Evidence map›Paper›PMID 37258561›Full record

ArticleScientific reports2023

Estimating urban spatial structure based on remote sensing data.

Masanobu Kii, Tetsuya Tamaki, Tatsuya Suzuki, Atsuko Nonomura

Abstract read
In one paragraph

Article in Scientific reports, 2023. 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

4 authors.

Masanobu KiiGraduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. kii@see.eng.osaka-u.ac.jp.
Tetsuya TamakiFaculty of Engineering and Design, Kagawa University, 2217-20 Hayashi-Cho, Takamatsu, Kagawa, 761-0396, Japan.
Tatsuya SuzukiFaculty of Engineering and Design, Kagawa University, 2217-20 Hayashi-Cho, Takamatsu, Kagawa, 761-0396, Japan.
Atsuko NonomuraFaculty of Engineering and Design, Kagawa University, 2217-20 Hayashi-Cho, Takamatsu, Kagawa, 761-0396, Japan.

Funding

Japan Society for the Promotion of Science 16KK0013Science and Technology Research Partnership for Sustainable Development JPMJSA1704
6 · The paper itself

Abstract

Understanding the spatial structure of a city is essential for formulating a spatial strategy for that city. In this study, we propose a method for analyzing the functional spatial structure of cities based on satellite remote sensing data. In this method, we first assume that urban functions consist of residential and central functions, and that these functions are measured by trip attraction by purpose. Next, we develop a model to explain trip attraction using remote sensing data, and estimate trip attraction on a grid basis. Using the estimated trip attraction, we created a contour tree to identify the spatial extent of the city and the hierarchical structure of the central functions of the city. As a result of applying this method to the Tokyo metropolitan area, we found that (1) our method reproduced 84% of urban areas and 94% of non-urban areas defined by the government, (2) our method extracted 848 urban centers, and their size distribution followed a Pareto distribution, and (3) the top-ranking urban centers were consistent with the districts defined in the master plans for the metropolitan area. Based on the results, we discussed the applicability of our method to urban structure analysis.

Identifiers

PMID37258561
PMCPMC10232531

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Registered trials

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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.