{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,5]],"date-time":"2026-02-05T23:10:45Z","timestamp":1770333045333,"version":"3.49.0"},"reference-count":96,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T00:00:00Z","timestamp":1599609600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971152"],"award-info":[{"award-number":["41971152"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The co-evolution of multi-cities has emerged as the primary form of urbanization in China in recent years. However, the processes, patterns, and coordination are not well characterized and understood, which hinders the understanding of the driving forces, consequences, and management of polycentric urban development. We used the Continuous Change Detection and Classification (CCDC) algorithm to integrate all available Landsat 5, 7, and 8 images and map annual land use and land cover (LULC) from 2001 to 2017 in the Chang\u2013Zhu\u2013Tan urban agglomeration (CZTUA), a typical urban agglomeration in China. Results showed that the impervious surface in the study area expanded by 371 km2 with an annual growth rate of 2.25%, primarily at the cost of cropland (169 km2) and forest (206 km2) during the study period. Urban growth has evolved from infilling being the dominant type in the earlier period to mainly edge-expansion and leapfrogging in the core cities, and from no dominant type to mainly leapfrogging in the satellite cities. The unfolding of the \u201ccool center and hot edge\u201d urban growth pattern in CZTUA, characterized by higher expansion rates in the peripheral than in the core cities, may signify a new form of the co-evolution of multi-cities in the process of urbanization. Detailed urban management and planning policies in CZTUA were analyzed. The co-evolution of multi-cities principles need to be studied in more extensive regions, which could help policymakers to promote sustainable and livable development in the future.<\/jats:p>","DOI":"10.3390\/rs12182905","type":"journal-article","created":{"date-parts":[[2020,9,9]],"date-time":"2020-09-09T09:01:09Z","timestamp":1599642069000},"page":"2905","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Co-Evolution of Emerging Multi-Cities: Rates, Patterns and Driving Policies Revealed by Continuous Change Detection and Classification of Landsat Data"],"prefix":"10.3390","volume":"12","author":[{"given":"Maochou","family":"Liu","sequence":"first","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Shuguang","family":"Liu","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Ying","family":"Ning","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Yu","family":"Zhu","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0493-7581","authenticated-orcid":false,"given":"Rub\u00e9n","family":"Valbuena","sequence":"additional","affiliation":[{"name":"School of Natural Sciences, Bangor University, Thoday Building, Bangor LL57 2UW, UK"}]},{"given":"Rui","family":"Guo","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Yuanyuan","family":"Li","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Wenxi","family":"Tang","sequence":"additional","affiliation":[{"name":"National Engineering Laboratory for Applied Technology of Forestry &amp; Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China"},{"name":"College of Biological Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Dengkui","family":"Mo","sequence":"additional","affiliation":[{"name":"College of Forestry, Central South University of Forestry and Technology, Changsha 410004, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8257-1963","authenticated-orcid":false,"given":"Isabel M.D.","family":"Rosa","sequence":"additional","affiliation":[{"name":"School of Natural Sciences, Bangor University, Thoday Building, Bangor LL57 2UW, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9996-2653","authenticated-orcid":false,"given":"Mykola","family":"Kutia","sequence":"additional","affiliation":[{"name":"Bangor College China, Joint Unit of Bangor University, Bangor, UK and Central South University of Forestry and Technology, Changsha 410004, China"}]},{"given":"Wenmin","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Forestry, Central South University of Forestry and Technology, Changsha 410004, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,9]]},"reference":[{"key":"ref_1","unstructured":"UN DESA (United Nations Department of Economic and Social Affairs) (2019). World Urbanization Prospects: The 2018 Revision, United Nations. Available online: https:\/\/www.un.org\/development\/desa\/publications\/2018-revision-of-world-urbanization-prospects.html."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Lin, A., He, L., Zhou, Z., and Yuan, M. (2020). Spatiotemporal Dynamics and Driving Forces of Urban Land-Use Expansion: A Case Study of the Yangtze River Economic Belt, China. Remote Sens., 12.","DOI":"10.3390\/rs12020287"},{"key":"ref_3","unstructured":"Mbow, H.O., Reisinger, A., Canadell, J., and O\u2019Brien, P. (2017). Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems (SR2), IPCC."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"943","DOI":"10.1007\/s11442-017-1414-4","article-title":"New-type urbanization in China: Predicted trends and investment demand for 2015\u20132030","volume":"27","author":"Sun","year":"2017","journal-title":"J. Geogr. