{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T07:01:07Z","timestamp":1780297267734,"version":"3.54.0"},"reference-count":34,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Transactions in GIS"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>There is an increasing demand for carbon emission data accuracy, but existing studies rely mainly on single or limited economic and social indicators such as nighttime lighting and population density, while largely neglecting the influence of environmental factors, resulting in insufficient carbon emission data accuracy. To address this limitation, and considering the direct and indirect impacts of environmental variables on carbon emissions, we introduced land cover data as an environmental factor and developed a Socio\u2010Economic\u2010Environmental (SEE) downscaling framework. The framework integrates population, gross domestic product (GDP), land use data, and NDVI to capture the interactions between natural and artificial environmental factors. Furthermore, by systematically comparing different combinations of variables as well as alternative modeling approaches, we identified the optimal model configuration for high\u2010resolution carbon emission estimation. After applying the model to the Beijing\u2013Tianjin\u2013Hebei (BTH) and Yangtze River Delta (YRD) urban agglomerations, we successfully downscaled carbon emission grids from a resolution of 0.1\u00b0 to 1\u2009km. Through the comparative analysis of the 1\u2010km resolution carbon emission grid data in 2019 and 2020, we reveal the differentiated impacts of the natural and artificial environments on carbon emissions, as well as the refined distribution characteristics of carbon emissions within different urban agglomerations. By integrating ecological and anthropogenic factors, the SEE model covers a wider range of carbon emission determinants and improves the precision and accuracy of carbon emission data.<\/jats:p>","DOI":"10.1111\/tgis.70272","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T05:46:33Z","timestamp":1778823993000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Advancing Urban Carbon Emission Downscaling to 1\u2009km Resolution: A Deep Learning\u2010Based Socio\u2010Economic\u2010Environmental (\n                    <scp>SEE<\/scp>\n                    ) Framework"],"prefix":"10.1111","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1274-7099","authenticated-orcid":false,"given":"Zehao","family":"Shen","sequence":"first","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuning","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Klaus","family":"Fraedrich","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Meteorology  Hamburg Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingyi","family":"Du","sequence":"additional","affiliation":[{"name":"School of Geomatics and Urban Spatial Informatics Beijing University of Civil Engineering and Architecture  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.5194\/acp\u201016\u201014979\u20102016"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467\u20109868.2007.00633.x"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1198\/jcgs.2010.09051"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.5067\/MODIS\/MOD13A3.061"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597\u2010023\u201001963\u20100"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.5194\/egusphere\u2010egu23\u20103303"},{"key":"e_1_2_9_8_1","volume-title":"Hands\u2010On Machine Learning With Scikit\u2010Learn, Keras, and TensorFlow","author":"G\u00e9ron A.","year":"2022"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.3390\/en3121895"},{"key":"e_1_2_9_10_1","unstructured":"Global gRidded dAily CO2 Emission Dataset.2021.https:\/\/carbonmonitor\u2010graced.com\/."},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2019.133805"},{"key":"e_1_2_9_12_1","first-page":"1","volume-title":"Deep Learning","author":"Goodfellow I.","year":"2016"},{"key":"e_1_2_9_13_1","first-page":"2672","volume-title":"Advances in Neural Information Processing Systems","author":"Goodfellow I. J.","year":"2014"},{"key":"e_1_2_9_14_1","first-page":"102","article-title":"Spatial Distribution Simulation of Carbon Emissions in Jiangsu Province Based on DMSP\/OLS and NDVI","volume":"4","author":"Guo X.","year":"2016","journal-title":"World Geography Research"},{"key":"e_1_2_9_15_1","unstructured":"Hong X.\u201cComparative Study on Spatialization Methods for Energy Consumption Carbon Emissions Based on Nighttime Light Data and Land Use Data\u201d(MA thesis Henan University 2019)."},{"key":"e_1_2_9_16_1","unstructured":"IPCC.2023.\u201cAR6 Synthesis Report: Climate Change 2023.\u201dhttps:\/\/www.ipcc.ch\/report\/sixth\u2010assessment\u2010report\u2010cycle\/."},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.5194\/acp\u201015\u201011411\u20102015"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jenvman.2024.122723"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2015.1123632"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597\u2010024\u201002913\u20100"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597\u2010020\u201000708\u20107"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467\u2010020\u201018922\u20107"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.5194\/acp\u201011\u2010543\u20102011"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.5194\/essd\u201010\u201087\u20102018"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.11821\/yj2010090010"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2008.2005605"},{"key":"e_1_2_9_30_1","doi-asserted-by":"publisher","DOI":"10.11821\/xb201110010"},{"key":"e_1_2_9_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2025.106435"},{"key":"e_1_2_9_32_1","doi-asserted-by":"publisher","DOI":"10.12078\/2017121102"},{"key":"e_1_2_9_33_1","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.5816591"},{"key":"e_1_2_9_34_1","doi-asserted-by":"publisher","DOI":"10.11821\/dlxb201311007"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41612\u2010025\u201001071\u20103"}],"container-title":["Transactions in GIS"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/tgis.70272","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/tgis.70272","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/tgis.70272","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T06:13:04Z","timestamp":1780294384000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/tgis.70272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":34,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["10.1111\/tgis.70272"],"URL":"https:\/\/doi.org\/10.1111\/tgis.70272","archive":["Portico"],"relation":{},"ISSN":["1361-1682","1467-9671"],"issn-type":[{"value":"1361-1682","type":"print"},{"value":"1467-9671","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"2025-09-10","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-16","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-05-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70272"}}