{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T17:16:24Z","timestamp":1726420584166},"reference-count":57,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,14]],"date-time":"2019-09-14T00:00:00Z","timestamp":1568419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Using artificial light data measured from satellites has the potential to change research methods in geography and urban planning. The Defense Meteorological Satellite Program Optical Linescan System (DMSP-OLS) night-time light datasets provided consistent and valuable data sources for investigating urbanization processes. This study intends to empirically investigate the relationship between night-time lights, population, and urban development patterns. A novel protocol was developed to integrate heterogeneous datasets into a standardized unit of analysis. Multivariate mixed-effects models were applied to detect correlations within and between provinces in South Korea. To capture physical variations of urban development, four landscape metrics were used and tested in the analyses. Diminishing returns of night-time lights to population were found in all models. In single landscape metric models, all coefficients of landscape metrics were positively related to night-time lights. In combination models, the aggregation index (AI) was no longer statistically significant. The protocol developed in this study provides an effective way to create analytical units for integrating heterogeneous forms of data. Creating standardized units of analyses will make it possible for researchers to compare their results with other studies. Landscape metrics used in this study for capturing the composition and configuration of urban development patterns will enrich the discussion in the future.<\/jats:p>","DOI":"10.3390\/rs11182140","type":"journal-article","created":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T07:17:57Z","timestamp":1568618277000},"page":"2140","source":"Crossref","is-referenced-by-count":12,"title":["Night on South Korea: Unraveling the Relationship between Urban Development Patterns and DMSP-OLS Night-Time Lights"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-1443-0135","authenticated-orcid":false,"given":"Mingyu","family":"Kang","sequence":"first","affiliation":[{"name":"Korea Research Institute for Human Settlements (KRIHS), Sejong-si 30147, Korea"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-7592-1512","authenticated-orcid":false,"given":"Meen","family":"Jung","sequence":"additional","affiliation":[{"name":"Department of Urban Design and Planning, University of Washington, Seattle, WA 98195, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Mellander, C., Lobo, J., Stolarick, K., and Matheson, Z. (2015). Night-Time Light Data: A Good Proxy Measure for Economic Activity?. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0139779"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.rse.2012.04.018","article-title":"Quantitative estimation of urbanization dynamics using time series of DMSP\/OLS nighttime light data: A comparative case study from China\u2019s cities","volume":"124","author":"Ma","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_3","first-page":"727","article-title":"Mapping of city lights using DMSP Operational Linescan System data","volume":"63","author":"Elvidge","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_4","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_5","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/S0034-4257(97)00046-1","article-title":"A technique for using composite DMSP\/OLS \u201cCity Lights\u201d satellite data to map urban area","volume":"61","author":"Imhoff","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S0034-4257(98)00098-4","article-title":"Radiance Calibration of DMSP-OLS Low-Light Imaging Data of Human Settlements","volume":"68","author":"Elvidge","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.rse.2010.08.021","article-title":"Spatial scaling of stable night lights","volume":"115","author":"Small","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1080\/01431160802430693","article-title":"Modelling the population density of China at the pixel level based on DMSP\/OLS non-radiance-calibrated night-time light images","volume":"30","author":"Zhuo","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4459","DOI":"10.1080\/01431160903261005","article-title":"The use of night-time lights satellite imagery as a measure of Australia\u2019s regional electricity consumption and population distribution","volume":"31","author":"Townsend","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.compenvurbsys.2003.09.004","article-title":"Estimating population and energy consumption in Brazilian Amazonia using DMSP night-time satellite data","volume":"29","author":"Amaral","year":"2005","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1890\/1540-9295(2004)002[0191:ELP]2.0.CO;2","article-title":"Ecological light pollution","volume":"2","author":"Longcore","year":"2004","journal-title":"Front. Ecol. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.1080\/01431160120888","article-title":"DMSP-OLS estimation of tropical forest area impacted by surface fires in Roraima, Brazil: 1995 versus 1998","volume":"22","author":"Elvidge","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"De La Cruz, A., Laneve, G., Cerra, D., Mielewczyk, M., Garcia, M.J., Santilli, G., Cadau, E., and Joyanes, G. (2007). On the Application of Nighttime Sensors for Rapid Detection of Areas Impacted by Disasters. Lecture Notes in Geoinformation and Cartography, Springer Science and Business Media LLC.","DOI":"10.1007\/978-3-540-72108-6_2"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"9359","DOI":"10.3390\/rs6109359","article-title":"The Integrated Use of DMSP-OLS Nighttime Light and MODIS Data for Monitoring Large-Scale Impervious Surface Dynamics: A Case Study in the Yangtze River Delta","volume":"6","author":"Shao","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1080\/15481603.2015.1007778","article-title":"A new method for extracting built-up urban areas using DMSP-OLS nighttime stable lights: A case study in the Pearl River Delta, southern China","volume":"52","author":"Su","year":"2015","journal-title":"GISci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1093\/cjres\/rsn018","article-title":"The rise of the mega-region","volume":"1","author":"Florida","year":"2008","journal-title":"Camb. J. Reg. Econ. Soc."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1257\/aer.101.3.194","article-title":"A Bright Idea for Measuring Economic Growth","volume":"101","author":"Henderson","year":"2011","journal-title":"Am. Econ. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1257\/aer.102.2.994","article-title":"MEASURING ECONOMIC GROWTH FROM OUTER SPACE","volume":"102","author":"Henderson","year":"2012","journal-title":"Am. Econ. Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1579\/0044-7447-29.3.157","article-title":"Night-time Imagery as a Tool for Global Mapping of Socioeconomic Parameters and Greenhouse Gas Emissions","volume":"29","author":"Doll","year":"2000","journal-title":"Ambio"},{"key":"ref_20","first-page":"5","article-title":"Estimation of gross domestic product at sub-national scales using nighttime satellite imagery","volume":"8","author":"Sutton","year":"2007","journal-title":"Int. J. Ecol. Econ. Stat."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1080\/00330124.2011.583590","article-title":"Global Metropolis: Assessing Economic Activity in Urban Centers Based on Nighttime Satellite Images","volume":"64","author":"Florida","year":"2012","journal-title":"Prof. Geogr."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","first-page":"3476","DOI":"10.3390\/rs5073476","article-title":"Can Night-Time Light Data Identify Typologies of Urbanization? A Global Assessment of Successes and Failures","volume":"5","author":"Zhang","year":"2013","journal-title":"Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"7301","DOI":"10.1073\/pnas.0610172104","article-title":"Growth, innovation, scaling, and the pace of life in cities","volume":"104","author":"Bettencourt","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.compenvurbsys.2016.04.006","article-title":"Diverse cities or the systematic paradox of Urban Scaling Laws","volume":"63","author":"Cottineau","year":"2017","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Bettencourt, L.M.A., Lobo, J., Strumsky, D., and West, G.B. (2010). Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities. PLoS ONE, 5.","DOI":"10.1371\/journal.pone.0013541"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.envpol.2015.08.039","article-title":"An optimum city size? The scaling relationship for urban population and fine particulate (PM 2.5) concentration","volume":"208","author":"Han","year":"2016","journal-title":"Environ. Pollut."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1111\/j.1467-9787.2009.00635.x","article-title":"THE COMPLEMENTARITY BETWEEN CITIES AND SKILLS","volume":"50","author":"Glaeser","year":"2010","journal-title":"J. Reg. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1016\/S1574-0080(04)80006-3","article-title":"Chapter 49 Evidence on the nature and sources of agglomeration economies","volume":"4","author":"Rosenthal","year":"2004","journal-title":"Handb. Reg. Urban Econ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.jue.2006.08.003","article-title":"Urban density and the rate of invention","volume":"61","author":"Carlino","year":"2007","journal-title":"J. Urban Econ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1016\/j.jue.2007.07.005","article-title":"Metropolitan patenting, inventor agglomeration and social networks: A tale of two effects","volume":"63","author":"Lobo","year":"2008","journal-title":"J. Urban Econ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1111\/j.1536-7150.2010.00764.x","article-title":"Do We Still Need Cities? Evidence on Rates of Innovation from Count Data Models of Metropolitan Statistical Area Patents","volume":"70","author":"Sedgley","year":"2011","journal-title":"Am. J. Econ. Soc."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2155","DOI":"10.1016\/j.physa.2011.02.013","article-title":"Scaling of Prosocial Behavior in Cities","volume":"390","author":"Arbesman","year":"2011","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.jum.2018.04.006","article-title":"Impacts of urbanization on land use\/cover changes and its probable implications on local climate and groundwater level","volume":"7","author":"Patra","year":"2018","journal-title":"J. Urban Manag."