{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:22:48Z","timestamp":1775326968659,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,19]],"date-time":"2021-07-19T00:00:00Z","timestamp":1626652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"H2020 E-SHAPE project\u2014EuroGEO Showcases: Applications Powered by Europe","award":["820852"],"award-info":[{"award-number":["820852"]}]},{"name":"SMURBS project - SMart URBan Solutions for air quality, disasters and city growth, funded by the European Commission in the framework of program ERA-PLANET","award":["689443"],"award-info":[{"award-number":["689443"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Local and Regional Authorities require indicators at the intra-urban scale to design adequate policies to foster the achievement of the objectives of Sustainable Development Goal (SDG) 11. Updated high-resolution population density and settlement maps are the basic input products for such indicators and their sub-indicators. When provided at the intra-urban scale, these essential variables can facilitate the extraction of population flows, including both local and regular migrant components. This paper discusses a modification of the dasymetric method implemented in our previous work, aimed at improving the population density estimation. The novelties of our paper include the introduction of building height information and site-specific weight values for population density correction. Based on the proposed improvements, selected indicators\/sub-indicators of four SDG 11 targets were updated or newly implemented. The output density map error values are provided in terms of the mean absolute error, root mean square error and mean absolute percentage indicators. The values obtained (i.e., 2.3 and 4.1 people, and 8.6%, respectively) were lower than those of the previous dasymetric method. The findings suggest that the new methodology can provide updated information about population fluxes and processes occurring over the period 2011\u20132020 in the study site\u2014Bari city in southern Italy.<\/jats:p>","DOI":"10.3390\/rs13142835","type":"journal-article","created":{"date-parts":[[2021,7,19]],"date-time":"2021-07-19T10:07:37Z","timestamp":1626689257000},"page":"2835","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Improvement of a Dasymetric Method for Implementing Sustainable Development Goal 11 Indicators at an Intra-Urban Scale"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4292-0329","authenticated-orcid":false,"given":"Mariella","family":"Aquilino","sequence":"first","affiliation":[{"name":"Institute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Via Amendola 173, 70126 Bari, Italy"},{"name":"Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3030-4884","authenticated-orcid":false,"given":"Maria","family":"Adamo","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Via Amendola 173, 70126 Bari, Italy"}]},{"given":"Palma","family":"Blonda","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Via Amendola 173, 70126 Bari, Italy"}]},{"given":"Angela","family":"Barbanente","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona 4, 70125 Bari, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3304-5355","authenticated-orcid":false,"given":"Cristina","family":"Tarantino","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Pollution Research (IIA), National Research Council (CNR), Via Amendola 173, 70126 Bari, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.envsci.2018.10.001","article-title":"Built-up Area and Population Density: Two Essential Societal Variables to Address Climate Hazard Impact","volume":"90","author":"Ehrlich","year":"2018","journal-title":"Environ. 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Principles and Applications of the Global Human Settlement Layer as Baseline for the Land Use Efficiency Indicator\u2014SDG 11.3.1. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8020096"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wang, Y., Huang, C., Feng, Y., Zhao, M., and Gu, J. (2020). Using Earth Observation for Monitoring SDG 11.3.1-Ratio of Land Consumption Rate to Population Growth Rate in Mainland China. Remote Sens., 12.","DOI":"10.3390\/rs12030357"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"111430","DOI":"10.1016\/j.rse.2019.111430","article-title":"Characterizing Urban Infrastructural Transitions for the Sustainable Development Goals Using Multi-Temporal Land, Population, and Nighttime Light Data","volume":"234","author":"Stokes","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Shelestov, A., Kussul, N., Yailymov, B., Shumilo, L., and Bilokonska, Y. (October, January 26). Assessment of Land Consumption for SDG Indicator 11.3.1 Using Global and Local Built-Up Area Maps. Proceedings of the IGARSS 