GlobalBuildingMap -- Unveiling the Mystery of Global Buildings

Xiao Xiang Zhu, Qingyu Li, Yilei Shi, Yuanyuan Wang, Adam Stewart +1 more
4/22/2024
cs.CV

No confident code implementation found for this paper.

Abstract

Understanding how buildings are distributed globally is crucial to revealing the human footprint on our home planet. This built environment affects local climate, land surface albedo, resource distribution, and many other key factors that influence well-being and human health. Despite this, quantitative and comprehensive data on the distribution and properties of buildings worldwide is lacking. To this end, by using a big data analytics approach and nearly 800,000 satellite images, we generated the highest resolution and highest accuracy building map ever created: the GlobalBuildingMap (GBM). A joint analysis of building maps and solar potentials indicates that rooftop solar energy can supply the global energy consumption need at a reasonable cost. Specifically, if solar panels were placed on the roofs of all buildings, they could supply 1.1-3.3 times -- depending on the efficiency of the solar device -- the global energy consumption in 2020, which is the year with the highest consumption on record. We also identified a clear geospatial correlation between building areas and key socioeconomic variables, which indicates our global building map can serve as an important input to modeling global socioeconomic needs and drivers.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{zhu2024globalbuildingmap,
  title  = {GlobalBuildingMap -- Unveiling the Mystery of Global Buildings},
  author = {Xiao Xiang Zhu and Qingyu Li and Yilei Shi and Yuanyuan Wang and Adam Stewart and Jonathan Prexl},
  year   = {2024},
  eprint = {2404.13911},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.13911v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2404.13911.svg)](https://codeofpaper.com/paper/2404.13911)

Discussion