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"330","DOI":"10.3390\/rs1030330","article-title":"Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data Using Post-Classification Enhancement","volume":"1","author":"Manandhar","year":"2009","journal-title":"Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"12070","DOI":"10.3390\/rs61212070","article-title":"Global Land Cover Mapping: A Review and Uncertainty Analysis","volume":"6","author":"Congalton","year":"2014","journal-title":"Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"6026","DOI":"10.3390\/rs5116026","article-title":"Exploring the Use of Google Earth Imagery and Object-Based Methods in Land Use\/Cover Mapping","volume":"5","author":"Hu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1016\/S0034-4257(01)00311-X","article-title":"Sensitivity of multitemporal NOAA AVHRR data of an urbanizing region to land-use\/land-cover changes and misregistration","volume":"80","author":"Stow","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.rse.2014.11.022","article-title":"Night-time light derived estimation of spatio-temporal characteristics of urbanization dynamics using DMSP\/OLS satellite data","volume":"158","author":"Ma","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_40","first-page":"351","article-title":"FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure","volume":"122","author":"McGarigal","year":"1995","journal-title":"Gen. Tech. Rep."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s10980-009-9327-y","article-title":"Surface metrics: An alternative to patch metrics for the quantification of landscape structure","volume":"24","author":"McGarigal","year":"2009","journal-title":"Landsc. Ecol."},{"key":"ref_42","first-page":"205","article-title":"A computational framework for generalized moving windows and its application to landscape pattern analysis","volume":"44","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s11252-010-0148-1","article-title":"Tree diversity, distribution, history and change in urban parks: Studies in Bangalore, India","volume":"14","author":"Nagendra","year":"2011","journal-title":"Urban Ecosyst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1016\/j.cities.2010.05.001","article-title":"Factors generating boardings at Metro stations in the Seoul metropolitan area","volume":"27","author":"Sohn","year":"2010","journal-title":"Cities"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/S0264-2751(00)00021-4","article-title":"High-speed rail developments and spatial restructuring: A case study of the Capital region in South Korea","volume":"17","author":"Kim","year":"2000","journal-title":"Cities"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Chu, H.-J., Yang, C.-H., and Chou, C.C. (2019). Adaptive Non-Negative Geographically Weighted Regression for Population Density Estimation Based on Nighttime Light. ISPRS Int. J. Geo.-Inf., 8.","DOI":"10.3390\/ijgi8010026"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2011.12.005","article-title":"High spatial resolution night-time light images for demographic and socio-economic studies","volume":"119","author":"Levin","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_48","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_49","doi-asserted-by":"crossref","first-page":"13469","DOI":"10.3390\/su71013469","article-title":"Multi-Scale Measurement of Regional Inequality in Mainland China during 2005\u20132010 Using DMSP\/OLS Night Light Imagery and Population Density Grid Data","volume":"7","author":"Xu","year":"2015","journal-title":"Sustainability"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1126\/science.1235823","article-title":"The Origins of Scaling in Cities","volume":"340","author":"Bettencourt","year":"2013","journal-title":"Science"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.respol.2006.09.026","article-title":"Invention in the city: Increasing returns to patenting as a scaling function of metropolitan size","volume":"36","author":"Bettencourt","year":"2007","journal-title":"Res. Policy"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"147","DOI":"10.2174\/1874923201003010147","article-title":"Shedding Light on the Global Distribution of Economic Activity","volume":"3","author":"Ghosh","year":"2010","journal-title":"Open Geogr. J."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1186\/1476-072X-4-5","article-title":"From wealth to health: Modelling the distribution of income per capita at the sub-national level using night-time light imagery","volume":"4","author":"Ebener","year":"2005","journal-title":"Int. J. Heal. Geogr."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.ecolecon.2005.03.007","article-title":"Mapping regional economic activity from night-time light satellite imagery","volume":"57","author":"Doll","year":"2006","journal-title":"Ecol. Econ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1080\/01431160500181861","article-title":"DMSP\/OLS night-time light imagery for urban population estimates in the Brazilian Amazon","volume":"27","author":"Amaral","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Wang, X., Rafa, M., Moyer, J.D., Li, J., Scheer, J., and Sutton, P. (2019). Estimation and Mapping of Sub-National GDP in Uganda Using NPP-VIIRS Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11020163"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Fragkias, M., Lobo, J., Strumsky, D., and Seto, K.C. (2013). Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0064727"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2140\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T15:08:26Z","timestamp":1718896106000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2140"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,14]]},"references-count":57,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["rs11182140"],"URL":"https:\/\/doi.org\/10.3390\/rs11182140","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,14]]}}}