{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T20:30:15Z","timestamp":1777062615203,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2017,8,2]],"date-time":"2017-08-02T00:00:00Z","timestamp":1501632000000},"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":["41330747"],"award-info":[{"award-number":["41330747"]}],"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>Nighttime light data can characterize urbanization, economic development, population density, energy consumption and other human activities. Additionally, carbon dioxide (CO2) emissions are closely related to the scope and intensity of human activities. In this study, we assess the utility of nighttime light data as a powerful tool to reflect CO2 emissions from energy consumption, analyze the uncertainty associated with different nighttime light data for modeling CO2 emissions, and provide guidance and a reference for modeling CO2 emissions based on nighttime light data. In this paper, Mainland China was taken as a case study, and nighttime light datasets (the Defense Meteorological Satellite Program\u2019s Operational Linescan System (DMSP-OLS) nighttime light data and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data) as well as a global gridded CO2 emissions dataset (PKU-CO2) were used to perform simple regressions at provincial, prefectural and 0.1\u00b0 \u00d7 0.1\u00b0 grid levels, respectively. The analyses are aimed at exploring the accuracy and uncertainty of DMSP-OLS and NPP-VIIRS nighttime light data in modeling CO2 emissions at different spatial scales. The improvement of nighttime light index and the potential factors influencing the effects of modeling CO2 emissions based on nighttime light datasets were also explored. The results show that DMSP-OLS is superior to NPP-VIIRS in modeling CO2 emissions at all spatial scales, and the bigger the scale, the more evident the advantages of DMSP-OLS. When modeling CO2 emissions with nighttime light datasets, not only the total amount of lights within a given statistical unit but also the agglomeration degree of lights should be taken into account. Furthermore, the geographical location and socio-economic conditions at the study site, such as gross regional product per capita (GRP per capita), population, and urbanization were shown to have an impact on the regression effect of the nighttime lights-CO2 emissions model. The regression effect was found to be better at higher latitude and longitude areas with higher GRP per capita and higher urbanization, while population showed little effect on the regression effect of the nighttime lights - CO2 emissions model. The limitation of this study is that the thresholds of potential factors are unclear and the quantitative guidance is insufficient.<\/jats:p>","DOI":"10.3390\/rs9080797","type":"journal-article","created":{"date-parts":[[2017,8,2]],"date-time":"2017-08-02T10:05:25Z","timestamp":1501668325000},"page":"797","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["The Uncertainty of Nighttime Light Data in Estimating Carbon Dioxide Emissions in China: A Comparison between DMSP-OLS and NPP-VIIRS"],"prefix":"10.3390","volume":"9","author":[{"given":"Xiwen","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory for Urban Habitat Environmental Science and Technology, Shenzhen Graduate School, Peking University, Shenzhen 518055, China"},{"name":"Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiansheng","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory for Urban Habitat Environmental Science and Technology, Shenzhen Graduate School, Peking University, Shenzhen 518055, China"},{"name":"Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Peng","sequence":"additional","affiliation":[{"name":"Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1604-4628","authenticated-orcid":false,"given":"Qiwen","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Architecture, Tsinghua University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1038\/scientificamerican0778-86","article-title":"Nighttime images of the earth from space","volume":"239","author":"Croft","year":"1978","journal-title":"Sci. Am."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1080\/01431160304982","article-title":"Validation of urban boundaries derived from global night-time satellite imagery","volume":"24","author":"Henderson","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.rse.2005.02.002","article-title":"Spatial analysis of global urban extent from DMSP-OLS night lights","volume":"96","author":"Small","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s10708-007-9104-x","article-title":"Potential for global mapping of development via a nightsat mission","volume":"69","author":"Elvidge","year":"2007","journal-title":"Geojournal"},{"key":"ref_5","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_6","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_7","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_8","first-page":"1303","article-title":"A Comparison of Nighttime Satellite Imagery and Population Density for the Continental United States","volume":"63","author":"Sutton","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_9","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_10","first-page":"1037","article-title":"Modeling the Population of China Using DMSP Operational Linescan System Nighttime Data","volume":"67","author":"Lo","year":"2001","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1080\/01431160802345685","article-title":"Spatial characterization of electrical power consumption patterns over India using temporal DMSP-OLS night-time satellite data","volume":"30","author":"Badarinath","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4443","DOI":"10.1080\/01431160903277464","article-title":"Estimating energy consumption from night-time DMPS\/OLS imagery after correcting for saturation effects","volume":"31","author":"Letu","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"8118","DOI":"10.1080\/01431161.2013.833358","article-title":"Detection of rural electrification in Africa using DMSP-OLS night lights imagery","volume":"34","author":"Brian","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","first-page":"1249","article-title":"Exurban change detection in fire-prone areas with nighttime satellite imagery","volume":"70","author":"Theobald","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/1476-072X-12-23","article-title":"A case-referent study: Light at night and breast cancer risk in Georgia","volume":"12","author":"Sarah","year":"2013","journal-title":"Int. J. Health Geogr."},{"key":"ref_16","first-page":"62","article-title":"Why VIIRS data are superior to DMSP for mapping nighttime lights","volume":"35","author":"Christopher","year":"2013","journal-title":"Proc. Asia Pac. Adv. Netw."},{"key":"ref_17","first-page":"70","article-title":"Nighttime Lights Compositing Using the VIIRS Day-Night Band: Preliminary Results","volume":"35","author":"Kimberly","year":"2013","journal-title":"Proc. Asia Pac. Adv. Netw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3057","DOI":"10.3390\/rs5063057","article-title":"Potential of NPP-VIIRS Nighttime Light Imagery for Modeling the Regional Economy of China","volume":"5","author":"Li","year":"2013","journal-title":"Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1705","DOI":"10.3390\/rs6021705","article-title":"Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data","volume":"6","author":"Shi","year":"2014","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Jing, X., Shao, X., Cao, C., Fu, X., and Yan, L. (2016). Comparison between the Suomi-NPP Day-Night Band and DMSP-OLS for Correlating Socio-Economic Variables at the Provincial Level in China. Remote Sens., 8.","DOI":"10.3390\/rs8010017"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1080\/2150704X.2014.905728","article-title":"Evaluation of NPP-VIIRS nighttime light composite data for extracting built-up urban areas","volume":"5","author":"Shi","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1080\/15481603.2015.1022420","article-title":"Modelling and mapping total freight traffic in China using NPP-VIIRS nighttime light composite data","volume":"52","author":"Shi","year":"2015","journal-title":"GISci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/S0924-2716(01)00040-5","article-title":"Night-time Lights of the World 1994\u20131995","volume":"56","author":"Elvidge","year":"2001","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","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 J. Hum. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4756","DOI":"10.1016\/j.enpol.2009.08.021","article-title":"Regional Variations in Spatial Structure of Nightlights, Population Density and Fossil-fuel CO2 Emissions","volume":"38","author":"Raupach","year":"2010","journal-title":"Energy Policy"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1016\/j.energy.2014.04.103","article-title":"Estimating CO2 (carbon dioxide) emissions at urban scales by DMSP\/OLS (Defense Meteorological Satellite Program\u2019s Operational Linescan System) nighttime light imagery: Methodological challenges and a case study for China","volume":"71","author":"Meng","year":"2014","journal-title":"Energy"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.rser.2014.04.015","article-title":"China\u2019s 19-Year City-Level Carbon Emissions of Energy Consumptions, Driving Forces and Regionalized Mitigation Guidelines","volume":"35","author":"Su","year":"2014","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.applthermaleng.2016.01.093","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_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0138310","article-title":"Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO2 Emissions: A Comparison with DMSP-OLS Nighttime Light Data","volume":"10","author":"Ou","year":"2015","journal-title":"PLoS ONE"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"595","DOI":"10.3390\/en20300595","article-title":"A fifteen year record of global natural gas Flaring Derived from Satellite Data","volume":"2","author":"Elvidge","year":"2009","journal-title":"Energies"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1109\/TGRS.2011.2178031","article-title":"A Saturated Light Correction Method for DMSP\/OLS Nighttime Satellite Imagery","volume":"50","author":"Letu","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"7356","DOI":"10.1080\/01431161.2013.820365","article-title":"Intercalibration of DMSP-OLS night-time light data by the invariant region method","volume":"34","author":"Wu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_33","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_34","doi-asserted-by":"crossref","first-page":"5189","DOI":"10.5194\/acp-13-5189-2013","article-title":"High-resolution mapping of combustion processes and implications for CO2 emissions","volume":"13","author":"Wang","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1038\/nature14677","article-title":"Reduced carbon emission estimates from fossil fuel combustion and cement production in China","volume":"524","author":"Zhu","year":"2015","journal-title":"Nature"},{"key":"ref_36","unstructured":"Kaya, Y. (1989). Impact of Carbon Dioxide Emission on GNP Growth: Interpretation of Proposed Scenarios, IPCC."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/B:POEN.0000039950.85422.eb","article-title":"Examining the impact of demographic factors on air pollution population and environment","volume":"26","author":"Cole","year":"2004","journal-title":"Popul. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/S0921-8009(02)00223-9","article-title":"The impact of population pressure on global carbon dioxide emissions, 1975\u20131996: Evidence from pooled cross-eountry data","volume":"44","author":"Shi","year":"2003","journal-title":"Ecol. Econ."},{"key":"ref_39","unstructured":"David, F.G., and Jason, Z.Y. (2017, August 02). Urbanization and energy in China: Issues and Implications. Available online: http:\/\/pirate.shu.edu\/~yinjason\/papers\/final%20version5-14-2001.pdf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0264-8377(95)00027-5","article-title":"The land use\u2014Transport connection: An overview","volume":"13","author":"Newman","year":"1996","journal-title":"Land Use Policy"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1080\/01944360108976228","article-title":"Urban Form and Thermal Efficiency: How the Design of Cities Influences the Urban Heat Island Effect","volume":"67","author":"Stone","year":"2001","journal-title":"J. Am. Plan. Assoc."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10511482.2008.9521624","article-title":"The Impact of Urban Form on U.S. Residential Energy Use","volume":"19","author":"Ewing","year":"2008","journal-title":"Hous. Policy Debate"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/8\/797\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:44:53Z","timestamp":1760208293000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/8\/797"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,2]]},"references-count":42,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2017,8]]}},"alternative-id":["rs9080797"],"URL":"https:\/\/doi.org\/10.3390\/rs9080797","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,2]]}}}