gloBFPr

Provides tools to access, search, and download global 3D building footprint datasets (3D-GloBFP). The package includes functions to retrieve metadata, filter by bounding box, and download building height tiles.

https://github.com/billbillbilly/globfpr

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.1%) to scientific vocabulary

Keywords

building-footprint-data building-height cran-r rpackage spatial-data spatial-data-analysis
Last synced: 6 months ago · JSON representation

Repository

Provides tools to access, search, and download global 3D building footprint datasets (3D-GloBFP). The package includes functions to retrieve metadata, filter by bounding box, and download building height tiles.

Basic Info
  • Host: GitHub
  • Owner: billbillbilly
  • License: other
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 1.43 MB
Statistics
  • Stars: 6
  • Watchers: 0
  • Forks: 2
  • Open Issues: 0
  • Releases: 0
Topics
building-footprint-data building-height cran-r rpackage spatial-data spatial-data-analysis
Created 9 months ago · Last pushed 7 months ago
Metadata Files
Readme

README.md

gloBFPr forestdata website

Lifecycle:
experimental R-CMD-check <!-- badges: end -->

Access and analyze the Building Footprint Datasets.

Overview

The gloBFPr package allows R users to search, download, and process global building footprint tiles with associated height information, derived from the 3D-GloBFP dataset published by Che et al. (2024, 2025). The data is hosted on Zenodo and covers global urban areas in shapefile format. The package will look to include more global Building Dataset in the future.

Features

📦 Access tiled metadata of 3D-GloBFP dataset

🔍 Search tiles by bounding box (BBOX) or area of interest

⬇️ Download only the necessary files

🏗️ Retrieve building polygons and height attributes

🌍 Generate rasters of binary presence or graduated height

🗺️ Output spatial data in sf or terra raster format

Installation

Install the development version: ```r

Install devtools if needed

install.packages("devtools")

Install from GitHub

devtools::install_github("billbillbilly/gloBFPr") ```

The package will be on CRAN soon.

Usage

  1. Load metadata

r library(gloBFPr) metadata <- get_metadata()

  1. Search and download data by bounding box

r bbox <- c(-83.065644,42.333792,-83.045217,42.346988) buildings_list <- search_3dglobdf(bbox = bbox, metadata = metadata, out_type = "all", # mask = TRUE, cell_size = 1) This will return a list containing: - poly: an sf object of 3D building footprints - binary: a binary raster of building presence - graduated: a raster representing building height in meters

Specify cell_size = 1 to generate raster layers with 1-meter resolution, ensuring detailed spatial representation of building geometries within the defined area of interest.

Setting mask = TRUE ensures the height raster is masked by the building footprints.

Output examples:

       

               

Note

The downloading process may take some time, depending on the number and size of building footprint tiles.

This implementation relies on the current structure of the dataset as hosted on Figshare. It may break if the dataset owner changes the file organization or metadata format.

Please read the function documentation carefully. The dataset may require proper citation when used.

Issues and bugs

If you discover a bug not associated with connection to the API that is not already a reported issue, please open a new issue providing a reproducible example.

Owner

  • Name: Xiaohao Yang
  • Login: billbillbilly
  • Kind: user
  • Location: Ann Arbor, MI

Graduate researcher assistant @land-info-lab at the School for Environment and Sustainability, University of Michigan

GitHub Events

Total
  • Issues event: 2
  • Watch event: 4
  • Issue comment event: 3
  • Public event: 1
  • Push event: 19
  • Fork event: 2
  • Create event: 1
Last Year
  • Issues event: 2
  • Watch event: 4
  • Issue comment event: 3
  • Public event: 1
  • Push event: 19
  • Fork event: 2
  • Create event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 2
  • Total pull requests: 0
  • Average time to close issues: 2 days
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 3.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: 2 days
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 3.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • nikosGeography (1)
  • MOB-Habitat (1)
Pull Request Authors
Top Labels
Issue Labels
bug (2)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 188 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: gloBFPr

Access Global Building Height Datasets

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 188 Last month
Rankings
Dependent packages count: 26.3%
Dependent repos count: 32.4%
Average: 48.4%
Downloads: 86.5%
Maintainers (1)
Last synced: 6 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 4.1 depends
  • dplyr * imports
  • httr2 * imports
  • sf * imports
  • terra * imports
  • knitr * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests