{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T03:54:48Z","timestamp":1767844488781,"version":"3.49.0"},"reference-count":64,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}]},{"name":"National Key Research and Development Program of China","award":["42171357"],"award-info":[{"award-number":["42171357"]}]},{"name":"National Key Research and Development Program of China","award":["42201384"],"award-info":[{"award-number":["42201384"]}]},{"name":"the research on the multi-perspective evaluation of urban green space based on remote sensing and street view data","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}]},{"name":"the research on the multi-perspective evaluation of urban green space based on remote sensing and street view data","award":["42171357"],"award-info":[{"award-number":["42171357"]}]},{"name":"the research on the multi-perspective evaluation of urban green space based on remote sensing and street view data","award":["42201384"],"award-info":[{"award-number":["42201384"]}]},{"name":"Study on the spatial-temporal heterogeneity of urban anthropogenic heat and its environmental effects simulation in multi-scenes","award":["2020YFC0833100"],"award-info":[{"award-number":["2020YFC0833100"]}]},{"name":"Study on the spatial-temporal heterogeneity of urban anthropogenic heat and its environmental effects simulation in multi-scenes","award":["42171357"],"award-info":[{"award-number":["42171357"]}]},{"name":"Study on the spatial-temporal heterogeneity of urban anthropogenic heat and its environmental effects simulation in multi-scenes","award":["42201384"],"award-info":[{"award-number":["42201384"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Urban spatial structures (USS) play an essential role in urbanization. Understanding the impact of USS patterns on their socioeconomic benefits is crucial to evaluating urban structure quality. Previous studies have, primarily, relied on statistical data and have significant temporal consistency and spatial accuracy limitations. Moreover, previous evaluation methods mainly determined the weight of indicators based on subjective assessments, such as the Delphi method, without integrating the actual socioeconomic benefits of complex urban systems. By measuring the two-dimensional (2D) urban functional landscape patterns and three-dimensional (3D) building forms of the city and considering the level of urban socioeconomic vitality as revealed by nighttime light intensity (NTLI), this study explores the influence of urban spatial structure on socioeconomic vitality. It provides a new perspective for evaluating the USS level. Furthermore, a comprehensive index, namely the Spatial Structure Socioeconomic Benefit Index (SSSBI), was constructed to quantify the socioeconomic benefits of USS. The results showed that (1) the impact of spatial structure on NTLI differs significantly with the distribution of urban functional landscape patterns and building forms. (2) The combined effect of any two spatial structure factors on NTLI was higher than the effect of each factor separately, indicating that multiple dimensions can improve urban spatial construction. (3) This study quantitatively extracts the characteristics of USS from multiple scales, which helps to find the optimal evaluation scale and build a scientific and objective evaluation model. The results showed that the USS assessment based on the SSSBI index is practical. This study could provide a reference for the government\u2019s urban planning and land-use decisions.<\/jats:p>","DOI":"10.3390\/rs14215511","type":"journal-article","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T03:36:44Z","timestamp":1667360204000},"page":"5511","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Evaluation of Urban Spatial Structure from the Perspective of Socioeconomic Benefits Based on 3D Urban Landscape Measurements: A Case Study of Beijing, China"],"prefix":"10.3390","volume":"14","author":[{"given":"Yujia","family":"Liu","sequence":"first","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123008, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}]},{"given":"Qingyan","family":"Meng","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}]},{"given":"Jichao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geomatics, Liaoning Technical University, Fuxin 123008, China"}]},{"given":"Linlin","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5835-1829","authenticated-orcid":false,"given":"Mona","family":"Allam","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Environment & Climate Changes Research Institute, National Water Research Center, El Qanater EI Khairiya 13621\/5, Egypt"}]},{"given":"Xinli","family":"Hu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Key Laboratory of Earth Observation of Hainan Province, Hainan Aerospace Information Research Institute, Sanya 572029, China"}]},{"given":"Chengxiang","family":"Zhan","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"School of Science, China University of Geosciences (Beijing), Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1126\/science.1248365","article-title":"Humanity\u2019s Unsustainable Environmental Footprint","volume":"344","author":"Hoekstra","year":"2014","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bhatta, B. (2010). Analysis of Urban Growth and Sprawl from Remote Sensing Data, Springer. Advances in Geographic Information Science.","DOI":"10.1007\/978-3-642-05299-6"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1007\/s11069-015-1865-9","article-title":"The Influence of Economic Growth, Urbanization, Trade Openness, Financial Development, and Renewable Energy on Pollution in Europe","volume":"79","author":"Ozturk","year":"2015","journal-title":"Nat. Hazards"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1021\/es202329f","article-title":"Landscape Urbanization and Economic Growth in China: Positive Feedbacks and Sustainability Dilemmas","volume":"46","author":"Bai","year":"2012","journal-title":"Environ. Sci. Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1177\/030913258400800320","article-title":"Book Review: Internal Structure of the City: Readings on Urban Growth, form and Policy","volume":"8","author":"Clark","year":"1984","journal-title":"Prog. Hum. Geogr."},{"key":"ref_6","unstructured":"Bourne, L.S. (1982). Internal Structure of the City: Readings on Urban Form, Growth, and Policy, Oxford University Press."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.progress.2011.04.001","article-title":"The Dimensions of Global Urban Expansion: Estimates and Projections for All Countries, 2000\u20132050","volume":"75","author":"Angel","year":"2011","journal-title":"Prog. Plan."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Chong, Z., Qin, C., and Ye, X. (2017). Environmental Regulation and Industrial Structure Change in China: Integrating Spatial and Social Network Analysis. Sustainability, 9.","DOI":"10.3390\/su9081465"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1177\/0042098009349770","article-title":"Economic Growth and the Expansion of Urban Land in China","volume":"47","author":"Deng","year":"2010","journal-title":"Urban Stud."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.apgeog.2016.12.018","article-title":"Four Decades of Urban Sprawl and Population Growth in Teresina, Brazil","volume":"79","year":"2017","journal-title":"Appl. Geogr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.gloenvcha.2012.10.016","article-title":"An Urbanization Bomb? Population Growth and Social Disorder in Cities","volume":"23","author":"Buhaug","year":"2013","journal-title":"Glob. Environ. Chang."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2019.04.010","article-title":"Investigating the Effects of 3D Urban Morphology on the Surface Urban Heat Island Effect in Urban Functional Zones by Using High-Resolution Remote Sensing Data: A Case Study of Wuhan, Central China","volume":"152","author":"Huang","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6305","DOI":"10.1109\/TGRS.2017.2725917","article-title":"A New Approach for Detecting Urban Centers and Their Spatial Structure With Nighttime Light Remote Sensing","volume":"55","author":"Chen","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2320","DOI":"10.1016\/j.rse.2011.04.032","article-title":"Mapping Urbanization Dynamics at Regional and Global Scales Using Multi-Temporal DMSP\/OLS Nighttime Light Data","volume":"115","author":"Zhang","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_15","first-page":"8","article-title":"Analysis of luojia1-01 index based on nighttime light imagery","volume":"45","author":"Li","year":"2020","journal-title":"J. Geomat."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1080\/13658816.2018.1555642","article-title":"Integration of Nighttime Light Remote Sensing Images and Taxi GPS Tracking Data for Population Surface Enhancement","volume":"33","author":"Yu","year":"2019","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1126\/science.aaf7894","article-title":"Combining Satellite Imagery and Machine Learning to Predict Poverty","volume":"353","author":"Jean","year":"2016","journal-title":"Science"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5104578","DOI":"10.1155\/2020\/5104578","article-title":"Housing Vacancy Rate in Major Cities in China: Perspectives from Nighttime Light Data","volume":"2020","author":"Tan","year":"2020","journal-title":"Complexity"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1080\/014311697218485","article-title":"Relation between Satellite Observed Visible-near Infrared Emissions, Population, Economic Activity and Electric Power Consumption","volume":"18","author":"Elvidge","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1080\/00045608.2015.1018773","article-title":"Social Sensing: A New Approach to Understanding Our Socioeconomic Environments","volume":"105","author":"Liu","year":"2015","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_21","first-page":"379","article-title":"Towards geo-spatial information science in big data era","volume":"45","author":"Li","year":"2016","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_22","first-page":"390","article-title":"Methods of Crowd Sourcing Geographic Data Processing and Analysis","volume":"39","author":"Shan","year":"2014","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_23","first-page":"102610","article-title":"Evaluation of urban green space in terms of thermal environmental benefits using geographical detector analysis","volume":"105","author":"Wang","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wang, B., Liu, Z., Mei, Y., and Li, W. (2019). Assessment of Ecosystem Service Quality and Its Correlation with Landscape Patterns in Haidian District, Beijing. