Evidence map›Paper›PMID 40108153›Full record

ArticleScientific data2025

A dataset of multi-level street-block divisions of 985 cities worldwide.

Jintong Tang, Liyan Xu, Hongbin Yu, Hezhishi Jiang, Dejie He, Tianshu Li, Wanchen Xiao, Xinying Zheng, Keyi Liu, Yiqin Li and 6 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Jintong Tang *Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0001-8581-6524
Liyan Xu *College of Architecture and Landscape Architecture, Peking University, Beijing, China. xuliyan@pku.edu.cn.ORCID http://orcid.org/0000-0002-6933-3394
Hongbin Yu *College of Architecture and Landscape Architecture, Peking University, Beijing, China.
Hezhishi JiangAcademy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
Dejie HeCollege of Urban and Environmental Sciences, Peking University, Beijing, China.
Tianshu LiCollege of Architecture and Landscape Architecture, Peking University, Beijing, China.ORCID http://orcid.org/0009-0009-0351-6209
Wanchen XiaoCollege of Urban and Environmental Sciences, Peking University, Beijing, China.
Xinying ZhengInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China.
Keyi LiuCollege of Architecture and Landscape Architecture, Peking University, Beijing, China.
Yiqin LiStuart Weitzman School of Design, University of Pennsylvania, Philadelphia, PA, USA.
Shijie LiCollege of Architecture and Landscape Architecture, Peking University, Beijing, China.
Qian HuangGlobal Technical Service Dept, Huawei Technologies, Beijing, China.
Jun ZhangGlobal Technical Service Dept, Huawei Technologies, Shanghai, China.
Yinsheng ZhouGlobal Technical Service Dept, Huawei Technologies, Beijing, China.
Lun WuInstitute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China.
Yu LiuInstitute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-0016-2902

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2022YFC3800803
6 · The paper itself

Abstract

Street-blocks, as basic geographical units for dividing urban space, are widely used in urban planning and statistics. However, the availability and quality of street-block data vary significantly across different countries or regions worldwide. While developed countries tend to have mature urban street-block division systems and corresponding public data, such data in most developing countries are often incomplete or non-existent. Even in countries with available data, the lack of consistent standards for street-block division causes difficulty in international comparative research. To address this gap, we are releasing a new open dataset: Multi-level Street-block Divisions of 985 Cities Worldwide (MSDCW), offering a logical, standardized, and user-friendly street-block division system for cities with the estimated population over 500,000 by Demographia from 142 countries or regions, with results at five spatial levels. Validation shows that compared with official datasets, MSDCW offers a reasonable division of urban street-blocks, and is therefore suitable as foundational data for related research. Additionally, researchers can use our method to generate their own street-block division datasets.

Identifiers

PMID40108153
PMCPMC11923264

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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.