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"111430","DOI":"10.1016\/j.rse.2019.111430","article-title":"Characterizing urban infrastructural transitions for the Sustainable Development Goals using multi-temporal land, population, and nighttime light data","volume":"234","author":"Stokes","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.scitotenv.2019.02.178","article-title":"Characterizing the spatial pattern of annual urban growth by using time series Landsat imagery","volume":"666","author":"Fu","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"104563","DOI":"10.1016\/j.landusepol.2020.104563","article-title":"Compact Urban Form and Expansion Pattern Slow Down the Decline in Urban Densities: A Global Perspective","volume":"94","author":"Xu","year":"2020","journal-title":"Land Use Policy"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.scitotenv.2019.01.039","article-title":"Understanding urban expansion combining macro patterns and micro dynamics in three Southeast Asian megacities","volume":"660","author":"Xu","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/j.scitotenv.2015.11.168","article-title":"Spatiotemporal trends of urban heat island effect along the urban development intensity gradient in China","volume":"544","author":"Zhou","year":"2016","journal-title":"Sci. Total Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"9600","DOI":"10.1021\/acs.est.5b00065","article-title":"Spatial and Temporal Dimensions of Urban Expansion in China","volume":"49","author":"Zhao","year":"2015","journal-title":"Environ. Sci. Technol."},{"key":"ref_11","unstructured":"Nuismer, S. (2017). Introduction to Coevolutionary Theory, Macmillan Higher Education. [1st ed.]."},{"key":"ref_12","first-page":"1","article-title":"A coevolutionary theory of the multinational firm","volume":"12","author":"Madhok","year":"2006","journal-title":"J. Int. Manag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.landurbplan.2017.02.014","article-title":"Urban agglomeration: An evolving concept of an emerging phenomenon","volume":"162","author":"Fang","year":"2017","journal-title":"Landsc. Urban Plan."},{"key":"ref_14","unstructured":"Strange, W.C. (2016). Urban Agglomeration. The New Palgrave Dictionary of Economics, Palgrave Macmillan."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"183","DOI":"10.2307\/142511","article-title":"Megalopolis: The Urbanized Northeastern Seaboard of the United States","volume":"39","author":"Vance","year":"1963","journal-title":"Econ. Geogr."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bestor, T.C. (1989). Neighborhood Tokyo, Stanford University Press. [1st ed.].","DOI":"10.1515\/9780804765732"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.rse.2019.02.016","article-title":"Benefits of the free and open Landsat data policy","volume":"224","author":"Zhu","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"105798","DOI":"10.1016\/j.ecolind.2019.105798","article-title":"The seasonal and annual impacts of landscape patterns on the urban thermal comfort using Landsat","volume":"110","author":"Li","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_19","first-page":"1","article-title":"A 30-meter resolution national urban land-cover dataset of China, 2000\u20132015","volume":"2019","author":"Kuang","year":"2019","journal-title":"Earth Syst. Sci. Data Discuss"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.landurbplan.2014.10.010","article-title":"A comparative study of urban expansion in Beijing, Tianjin and Shijiazhuang over the past three decades","volume":"134","author":"Wu","year":"2015","journal-title":"Landsc. Urban Plan."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zou, Y., Peng, H., Liu, G., Yang, K., Xie, Y., and Weng, Q. (2017). Monitoring Urban Clusters Expansion in the Middle Reaches of the Yangtze River, China, Using Time-Series Nighttime Light Images. Remote Sens., 9.","DOI":"10.3390\/rs9101007"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.rse.2019.04.025","article-title":"An efficient approach to capture continuous impervious surface dynamics using spatial-temporal rules and dense Landsat time series stacks","volume":"229","author":"Liu","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"104753","DOI":"10.1016\/j.landusepol.2020.104753","article-title":"Comparing the spatial and temporal dynamics of urban expansion in Guangzhou and Shenzhen from 1975 to 2015: A case study of pioneer cities in China\u2019s rapid urbanization","volume":"97","author":"Meng","year":"2020","journal-title":"Land Use Policy"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"135828","DOI":"10.1016\/j.scitotenv.2019.135828","article-title":"A comparative analysis of urban impervious surface and green space and their dynamics among 318 different size cities in China in the past 25 years","volume":"706","author":"Dou","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.landurbplan.2019.04.008","article-title":"Polycentric urban development and urban thermal environment: A case of Hangzhou, China","volume":"189","author":"Yue","year":"2019","journal-title":"Landsc. Urban Plan."},{"key":"ref_26","unstructured":"Unit, Economist Intelligence (2020, July 17). Supersized Cities: China\u2019s 13 Megalopolises. The Economist., Available online: https:\/\/www.eiu.com\/public\/topical_report.aspx?campaignid=Megalopolis2012."