| Abstract: |
Urban tree canopy (UTC) is an integral component of green infrastructure that benefits communities by improving air and water quality, enhancing property values, providing wildlife habitat, and providing social aesthetics. Detailed, high-resolution landcover data are a necessity in communities that are assessing and developing management plans for their green infrastructure. Traditional sources of tree canopy data derived from moderate resolution sensors and pixel-based classification are too coarse for accurately identifying tree canopy. Recent developments in object-based image analysis (OBIA) and availability of high-resolution imagery and LiDAR data have improved the accuracy and efficiency of mapping landcover features. UTC assessments for several US cities were conducted using land cover data derived from high-resolution multispectral imagery, LiDAR surface data, and vector layers. As part of these assessments, UTC metrics were summarized using administrative, zoning, and cadastral boundaries and compared to estimates derived from the National Land Cover Dataset (NLCD). |