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Nathan Foks

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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...
These layers cover conterminous U.S.; The file format is raster IMG; and the cell size is 30m. Files are: (1) total footprint coverage, [Conterminous_US_Building_Total_Area] (2) number of unique buildings intersecting each cell, [Conterminous_US_Building_Count] (3) number of building centroids falling inside each cell, [Conterminous_US_Building_Centroid_Count] and (4) average area of the buildings that intersect each cell, [Conterminous_US_Building_Average_Area]; (5) area of the smallest building that intersects each cell, [Conterminous_US_Building_Min_Area]; and (6) area of the largest building that intersects each cell [Conterminous_US_Building_Max_Area].
Each state has a zipped folder that contains six Geotiff files: 1- <StateName>_avg.tif ===> The value of each cell in this raster layer is the avarage area of all buildings that intersect the cell. The unit is sq meter. 2- <StateName>_cnt.tif ===> The value of each cell in this raster layer is the number of buildings that intersect the cell. 3- <StateName>_max.tif ===> The value of each cell in this raster layer is the maximum of area of all building that intersect the cell. The unit is sq meter. 4- <StateName>_min.tif ===> The value of each cell in this raster layer is the minimum of area of all building that intersect the cell. The unit is sq meter. 5- <StateName>_sum.tif ===> The value of each cell in...
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