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.scitotenv.2019.02.008","article-title":"Urban land expansion in China\u2019s six megacities from 1978 to 2015","volume":"664","author":"Fei","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1068\/b140002p","article-title":"Coevolution of urban form and built form: A new typomorphological model for Tehran","volume":"42","author":"Shayesteh","year":"2015","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1007\/s10661-010-1660-8","article-title":"Monitoring urban expansion and land use\/land cover changes of Shanghai metropolitan area during the transitional economy (1979\u20132009) in China","volume":"177","author":"Yin","year":"2010","journal-title":"Environ. Monit. Assess."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.gloenvcha.2018.05.001","article-title":"Urban land-use change: The role of strategic spatial planning","volume":"51","author":"Hersperger","year":"2018","journal-title":"Glob. Environ. Chang."},{"key":"ref_31","first-page":"269","article-title":"A simplified urban-extent algorithm to characterize surface urban heat islands on a global scale and examine vegetation control on their spatiotemporal variability","volume":"74","author":"Chakraborty","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"103595","DOI":"10.1016\/j.landurbplan.2019.103595","article-title":"Conceptualizing and characterizing micro-urbanization: A new perspective applied to Africa","volume":"190","author":"Chai","year":"2019","journal-title":"Landsc. Urban Plan."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.rse.2011.10.030","article-title":"Continuous monitoring of forest disturbance using all available Landsat imagery","volume":"122","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.isprsjprs.2019.10.003","article-title":"A time-series classification approach based on change detection for rapid land cover mapping","volume":"158","author":"Yan","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"7708","DOI":"10.3390\/rs6087708","article-title":"Characterizing Spatio-Temporal Dynamics of Urbanization in China Using Time Series of DMSP\/OLS Night Light Data","volume":"6","author":"Xu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41893-020-0521-x","article-title":"High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015","volume":"3","author":"Liu","year":"2020","journal-title":"Nat. Sustain."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.rse.2014.01.011","article-title":"Continuous change detection and classification of land cover using all available Landsat data","volume":"144","author":"Zhu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"110929","DOI":"10.1016\/j.rse.2018.10.011","article-title":"Continuous subpixel monitoring of urban impervious surface using Landsat time series","volume":"238","author":"Deng","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.rse.2019.02.003","article-title":"Near real-time monitoring of tropical forest disturbance: New algorithms and assessment framework","volume":"224","author":"Tang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"509","DOI":"10.14358\/PERS.85.7.509","article-title":"A Novel Method for Separating Woody and Herbaceous Time Series","volume":"85","author":"Zhou","year":"2019","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"20672","DOI":"10.1073\/pnas.0705527105","article-title":"The evolution of urban sprawl: Evidence of spatial heterogeneity and increasing land fragmentation","volume":"104","author":"Irwin","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.cities.2016.04.002","article-title":"Sustainable urbanization in China: A comprehensive literature review","volume":"55","author":"Tan","year":"2016","journal-title":"Cities"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Zhang, J., Yu, L., Li, X., Zhang, C., Shi, T., Wu, X., Yang, C., Gao, W., Li, Q., and Wu, G. (2020). Exploring Annual Urban Expansions in the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal Features and Driving Factors in 1986\u20132017. Remote Sens., 12.","DOI":"10.3390\/rs12162615"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2897","DOI":"10.1016\/j.rse.2010.07.008","article-title":"Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr\u2014Temporal segmentation algorithms","volume":"114","author":"Kennedy","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Zhu, L., Liu, X., Wu, L., Tang, Y., and Meng, Y. (2019). Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11101234"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.rse.2009.08.017","article-title":"An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks","volume":"114","author":"Huang","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-019-13798-8","article-title":"Forest management in southern China generates short term extensive carbon sequestration","volume":"11","author":"Tong","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.isprsjprs.2016.03.008","article-title":"Optical remotely sensed time series data for land cover classification: A review","volume":"116","author":"White","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Cohen, W.B., Healey, S.P., Yang, Z., Zhu, Z., and Gorelick, N. (2020). Diversity of Algorithm and Spectral Band Inputs Improves Landsat Monitoring of Forest Disturbance. Remote Sens., 12.","DOI":"10.3390\/rs12101673"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"137409","DOI":"10.1016\/j.scitotenv.2020.137409","article-title":"Spatiotemporal tracking of carbon emissions and uptake using time series analysis of Landsat data: A spatially explicit carbon bookkeeping model","volume":"720","author":"Tang","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"137214","DOI":"10.1016\/j.scitotenv.2020.137214","article-title":"Mapping the cumulative impacts of long-term mining disturbance and progressive rehabilitation on ecosystem