ArticleScientific data2025
Mapping 10-m Industrial Lands across 1000+ Global Large Cities, 2017-2023.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Mapping 10-m Industrial Lands across 1000+ Global Large Cities, 2017-2023.Scientific data · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Industrial lands, as a key component of economic development, pose great environmental challenges, which underscores the need for close global monitoring to support sustainable urban development. Despite this importance, global city-level maps of industrial land use, especially over multiple years, have been lacking. Here, we present a 10-m resolution global dataset tracking industrial land use in 1,093 large cities (area 100 km² or more) from 2017 to 2023. Using multisource geospatial data and machine learning, the dataset achieves a high overall accuracy of 91.87% to 92.21% across the seven-year period, aligning well with official city maps. We further validated its reliability by computing industrial land area per capita for 1,093 cities, which correlated strongly with per capita CO
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.