ArticleScientific data2025
The first urban open space product of global 169 megacities using remote sensing and geospatial data.
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 2 papers.
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
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Who cites it
2 citing papers in PubMed.
- Multi-scale boundary-aware network for remote sensing image semantic segmentation.Scientific reports · 2026Article
- The first urban open space product of global 169 megacities using remote sensing and geospatial data.Scientific data · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
Urban open space (UOS) plays an important environmental role, especially in areas characterized by intense social and economic activity. However, the high interclass similarities, complex surroundings, and scale variations of UOS lead to unsatisfactory UOS mapping performance, and UOS mapping products for major cities around the world are lacking. To fill this gap, we used a deep learning-based method based on a tiny-manual annotation strategy and optical remote sensing imagery to produce a 1.19 m resolution UOS map of 169 megacities, namely the OpenspaceGlobal product. We generated the OpenspaceGlobal product with five urban open space categories. To obtain the final OpenspaceGlobal product, we processed over 8.5 TB of remote sensing images and nearly 90 million polygons in crowdsourced geospatial data. The validation results showed that the OpenspaceGlobal product had an overall accuracy of 79.13 % and a kappa coefficient of 73.47 %. The OpenspaceGlobal product can promote a better understanding of human-made space surfaces in major cities around the world.
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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.