services","volume":"717","author":"Wang","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"106201","DOI":"10.1016\/j.ecolind.2020.106201","article-title":"Spatial monitoring of grassland management using multi-temporal satellite imagery","volume":"113","author":"Stumpf","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.isprsjprs.2017.06.013","article-title":"Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications","volume":"130","author":"Zhu","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1016\/j.isprsjprs.2016.11.004","article-title":"Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative","volume":"122","author":"Zhu","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.rse.2016.03.036","article-title":"Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000\u20132014)","volume":"185","author":"Zhu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.rse.2015.12.040","article-title":"A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery","volume":"175","author":"Fu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.rse.2019.04.020","article-title":"Understanding an urbanizing planet: Strategic directions for remote sensing","volume":"228","author":"Zhu","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1363","DOI":"10.1007\/s11442-019-1664-5","article-title":"Exploring spatial-temporal change and gravity center movement of construction land in the Chang-Zhu-Tan urban agglomeration","volume":"29","author":"Li","year":"2019","journal-title":"J. Geogr. Sci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.compenvurbsys.2017.06.003","article-title":"A machine learning-based method for the large-scale evaluation of the qualities of the urban environment","volume":"65","author":"Liu","year":"2017","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.rdf.2010.10.001","article-title":"China\u2019s regional disparities: Experience and policy","volume":"1","author":"Fan","year":"2011","journal-title":"Rev. Dev. Financ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s11355-018-0349-y","article-title":"Quantifying spatiotemporal patterns concerning land change in Changsha, China","volume":"14","author":"Quan","year":"2018","journal-title":"Landsc. Ecol. Eng."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Berhane, T.M., Lane, C.R., Mengistu, S.G., Christensen, J.R., Golden, H.E., Qiu, S., Zhu, Z., and Wu, Q. (2020). Land-Cover Changes to Surface-Water Buffers in the Midwestern USA: 25 Years of Landsat Data Analyses (1993\u20132017). Remote Sens., 12.","DOI":"10.3390\/rs12050754"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/LGRS.2005.857030","article-title":"A Landsat Surface Reflectance Dataset for North America, 1990\u20132000","volume":"3","author":"Masek","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.rse.2015.08.030","article-title":"Evaluation of the Landsat-5 TM and Landsat-7 ETM+ surface reflectance products","volume":"169","author":"Claverie","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.rse.2015.12.024","article-title":"Characterization of Landsat-7 to Landsat-8 reflective wavelength and normalized difference vegetation index continuity","volume":"185","author":"Roy","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_66","first-page":"2653","article-title":"Landsat ecosystem disturbance adaptive processing system (LEDAPS) algorithm description","volume":"27","author":"Schmidt","year":"2013","journal-title":"Open File Rep."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2439","DOI":"10.1109\/JSTARS.2019.2894553","article-title":"Validation of the LaSRC Cloud Detection Algorithm for Landsat 8 Images","volume":"12","author":"Skakun","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/36.581987","article-title":"Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: An overview","volume":"35","author":"Vermote","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.rse.2017.07.002","article-title":"Improving Fmask cloud and cloud shadow detection in mountainous area for Landsats 4\u20138 images","volume":"199","author":"Qiu","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"111205","DOI":"10.1016\/j.rse.2019.05.024","article-title":"Fmask 4.0: Improved cloud and cloud shadow detection in Landsats 4\u20138 and Sentinel-2 imagery","volume":"231","author":"Qiu","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Xu, H., Wei, Y., Liu, C., Li, X., and Fang, H. (2019). A Scheme for the Long-Term Monitoring of Impervious\u2014Relevant Land Disturbances Using High Frequency Landsat Archives and the Google Earth Engine. Remote Sens., 11.","DOI":"10.3390\/rs11161891"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1080\/01431161.2012.748992","article-title":"Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data","volume":"34","author":"Gong","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Zhou, Q., Rover, J., Brown, J.F., Worstell, B.B., Howard, D., Wu, Z., Gallant, A.L., Rundquist, B., and Burke, M. (2019). Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data. Remote Sens., 11.","DOI":"10.3390\/rs11030328"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"15","DOI":"10.4995\/raet.2016.4029","article-title":"Classification of forest development stages from national low-density lidar datasets: A comparison of machine learning methods","volume":"45","author":"Valbuena","year":"2016","journal-title":"Rev. Teledetecci\u00f3n"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Awty-Carroll, K., Bunting, P., Hardy, A., and Bell, G. (2019). Using Continuous Change Detection and Classification of Landsat Data to Investigate Long-Term Mangrove Dynamics in the Sundarbans Region. Remote Sens., 11.","DOI":"10.3390\/rs11232833"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1016\/j.scib.2019.03.002","article-title":"Stable classification with limited sample: Transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017","volume":"64","author":"Gong","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"111630","DOI":"10.1016\/j.rse.2019.111630","article-title":"Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification","volume":"239","author":"Foody","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1007\/BF00133027","article-title":"Some general principles of landscape and regional ecology","volume":"10","author":"Forman","year":"1995","journal-title":"Landsc. Ecol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1007\/s10980-010-9454-5","article-title":"A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data","volume":"25","author":"Liu","year":"2010","journal-title":"Landsc. Ecol."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/BF00158551","article-title":"A factor analysis of landscape pattern and structure metrics","volume":"10","author":"Riitters","year":"1995","journal-title":"Landsc. Ecol."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"McGarigal, K. (1995). FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure.","DOI":"10.2737\/PNW-GTR-351"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.isprsjprs.2015.03.014","article-title":"Exploring issues of training data imbalance and mislabelling on random forest performance for large area land cover classification using the ensemble margin","volume":"105","author":"Mellor","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.1080\/01431161.2014.885152","article-title":"Assessing the impact of training sample selection on accuracy of an urban classification: A case study in Denver, Colorado","volume":"35","author":"Jin","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_84","first-page":"1204","article-title":"Competence development on the shop floor and industrial upgrading: Case studies of auto makers in China","volume":"26","author":"Krzywdzinski","year":"2014","journal-title":"Int. J. Hum. Resour. Manag."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Wan, Y., Deng, C., Wu, T., Jin, R., Chen, P., and Kou, R. (2019). Quantifying the Spatial Integration Patterns of Urban Agglomerations along an Inter-City Gradient. Sustainability, 11.","DOI":"10.3390\/su11185000"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"101649","DOI":"10.1016\/j.scs.2019.101649","article-title":"Comparison of urban growth patterns and changes between three urban agglomerations in China and three metropolises in the USA from 1995 to 2015","volume":"50","author":"He","year":"2019","journal-title":"Sustain. Cities Soc."},{"key":"ref_87","first-page":"2","article-title":"The Global Automotive Industry Value Chain: What Prospects for Upgrading by Developing Countries","volume":"2","author":"Humphrey","year":"2003","journal-title":"SSRN Electron. J."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.catena.2006.04.019","article-title":"Rapid urbanization in China: A real challenge to soil protection and food security","volume":"69","author":"Chen","year":"2007","journal-title":"Catena"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.landurbplan.2003.09.004","article-title":"Movement of people across the landscape: A blurring of distinctions between areas, interests, and issues affecting natural resource management","volume":"69","author":"Dwyer","year":"2004","journal-title":"Landsc. Urban Plan."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1002\/1520-6688(200023)19:4<569::AID-PAM3>3.0.CO;2-P","article-title":"The environmental impact of suburbanization","volume":"19","author":"Kahn","year":"2000","journal-title":"J. Policy Anal. Manag."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/S0264-8377(01)00018-7","article-title":"Community features and urban sprawl: The case of the Chicago metropolitan region","volume":"18","author":"Zhang","year":"2001","journal-title":"Land Use Policy"},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/tqem.1000","article-title":"Environment, Quality of Life, and Urban Growth in the New Economy","volume":"10","author":"Hirschhorn","year":"2001","journal-title":"Environ. Qual. Manag."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1007\/s11442-019-1665-3","article-title":"Evolution and driving forces of rural functions in urban agglomeration: A case study of the Chang-Zhu-Tan region","volume":"29","author":"Tan","year":"2019","journal-title":"J. Geogr. Sci."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"1286","DOI":"10.1016\/j.scitotenv.2019.06.179","article-title":"Policy-driven changes in enclosure fisheries of large lakes in the Yangtze Plain: Evidence from satellite imagery","volume":"688","author":"Dai","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_95","first-page":"660","article-title":"Methods of dividing the boundary of urban agglomerations: Chang-Zhu-Tan Urban Agglomeration as a case","volume":"30","author":"Chen","year":"2010","journal-title":"Sci. Geogr. Sin."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.ecoenv.2012.06.021","article-title":"Distribution patterns and major sources of dioxins in soils of the Changsha-Zhuzhou-Xiangtan urban agglomeration, China","volume":"84","author":"Yang","year":"2012","journal-title":"Ecotoxicol. Environ. 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