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16071248"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2328","DOI":"10.1080\/13658816.2014.922186","article-title":"Object-Based Spatial Cluster Analysis of Urban Landscape Pattern Using Nighttime Light Satellite Images: A Case Study of China","volume":"28","author":"Yu","year":"2014","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"4258","DOI":"10.1109\/TGRS.2018.2805829","article-title":"Mapping Urban Areas in China Using Multisource Data With a Novel Ensemble SVM Method","volume":"56","author":"Huang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Liu, X. (2019). Mapping Urban Extent at Large Spatial Scales Using Machine Learning Methods with VIIRS Nighttime Light and MODIS Daytime NDVI Data. Remote Sens., 11.","DOI":"10.3390\/rs11101247"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"5851","DOI":"10.1080\/01431161.2013.798055","article-title":"Improving 30 m Global Land-Cover Map FROM-GLC with Time Series MODIS and Auxiliary Data Sets: A Segmentation-Based Approach","volume":"34","author":"Yu","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1007\/s10980-019-00834-7","article-title":"The Effect of Urban 2D and 3D Morphology on Air Temperature in Residential Neighborhoods","volume":"34","author":"Tian","year":"2019","journal-title":"Landsc. Ecol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Small, C. (2019). Multisensor Characterization of Urban Morphology and Network Structure. Remote Sens., 11.","DOI":"10.3390\/rs11182162"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Chen, K., Zou, Z., and Shi, Z. (2021). Building Extraction from Remote Sensing Images with Sparse Token Transformers. Remote Sens., 13.","DOI":"10.3390\/rs13214441"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Chen, M., Wu, J., Liu, L., Zhao, W., Tian, F., Shen, Q., Zhao, B., and Du, R. (2021). DR-Net: An Improved Network for Building Extraction from High Resolution Remote Sensing Image. Remote Sens., 13.","DOI":"10.3390\/rs13020294"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Lv, N., Zhang, Z., Li, C., Deng, J.X., Su, T., and Chen, C. (2022). A hybrid-attention semantic segmentation network for remote sensing interpretation in land-use surveillance. Int. J. Mach. Learn. Cyber.","DOI":"10.1007\/s13042-022-01517-7"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, J., Hu, X., Meng, Q., Zhang, L., Wang, C., Liu, X., and Zhao, M. (2021). Developing a Method to Extract Building 3D Information from GF-7 Data. Remote Sens., 13.","DOI":"10.3390\/rs13224532"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Bullinger, S., Bodensteiner, C., and Arens, M. (2021). 3D Surface Reconstruction From Multi-Date Satellite Images. arXiv.","DOI":"10.5194\/isprs-archives-XLIII-B2-2021-313-2021"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1080\/13658816.2017.1384830","article-title":"An Extended Minimum Spanning Tree Method for Characterizing Local Urban Patterns","volume":"32","author":"Wu","year":"2018","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Xie, J., and Feng, C.-C. (2016). An Integrated Simplification Approach for 3D Buildings with Sloped and Flat Roofs. IJGI, 5.","DOI":"10.3390\/ijgi5080128"},{"key":"ref_38","first-page":"453","article-title":"Variation pattern and its affecting factors of three-dimensional landscape in urban residential community of Shenyang","volume":"2011","author":"Zhang","year":"2011","journal-title":"Chin. J. Appl. Ecol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.landurbplan.2017.05.022","article-title":"Measuring landscape pattern in three dimensional space","volume":"167","author":"Wu","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_40","first-page":"1673","article-title":"Three-dimensional Urban Form at the Street Block Level for Major Cities in China","volume":"3","author":"Long","year":"2019","journal-title":"Shanghai Urban Plan. Rev."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.rse.2017.01.005","article-title":"Advances in Using Multitemporal Night-Time Lights Satellite Imagery to Detect, Estimate, and Monitor Socioeconomic Dynamics","volume":"192","author":"Bennett","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"139148","DOI":"10.1016\/j.scitotenv.2020.139148","article-title":"Improving Population Mapping Using Luojia 1-01 Nighttime Light Image and Location-Based Social Media Data","volume":"730","author":"Wang","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2188","DOI":"10.1109\/JSTARS.2015.2418201","article-title":"Estimating House Vacancy Rate in Metropolitan Areas Using NPP-VIIRS Nighttime Light Composite Data","volume":"8","author":"Chen","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.fluiddyn.2004.06.001","article-title":"A General Solution of Unsteady Stokes Equations","volume":"35","author":"Venkatalaxmi","year":"2004","journal-title":"Fluid Dyn. Res."