Tree canopy was mapped from leaf-off LiDAR collected in the spring of 2016 and leaf-on high-resolution imagery collected in the summer of 2015 to complete this tree canopy cover assessment. Tree canopy cover mapping was carried out using a semi-automated approach that coupled automated feature extraction with manual editing. Automated feature extraction was done using a rule-based expert system embedded within an object-based framework. Object-based image analysis techniques (OBIA) 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. Manual corrections carried out on a scale of 1:2,500, followed by a final review for completeness and consistency at a scale of 1:10,000.Displays data from CARTO.TreeCanopy_2016. Will not display when zoomed out beyond 1:50,000.Static data layer, no updates.