{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T18:01:34Z","timestamp":1772906494281,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T00:00:00Z","timestamp":1631232000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UCMexus","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]},{"name":"UCMexus","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>One of the challenges in the fight against poverty is the precise localization and assessment of vulnerable communities\u2019 sprawl. The characterization of vulnerability is traditionally accomplished using nationwide census exercises, a burdensome process that requires field visits by trained personnel. Unfortunately, most countrywide censuses exercises are conducted only sporadically, making it difficult to track the short-term effect of policies to reduce poverty. This paper introduces a definition of vulnerability following UN-Habitat criteria, assesses different CNN machine learning architectures, and establishes a mapping between satellite images and survey data. Starting with the information corresponding to the 2,178,508 residential blocks recorded in the 2010 Mexican census and multispectral Landsat-7 images, multiple CNN architectures are explored. The best performance is obtained with EfficientNet-B3 achieving an area under the ROC and Precision-Recall curves of 0.9421 and 0.9457, respectively. This article shows that publicly available information, in the form of census data and satellite images, along with standard CNN architectures, may be employed as a stepping stone for the countrywide characterization of vulnerability at the residential block level.<\/jats:p>","DOI":"10.3390\/rs13183603","type":"journal-article","created":{"date-parts":[[2021,9,12]],"date-time":"2021-09-12T21:48:01Z","timestamp":1631483281000},"page":"3603","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Fine-Grained Large-Scale Vulnerable Communities Mapping via Satellite Imagery and Population Census Using Deep Learning"],"prefix":"10.3390","volume":"13","author":[{"given":"Joaqu\u00edn","family":"Salas","sequence":"first","affiliation":[{"name":"CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Cerro Blanco 141, Colinas del Cimatario, Quer\u00e9taro 76090, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3286-3962","authenticated-orcid":false,"given":"Pablo","family":"Vera","sequence":"additional","affiliation":[{"name":"CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Cerro Blanco 141, Colinas del Cimatario, Quer\u00e9taro 76090, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marivel","family":"Zea-Ortiz","sequence":"additional","affiliation":[{"name":"CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Cerro Blanco 141, Colinas del Cimatario, Quer\u00e9taro 76090, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8611-8661","authenticated-orcid":false,"given":"Elio-Atenogenes","family":"Villase\u00f1or","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Estad\u00edstica y Geograf\u00eda, H\u00e9roe de Nacozari Sur 2301, Jardines del Parque, Aguascalientes 20276, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6374-9663","authenticated-orcid":false,"given":"Dagoberto","family":"Pulido","sequence":"additional","affiliation":[{"name":"CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Cerro Blanco 141, Colinas del Cimatario, Quer\u00e9taro 76090, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alejandra","family":"Figueroa","sequence":"additional","affiliation":[{"name":"Instituto Nacional de Estad\u00edstica y Geograf\u00eda, H\u00e9roe de Nacozari Sur 2301, Jardines del Parque, Aguascalientes 20276, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Atamanov, A., Lakner, C., Mahler, D.G., Tetteh Baah, S.K., and Yang, J. 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