A complete building coverage area dataset (i.e. area occupied by building structures, excluding other built surfaces such as roads, parking lots, and public parks) at the level of census block groups for the contiguous United States (CONUS). The dataset was assembled based on an ensemble prediction of nonlinear hierarchical models to account for spatial heterogeneities in the distribution of built surfaces across different urban communities. Percentage of impervious land and housing density were used as predictors of the estimated area of buildings and cross-validation results showed that the product estimated area represented by buildings with a mean error of 0.049 %.
Building Coverage Area, Urban Geography; Regional, Sustainability, US Census Block Groups, CONUS Data
| DOI | 10.13012/B2IDB-4137411_V1 |
|---|---|
| Publcation Date | 06-05-2018 |
| Title | Dataset for: Quantifying the geographic distribution of building coverage across the US for urban sustainability studies |
| Author | Soliman, Aiman Mackay, Andrew Schmidt, Arthur Allan, Brian Wang, Shaowen |
| Keywords | Building Coverage Area, Urban Geography; Regional, Sustainability, US Census Block Groups, CONUS Data |
| Related Publication (Citation) | Soliman, A., Mackay, A., Schmidt, A., Allan, B. and Wang, S. Quantifying the geographic distribution of built up area across the US for urban sustainability studies. Computers, Environment and Urban Systems (2018). https://doi.org/10.1016/j.compenvurbsys.2018.05.010 |
| Note |
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nunc tincidunt pellentesque massa nec fermentum. Aliquam tincidunt magna in sem sagittis facilisis. Nam vel lorem vel nibh euismod scelerisque. Mauris hendrerit lacinia tellus non consectetur. Praesent sagittis dolor iaculis, hendrerit neque non, feugiat mauris. Morbi vitae tortor ut erat efficitur suscipit id sit amet felis. In lacinia orci at laoreet porttitor. In sagittis orci hendrerit massa commodo, at consequat erat tempus. Phasellus at purus suscipit, viverra mi faucibus, blandit erat.
Maecenas quis interdum lorem. Ut malesuada dignissim sollicitudin. Aenean et euismod mauris, sit amet tempus eros. Ut leo sapien, lobortis id risus sed, semper ultricies lorem. Quisque hendrerit libero in nunc semper, eu interdum ex volutpat. Nunc varius venenatis venenatis. Vivamus pretium finibus metus vitae feugiat. Aenean ac neque eu nunc pretium pulvinar. Nulla facilisi. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. In commodo felis turpis, et faucibus ligula auctor quis. Suspendisse non eros facilisis, placerat nulla ac, iaculis massa. Curabitur nec turpis placerat lorem condimentum ultrices at vel metus. Maecenas tortor ligula, ultrices et metus auctor, volutpat laoreet diam. Maecenas sodales bibendum accumsan.
Mauris lacinia est quis ante faucibus rhoncus. Sed cursus luctus dui. Quisque vel sapien nec lectus sodales interdum ut ut orci. In porta odio diam, venenatis tempor est luctus ut. Donec ac ligula imperdiet, facilisis justo non, dapibus sem. Nulla dui nulla, feugiat feugiat porta vitae, semper sed purus. Nullam erat lacus, scelerisque eget eros nec, vulputate facilisis massa. Aliquam dictum quis nunc sed lacinia. Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Aenean gravida, orci nec auctor blandit, justo ante accumsan leo, nec condimentum urna ante id diam. Nam sed placerat urna. Phasellus est nisi, commodo at diam sit amet, pretium maximus diam. Integer dictum ligula dui, vel fermentum arcu efficitur id. Suspendisse potenti. Nunc mollis massa elementum felis laoreet, vel luctus odio ultrices.
© CyberGIS Center