2020\u20142020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA.","DOI":"10.1109\/IGARSS39084.2020.9324390"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Schiavina, M., Melchiorri, M., Corbane, C., Florczyk, A., Freire, S., Pesaresi, M., and Kemper, T. (2019). Multi-Scale Estimation of Land Use Efficiency (SDG 11.3.1) across 25 Years Using Global Open and Free Data. Sustainability, 11.","DOI":"10.3390\/su11205674"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Aquilino, M., Tarantino, C., Adamo, M., Barbanente, A., and Blonda, P. (2020). Earth Observation for the Implementation of Sustainable Development Goal 11 Indicators at Local Scale: Monitoring of the Migrant Population Distribution. Remote Sens., 12.","DOI":"10.3390\/rs12060950"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Pesaresi, M., Corbane, C., Ren, C., and Edward, N. (2021). Generalized Vertical Components of Built-up Areas from Global Digital Elevation Models by Multi-Scale Linear Regression Modelling. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0244478"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"112128","DOI":"10.1016\/j.rse.2020.112128","article-title":"National-Scale Mapping of Building Height Using Sentinel-1 and Sentinel-2 Time Series","volume":"252","author":"Frantz","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6473","DOI":"10.1109\/JSTARS.2020.3036345","article-title":"Leveraging ALOS-2 PALSAR-2 for Mapping Built-up Areas and Assessing Their Vertical Component","volume":"13","author":"Corbane","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1111\/gean.12112","article-title":"Can Dasymetric Mapping Significantly Improve Population Data Reallocation in a Dense Urban Area?: Dasymetric Mapping in an Urban Area","volume":"49","author":"Cantarino","year":"2017","journal-title":"Geogr. Anal."},{"key":"ref_15","unstructured":"Copernicus Land Monitoring Services (CLMS) (2021, March 30). Urban Atlas (UA). Available online: https:\/\/land.copernicus.eu\/local\/urban-atlas."},{"key":"ref_16","unstructured":"Alessandrini, A., Natale, F., Sermi, F., and Vespe, M. (2017). High Resolution Map of Migrants in the EU. JRC Tech. Rep. EUR, 28770."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1385","DOI":"10.5194\/essd-11-1385-2019","article-title":"The Spatial Allocation of Population: A Review of Large-Scale Gridded Population Data Products and Their Fitness for Use","volume":"11","author":"Leyk","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1080\/00045608.2013.843439","article-title":"Dasymetric Modeling and Uncertainty","volume":"104","author":"Nagle","year":"2014","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kuffer, M., Persello, C., Pfeffer, K., Sliuzas, R., and Rao, V. (2019, January 22\u201324). Do We Underestimate the Global Slum Population?. Proceedings of the 2019 Joint Urban Remote Sensing Event (JURSE), Vannes, France.","DOI":"10.1109\/JURSE.2019.8809066"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kuffer, M., Wang, J., Nagenborg, M., Pfeffer, K., Kohli, D., Sliuzas, R., and Persello, C. (2018). The Scope of Earth-Observation to Improve the Consistency of the SDG Slum Indicator. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7110428"},{"key":"ref_21","unstructured":"SVIMEZ (2021, January 20). Il Mezzogiorno Nella Nuova Geografia Europea Delle Disuguaglianze. Available online: http:\/\/lnx.svimez.info\/svimez\/wp-content\/uploads\/2019\/11\/rapporto_svimez_2019_sintesi.pdf."},{"key":"ref_22","unstructured":"ISTAT (2021, March 30). Demographic Indicators. Available online: http:\/\/dati.istat.it\/Index.aspx?QueryId=18462."},{"key":"ref_23","unstructured":"(2018, May 09). USGS Portal, Available online: https:\/\/earthexplorer.usgs.gov\/."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.isprsjprs.2010.11.001","article-title":"Support Vector Machines in Remote Sensing: A Review","volume":"66","author":"Mountrakis","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_25","unstructured":"Di Gregorio, A. (2005). Land Cover Classification System: Classification Concepts and User Manual: LCCS, Food & Agriculture Organization of the United Nations."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (2008). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, CRC Press. [2nd ed.].","DOI":"10.1201\/9781420055139"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1080\/17445647.2013.764830","article-title":"A High-Resolution Population Grid Map for Europe","volume":"9","author":"Gallego","year":"2013","journal-title":"J. Maps"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Calka, B., and Bielecka, E. (2019). Reliability Analysis of LandScan Gridded Population Data. The Case Study of Poland. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8050222"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1111\/0033-0124.10042","article-title":"Generating Surface Models of Population Using Dasymetric Mapping","volume":"55","author":"Mennis","year":"2003","journal-title":"Prof. Geogr."