{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T14:43:51Z","timestamp":1776177831655,"version":"3.50.1"},"reference-count":62,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T00:00:00Z","timestamp":1598572800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key Research and Development Program of China","award":["No.2016YFB0501403"],"award-info":[{"award-number":["No.2016YFB0501403"]}]},{"name":"The Key Laboratory of Earth Observation and Geospatial Information Science of NASG","award":["No. 201808360267"],"award-info":[{"award-number":["No. 201808360267"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The evaluation of urban economies has been one key concern identified by scholars. In the past, most research methods on urban development assessments have been based on statistical data, and the analysis results have been presented in the form of statistical tables. Moreover, the development of urban road networks reflects the status of urban development and spatial metrics, which are obtained from the urban road network which can be used to evaluate the growth of the urban economy. The OpenStreetMap (OSM) is collected through crowdsourcing, and the OSM road network has the characteristics of a simplified and efficient approach to collect data, update data, free available data, etc. Therefore, in this paper, the OSM road network density is used as a spatial metric which is taken as the main study subject, to evaluate the economic development of Chinese cities. In our experiment, results show that there is a significant regression correlation between the OSM road network density and municipal gross domestic product (GDP). For the 85 selected Chinese cities, a total of 71 cities with residuals between \u22120.1 and 0.1 account for 83.53%, and a total of 79 cities with residuals between \u22120.2 and 0.2 account for 92.94%. Therefore, it is apparent that the OSM road network density can be used as a spatial metric to evaluate the municipal GDP, and as a result, can be used by local governments and scholars to estimate, evaluate, and forecast the urban economic development of China.<\/jats:p>","DOI":"10.3390\/ijgi9090517","type":"journal-article","created":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T09:17:08Z","timestamp":1598606228000},"page":"517","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["An Economic Development Evaluation Based on the OpenStreetMap Road Network Density: The Case Study of 85 Cities in China"],"prefix":"10.3390","volume":"9","author":[{"given":"Bo","family":"Liu","sequence":"first","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, 418# Guanglan Road, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Shi","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, 418# Guanglan Road, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Da-Jun","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Geomatics, East China University of Technology, 418# Guanglan Road, Nanchang 330013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan-Dong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129# Luoyu Road, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriela","family":"Fernandez","sequence":"additional","affiliation":[{"name":"Department of Geography, Center for Human Dynamics in the Mobile Age (HDMA), San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3421-486X","authenticated-orcid":false,"given":"Ming-Hsiang","family":"Tsou","sequence":"additional","affiliation":[{"name":"Department of Geography, Center for Human Dynamics in the Mobile Age (HDMA), San Diego State University, 5500 Campanile Drive, San Diego, CA 92182-4493, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s100219900011","article-title":"Quantifying landscape spatial pattern: What is the state of the art?","volume":"1","author":"Gustafson","year":"1998","journal-title":"Ecosystems"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1023\/A:1007965018633","article-title":"The behavior of landscape metrics commonly used in the study of habitat fragmentation","volume":"13","author":"Hargis","year":"1998","journal-title":"Landsc. 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