The Bing Maps team at Microsoft released a U.S.-wide vector building dataset in 2018, which includes over 125 million building footprints for all 50 states in GeoJSON format. This dataset is extracted from aerial images using deep learning object classification methods. Large-extent modelling (e.g., urban morphological analysis or ecosystem assessment models) or accuracy assessment with vector layers is highly challenging in practice. Although vector layers provide accurate geometries, their use in large-extent geospatial analysis comes at a high computational cost. We used High Performance Computing (HPC) to develop an algorithm that calculates six summary values for each cell in a raster representation of each U.S. state: (1) total footprint coverage, (2) number of unique buildings intersecting each cell, (3) number of building centroids falling inside each cell, and area of the (4) average, (5) smallest, and (6) largest area of buildings that intersect each cell. These values a ...

This dataset contains lines for all highways in the state of New Mexico. It is in a vector digital data structure digitized from a USGS 1:500,000 scale map of the state of New Mexico to which highways: Interstate, U.S., and State have been added. The source was ARC/INFO 5.0.1. and the conversion software was ARC/INFO 7.0.3. The size of the file is .36 Mb, compressed.