The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Annual maps of global artificial impervious area (GAIA) between 1985 and 2018
Abstract
Abstract Artificial impervious areas are predominant indicators of human settlements. Timely, accurate, and frequent information on artificial impervious areas is critical to understanding the process of urbanization and land use/cover change, as well as of their impacts on the environment and biodiversity. Despite their importance, there still lack annual maps of high-resolution Global Artificial Impervious Areas (GAIA) with longer than 30-year records, due to the high demand of high performance computation and the lack of effective mapping algorithms. In this paper, we mapped annual GAIA from 1985 to 2018 using the full archive of 30-m resolution Landsat images on the Google Earth Engine platform. With ancillary datasets, including the nighttime light data and the Sentinel-1 Synthetic Aperture Radar data, we improved the performance of our previously developed algorithm in arid areas. We evaluated the GAIA data for 1985, 1990, 1995, 2000, 2005, 2010, and 2015, and the mean overall accuracy is higher than 90%. A cross-product comparison indicates the GAIA data are the only dataset spanning over 30 years. The temporal trend in GAIA agrees well with other datasets at the local, regional, and global scales. Our results indicate that the GAIA reached 797,076 km2 in 2018, which is 1.5 times more than that in 1990. China and the United States (US) rank among the top two in artificial impervious area, accounting for approximately 50% of the world's total in 2018. The artificial impervious area of China surpassed that of the US in 2015. By 2018, the remaining eight among the top ten countries are India, Russia, Brazil, France, Italy, Germany, Japan, and Canada. The GAIA dataset can be freely downloaded from http://data.ess.tsinghua.edu.cn .
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Terrestrial ecoregions of the world: a new map of life on Earth
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., et al. (2001) · BioScience · doi:10.1641/0006-3568(2001)051[0933:teotwa]2.0.co;2 · Cited by 8,488
Whitmee, S., Haines, A., Beyrer, C., Boltz, F., Capon, A. G., de Souza Dias, B. F., Ezeh, A., Frumkin, H., Gong, P., Head, P., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(15)60901-1 · Cited by 2,998
Self-citationThe dimensions of global urban expansion: Estimates and projections for all countries, 2000–2050
Angel, S., Parent, J., Civco, D. L., Blei, A., & Potere, D. (2011) · Progress in Planning · doi:10.1016/j.progress.2011.04.001 · Cited by 1,343
MODIS detected surface urban heat islands and sinks: Global locations and controls
Clinton, N., & Gong, P. (2013) · Remote Sensing of Environment · doi:10.1016/j.rse.2013.03.008 · Cited by 521
Self-citation
Cited by
High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015
Liu, X., Huang, Y., Xu, X., Li, X., Li, X., Ciais, P., Lin, P., Gong, K., Ziegler, A. D., Chen, A., et al. (2020) · Nature Sustainability · doi:10.1038/s41893-020-0521-x · Cited by 874
Self-citationUrban heat island mitigation by green infrastructure in European Functional Urban Areas
Marando, F., Heris, M. P., Zulian, G., Udías, A., Mentaschi, L., Chrysoulakis, N., Parastatidis, D., & Maes, J. (2022) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.103564 · Cited by 523
Chen, B., Wu, S., Song, Y., Webster, C., Xu, B., & Gong, P. (2022) · Nature Communications · doi:10.1038/s41467-022-32258-4 · Cited by 362
Self-citationSurface urban heat island intensity in five major cities of Bangladesh: Patterns, drivers and trends
Dewan, A., Kiselev, G., Botje, D., Mahmud, G. I., Bhuian, M. H., & Hassan, Q. K. (2021) · Sustainable Cities and Society · doi:10.1016/j.scs.2021.102926 · Cited by 259
Dewan, A., Kiselev, G., & Botje, D. (2021) · Applied Geography · doi:10.1016/j.apgeog.2021.102533 · Cited by 109
Metadata
- Authors
- Gong, P., Li, X., Wang, J., Bai, Y., Chen, B., Hu, T., Liu, X., Xu, B., Yang, J., Zhang, W., & Zhou, Y.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 236
- Pages
- 111510
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2990323597
- Cited by
- 1,243
- References
- 4
- FWCI
- 51.34
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Annual maps of global artificial impervious area (GAIA) between 1985 and 2018. https://app.cochat.ai/papers/10.1016/j.rse.2019.111510
- The paper
- Gong, P., Li, X., Wang, J., Bai, Y., Chen, B., Hu, T., Liu, X., Xu, B., Yang, J., Zhang, W., & Zhou, Y. (2020). Annual maps of global artificial impervious area (GAIA) between 1985 and 2018. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2019.111510
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
