{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T21:08:23Z","timestamp":1772658503593,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T00:00:00Z","timestamp":1617062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China","award":["4200118"],"award-info":[{"award-number":["4200118"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019M663038"],"award-info":[{"award-number":["2019M663038"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A country can be well-comprehended through its core cities. Similarly, we can learn about a city from its hotspots, as they manifest the concentration of urban infrastructures and human activities. Following this philosophy, this paper studies the intra-urban form and function from a complexity science perspective by exploring the power law distribution of hotspot sizes and related socio-economic attributes. To detect hotspots, we rely on spatial clustering of geospatial big data sets, including street data from OpenStreetMap platform and nighttime light (NTL) data from the visible infrared imaging radiometer suite (VIIRS) imagery. Unlike conventional spatial units, which are imposed by governments or authorities (such as census block), the delineation of hotspots is done in a totally bottom-up manner and, more importantly, can help us examine precisely the scaling pattern of urban morphological and functional aspects. This results in two types of urban hotspots\u2014street-based and NTL-based hotspots\u2014being generated across 20 major cities in China. We find that Zipf\u2019s law of hotspot sizes (both types) holds remarkably well for each city, as do the city-size distributions at the country level, indicating a statistically self-similar structure of geographic space. We further find that the urban scaling law can be effectively detected when using NTL-based hotspots as basic units. Furthermore, the comparison between two types of hotspots enables us to gain in-depth insights of urban planning and urban economic development.<\/jats:p>","DOI":"10.3390\/rs13071322","type":"journal-article","created":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T00:13:10Z","timestamp":1617149590000},"page":"1322","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Intra-Urban Scaling Properties Examined by Automatically Extracted City Hotspots from Street Data and Nighttime Light Imagery"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9328-9584","authenticated-orcid":false,"given":"Ding","family":"Ma","sequence":"first","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"},{"name":"Faculty of Engineering and Sustainable Development, University of G\u00e4vle, 80176 G\u00e4vle, Sweden"}]},{"given":"Renzhong","family":"Guo","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Ying","family":"Jing","sequence":"additional","affiliation":[{"name":"Ningbo Institute of Technology, School of Economics, Zhejiang University, Ningbo 315000, China"}]},{"given":"Ye","family":"Zheng","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Zhigang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"}]},{"given":"Jiahao","family":"Yang","sequence":"additional","affiliation":[{"name":"Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,30]]},"reference":[{"key":"ref_1","unstructured":"United Nations (2019). 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