},{"key":"ref_30","unstructured":"Municipality of Bari (2021, May 31). Technical Building Regulations. Available online: https:\/\/www.comune.bari.it\/documents\/114869\/648857\/Adozione+Bozza+Regolamento+Edilizio\/7a0aa429-072f-4aac-be76-3d6967656742%20."},{"key":"ref_31","unstructured":"UN Habitat (2021, March 30). SDG 11.1.1. Metadata (2018 Release). Available online: https:\/\/unhabitat.org\/sites\/default\/files\/2020\/06\/metadata_on_sdg_indicator_11.1.1.pdf."},{"key":"ref_32","unstructured":"Repubblica Italiana (1975). Decreto Del Ministero Della Salute \u201cAltezza Minima e Requisiti Igienico Sanitari Principali Dei Locali Di Abitazione\u201d, Gazzetta Ufficiale, n. 190, Istituto Poligrafico e Zecca dello Stato."},{"key":"ref_33","unstructured":"UN Habitat (2021, March 30). SDG 11.2.1. Metadata 2020. Available online: https:\/\/unhabitat.org\/sites\/default\/files\/2020\/06\/metadata_on_sdg_indicator_11.2.1.pdf."},{"key":"ref_34","unstructured":"UN Habitat (2021, March 30). SDG 11.3.1. Metadata (2018 Release). Available online: https:\/\/unhabitat.org\/sites\/default\/files\/2020\/07\/metadata_on_sdg_indicator_11.3.1.pdf."},{"key":"ref_35","unstructured":"Copernicus Land Monitoring Services (CLMS) (2021, March 30). European Settlement Map (ESM). Available online: https:\/\/land.copernicus.eu\/pan-european\/GHSL\/european-settlement-map."},{"key":"ref_36","unstructured":"UN Habitat (2021, March 30). SDG 11.6.2. Metadata 2017. Available online: https:\/\/unhabitat.org\/sites\/default\/files\/2020\/07\/metadata_on_sdg_indicator_11.6.2.pdf."},{"key":"ref_37","unstructured":"De Lorenzo, N., and Dugger, A. (2020, March 01). Choroplet Map. Esri, U.S. Census Bureau. Available online: https:\/\/www.arcgis.com\/apps\/MapJournal\/index.html?appid=75eff041036d40cf8e70df99641004ca."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3354\/cr030079","article-title":"Advantages of the Mean Absolute Error (MAE) over the Root Mean Square Error (RMSE) in Assessing Average Model Performance","volume":"30","author":"Willmott","year":"2005","journal-title":"Clim. Res."},{"key":"ref_39","unstructured":"Repubblica Italiana (2006). Decreto Legislativo 3 Aprile 2006, n. 152 Norme in Materia Ambientale, Gazzetta Ufficiale, n. 88, Istituto Poligrafico e Zecca dello Stato."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1016\/j.scitotenv.2017.07.217","article-title":"Temporal Trends of Surface Urban Heat Islands and Associated Determinants in Major Chinese Cities","volume":"609","author":"Yao","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Forman, R.T.T. (2013). Urban Ecology: Science of Cities, Cambridge University Press.","DOI":"10.1017\/CBO9781139030472"},{"key":"ref_42","unstructured":"(2021, March 30). WorldPop Global 100m Population. Available online: https:\/\/www.worldpop.org\/."},{"key":"ref_43","unstructured":"Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Documentation for the Gridded Population of the World, Version 4 (GPWv4), Revision 11 Data Sets."},{"key":"ref_44","unstructured":"(2021, April 30). ARPA PUGLIA Relazione Annuale Sulla Qualit\u00e0 Dell\u2019Aria in Puglia Anno 2019. Available online: https:\/\/www.snpambiente.it\/2020\/07\/03\/relazione-annuale-sulla-qualita-dellaria-in-puglia-anno-2019\/."},{"key":"ref_45","unstructured":"Marcil, S., and Sharon, J. (2021). Biden Presidency Is Likely to Deviate from Trump Administration on Foreign Policy, Climate Change, Race Relations, Indian Express."},{"key":"ref_46","unstructured":"(2021, May 31). European Parliament Resolution of 19 May 2021 on Human Rights Protection and the EU External Migration Policy (2020\/2116(INI)). Available online: https:\/\/www.europarl.europa.eu\/doceo\/document\/TA-9-2021-0242_EN.html."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"398","DOI":"10.2105\/AJPH.2020.306128","article-title":"A Window of Opportunity Is Opening to Improve Immigrant Health: A Research and Practice Agenda","volume":"111","author":"Wallace","year":"2021","journal-title":"Am. J. Public Health"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Santoro, M., Mazzetti, P., and Nativi, S. (2020). The VLab Framework: An Orchestrator Component to Support Data to Knowledge Transition. Remote Sens., 12.","DOI":"10.3390\/rs12111795"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2835\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:31:51Z","timestamp":1760164311000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2835"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,19]]},"references-count":48,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["rs13142835"],"URL":"https:\/\/doi.org\/10.3390\/rs13142835","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,19]]}}}