This layer is a high-resolution wetlands layer for Virginia Beach, Virginia. Three wetlands classes were mapped: (1) emergent wetlands, (2) , forest wetlands and (3) shrub/scrub wetlands at 3 Foot resolution. The primary sources used to derive this wetlands layer were 2018 LiDAR data and 2018 NAIP imagery. Wetlands were classed based on the average height of vegetation in the 2018 LiDAR. The emergent class represents wetlands where the average vegetation height ranged from 0-6ft. The shrub/scrub class represents wetlands where the average vegetation height ranged from 6ft - 20ft. The forest class represents wetlands where the average vegetation height is above 20ft. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. The dataset was created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). 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. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.

This layer is a high-resolution wetlands layer for Virginia Beach, Virginia. Three wetlands classes were mapped: (1) emergent wetlands, (2) , forest wetlands and (3) shrub/scrub wetlands at 3 Foot resolution. The primary sources used to derive this wetlands layer were 2018 LiDAR data and 2018 NAIP imagery. Wetlands were classed based on the average height of vegetation in the 2018 LiDAR. The emergent class represents wetlands where the average vegetation height ranged from 0-6ft. The shrub/scrub class represents wetlands where the average vegetation height ranged from 6ft - 20ft. The forest class represents wetlands where the average vegetation height is above 20ft. Mapping was carried out using an approach that integrated automated feature extraction with manual edits. Care was taken to ensure that changes to the tree canopy were due to actual change in the land cover as opposed to differences in the remotely sensed data stemming from lighting conditions or image parallax. The dataset was created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). 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. No accuracy assessment was conducted, but the dataset was subjected to manual review and correction.