious, and (8) railroads. The primary sources used to derive this land cover layer were 2016 LiDAR data and 2021/2022 NAIP imagery. Ancillary data sources included GIS data provided by State of Vermont 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 ensure 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 1:2500 and all observable errors were corrected. This dataset was developed as part of the Updated High-Resolution Land Cover Mapping for Vermont. As such, it represents a 'top down' mapping perspective in which tree canopy over hanging other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the area.