30-arc second spatial resolution of urban geometric datasets with global coverage

Grid-based building morphological parameters with global coverage at 30-arc second spatial resolution are currently available in GeoTIFF format. Provided datasets contains three-building morphological parameters (the mean building height <i>Have</i>, plan area density <i>PAD</i> and frontal area density <i>FAD</i>) and two-aerodynamic parameters (aerodynamic roughness length <i>z₀</i> and zero-place displacement <i>d</i>) and sky-view factor (<i>svf</i>).The building morphological datasets were estimated from the global databases such as population, nighttime light, impervious surface area and gross domestic products. Two aerodynamic parameters and sky-view factors are calculated using the empirical equations discussed by Kanda et al. (2013) and Kanda et al. (2005), respectively.<br><b>1. Raster files</b>: (parameter name)_2013.tifFormat: GeoTIFFProjection: WGS 1984 World Mercator projectionSpatial resolution: 30-arc second<br>Data list: <i>Have_2013.tif</i>, <i>PAD_2013.tif</i>, <i>FAD_2013.tif</i>, <i>d_2013.tif</i>, <i>z0_2013.tif</i>, <i>svf_2013.tif</i><br><b>2. Building Original Data</b>Format: Microsoft Excel Workbook<i>Original_building_data.xlsx</i> contains observed building morphological parameters calculated from three- and two-dimensional building databases, and global databases (impervious surface area <i>ISA</i> and population density adjusted by nighttime light <i>PopdenVIIRS</i>) at each grid code.<br><i>Validation_analysis.xlsx</i> contains building morphological parameters calculated from three-dimensional building database (observed) and parameters estimated from global databases (predicted) at one-km spatial resolution in Berlin, Singapore and Osaka.<i>Additional_validation_UScities.xlsx</i> contains building morphological parameters at one-km resolution by NUDAPT database (observed) and estimated from global databases (predicted) for 42 US cities. We used this data in the Supplementary Discussion. <i>Megacities_statistic.xlsx</i> contains <i>GDP_city</i>, the maximum, minimum, mean value and standard deviation of each predicted building morphological parameters at 37 megacities. <br><br><b>3. Source Code</b>Programming language 1: Python site package in ArcGIS v10.3.1<i>Calculate_parameters.py</i> contains code for calculating observed building morphological parameters from grid-based two- and three-dimensional building database input. We recommend using this script after using the Split By Attributing Tools to convert a fishnet building footprint map into multiple grids.<i>Modifying_population_by_nightlight.py</i> contains code for adjusted population density by nighttime light at each grid.Programming language 2: Python v2.7<br><i>Converting_grids.py</i> contains code for converting grid-based population density adjusted by nighttime light into a global map. This source code is used after running <i>Modifying_population_by_nightlight.py</i>. <br>