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However, relying solely on socioeconomic indicators or low\u2010resolution nighttime light data hinders the precision of poverty identification. Moreover, the spatial characteristics of buildings, as key indicators of socioeconomic development, remain under\u2010investigated for their potential in identifying impoverished areas. To bridge these gaps, this study combined high\u2010resolution (10\u2010m) SDGSAT\u20101 nighttime light with three\u2010dimensional (3D) building indicators to enable precise poverty identification. The XGBoost algorithm was employed to assess the Multidimensional Poverty Index (MPI) for counties within Jiangxi Province, China. A comparison was also made with conventional NPP\u2010VIIRS nighttime light (500\u2010m resolution). The findings indicate that the incorporation of 3D building indicators into SDGSAT\u20101 data substantially improves model performance, providing a more robust poverty estimation than single\u2010source datasets. Specifically, the combined model achieved R\n                    <jats:sup>2<\/jats:sup>\n                    values of 0.8986 and 0.8540 for SDGSAT\u20101 and NPP\u2010VIIRS, respectively. This represents an information gain of 0.1160 for the high\u2010resolution SDGSAT\u20101 data compared to its baseline value of 0.7826. Additionally, SHAP analysis elucidates that \u201cmean building height\u201d, \u201csky view factor\u201d, and \u201cstandard deviation of pixel light values\u201d are the predominant drivers of the model. In conclusion, combining 3D building indicators with fine\u2010grained nighttime light data enables a higher precision in identifying poverty across county\u2010level units. This approach presents a novel methodology for the timely monitoring of poverty across large regions. These findings provide a robust foundation for optimizing resource allocation and informing sustainable poverty alleviation strategies.\n                  <\/jats:p>","DOI":"10.1111\/tgis.70332","type":"journal-article","created":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T05:44:30Z","timestamp":1782971070000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Combining Three\u2010Dimensional Building Indicators With\n                    <scp>SDGSAT<\/scp>\n                    \u20101 Nighttime Light Data for Poverty Identification\u2014A Case Study in Jiangxi, China"],"prefix":"10.1111","volume":"30","author":[{"given":"Jiali","family":"Yang","sequence":"first","affiliation":[{"name":"School of Geography and Remote Sensing Guangzhou University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifei","family":"Liufu","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing Guangzhou University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zejia","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing Guangzhou University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5048-6510","authenticated-orcid":false,"given":"Jinyao","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing Guangzhou University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaoying","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing Guangzhou University  Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinchang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Geography and Remote Sensing Guangzhou University  Guangzhou China"},{"name":"College of Geography and Remote Sensing Sciences Xinjiang University  Urumqi China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,1]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpubeco.2010.11.006"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.worlddev.2014.01.026"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2023.3320192"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1080\/17516234.2024.2325857"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.5194\/essd\u201016\u20105357\u20102024"},{"key":"e_1_2_10_7_1","doi-asserted-by":"crossref","unstructured":"Chen T. 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