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Zhao, X., Yu, B., Liu, Y., Chen, Z., Li, Q., Wang, C., and Wu, J. (2019). Estimation of Poverty Using Random Forest Regression with Multi-Source Data: A Case Study in Bangladesh. Remote Sens., 11.","DOI":"10.3390\/rs11040375"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.apenergy.2016.10.032","article-title":"Detecting Spatiotemporal Dynamics of Global Electric Power Consumption Using DMSP-OLS Nighttime Stable Light Data","volume":"184","author":"Shi","year":"2016","journal-title":"Appl. Energy"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.apenergy.2015.11.055","article-title":"Modeling Spatiotemporal CO2 (Carbon Dioxide) Emission Dynamics in China from DMSP-OLS Nighttime Stable Light Data Using Panel Data Analysis","volume":"168","author":"Shi","year":"2016","journal-title":"Appl. Energy"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"112014","DOI":"10.1016\/j.rse.2020.112014","article-title":"How Do Land-Use Patterns Influence Residential Environment Quality? A Multiscale Geographic Survey in Beijing","volume":"249","author":"Zhang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"8589","DOI":"10.1073\/pnas.1017031108","article-title":"Using Luminosity Data as a Proxy for Economic Statistics","volume":"108","author":"Chen","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"041120","DOI":"10.1103\/PhysRevE.86.041120","article-title":"Multiscale Community Geometry in a Network and Its Application","volume":"86","author":"Chen","year":"2012","journal-title":"Phys. Rev. E"},{"key":"ref_51","unstructured":"Mcgarigal, K.S., Cushman, S.A., and Neel, M.C. (2021, March 03). Spatial Pattern Analysis Program for Categorical Maps. Available online: www.umass.edu\/landeco\/research\/fragstats\/fragstats.html."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/13658810802443457","article-title":"Geographical Detectors-Based Health Risk Assessment and Its Application in the Neural Tube Defects Study of the Heshun Region, China","volume":"24","author":"Wang","year":"2010","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhao, X., Liu, J., Hao, H., and Yang, Y. (2020). Quantifying the Spatial Heterogeneity and Driving Factors of Aboveground Forest Biomass in the Urban Area of Xi\u2019an, China. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9120744"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Zhao, X., Liu, J., and Bu, Y. (2021). Quantitative Analysis of Spatial Heterogeneity and Driving Forces of the Thermal Environment in Urban Built-up Areas: A Case Study in Xi\u2019an, China. Sustainability, 13.","DOI":"10.3390\/su13041870"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00058655","article-title":"Bagging Predictors","volume":"24","author":"Breiman","year":"1996","journal-title":"Mach. Learn."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Statistics","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.compenvurbsys.2011.07.004","article-title":"Effects of Increasing Fuzziness on Analytic Hierarchy Process for Spatial Multicriteria Decision Analysis","volume":"36","author":"Kordi","year":"2012","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Parsian, S., Amani, M., Moghimi, A., Ghorbanian, A., and Mahdavi, S. (2021). Flood Hazard Mapping Using Fuzzy Logic, Analytical Hierarchy Process, and Multi-Source Geospatial Datasets. Remote Sens., 13.","DOI":"10.3390\/rs13234761"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11518-006-0151-5","article-title":"Decision Making\u2014The Analytic Hierarchy and Network Processes (AHP\/ANP)","volume":"13","author":"Saaty","year":"2004","journal-title":"J. Syst. Sci. Syst. Eng."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.landurbplan.2016.11.007","article-title":"Accessibility of Public Urban Green Space in an Urban Periphery: The Case of Shanghai","volume":"165","author":"Fan","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_61","first-page":"112","article-title":"Vertical decentralization and horizontal competition: How administrative governance models affect the coordinated development of urbanization and industrialization in prefecture-level cities","volume":"43","author":"Zhang","year":"2022","journal-title":"Financ. Trade Econ."},{"key":"ref_62","first-page":"338","article-title":"Simulation of landscape pattern and socio-economic response relationship in the Danjiang Tusk Mountains","volume":"26","author":"Zheng","year":"2019","journal-title":"Soil Water Conserv. Res."},{"key":"ref_63","first-page":"101989","article-title":"Analyzing Parcel-Level Relationships between Luojia 1-01 Nighttime Light Intensity and Artificial Surface Features across Shanghai, China: A Comparison with NPP-VIIRS Data","volume":"85","author":"Wang","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_64","first-page":"135","article-title":"Analysis of influencing factors of urban three-dimensional architectural landscape","volume":"16","author":"Zhang","year":"2019","journal-title":"Urban Archit."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/21\/5511\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:09:02Z","timestamp":1760144942000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/21\/5511"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,1]]},"references-count":64,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["rs14215511"],"URL":"https:\/\/doi.org\/10.3390\/rs14215511","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,1]]}}}