{"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":1775326968147,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,19]],"date-time":"2019-07-19T00:00:00Z","timestamp":1563494400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia \/ CICS.NOVA","award":["UID\/SOC\/04647\/2013"],"award-info":[{"award-number":["UID\/SOC\/04647\/2013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multi-temporal analysis of census small-area microdata is hampered by the fact that census tract shapes do not often coincide between census exercises. Dasymetric mapping techniques provide a workaround that is nonetheless highly dependent on the quality of ancillary data. The objectives of this work are to: (1) Compare the use of three spatial techniques for the estimation of population according to census tracts: Areal interpolation and dasymetric mapping using control data\u2014building block area (2D) and volume (3D); (2) demonstrate the potential of unmanned aerial vehicle (UAV) technology for the acquisition of control data; (3) perform a sensitivity analysis using Monte Carlo simulations showing the effect of changes in building block volume (3D information) in population estimates. The control data were extracted by a (semi)-automatic solution\u20143DEBP (3D extraction building parameters) developed using free open source software (FOSS) tools. The results highlight the relevance of 3D for the dasymetric mapping exercise, especially if the variations in height between building blocks are significant. Using low-cost UAV backed systems with a FOSS-only computing framework also proved to be a competent solution with a large scope of potential applications.<\/jats:p>","DOI":"10.3390\/rs11141716","type":"journal-article","created":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T02:55:37Z","timestamp":1563764137000},"page":"1716","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Dasymetric Mapping Using UAV High Resolution 3D Data within Urban Areas"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5448-4790","authenticated-orcid":false,"given":"Carla","family":"Rebelo","sequence":"first","affiliation":[{"name":"Interdisciplinary Centre of Social Sciences (CICS.NOVA), Faculty of Social Sciences and Humanities, (NOVA FCSH), Universidade NOVA de Lisboa, Av. de Berna, 26-C, 1069-061 Lisboa, Portugal"}]},{"given":"Ant\u00f3nio Manuel","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre of Social Sciences (CICS.NOVA), Faculty of Social Sciences and Humanities, (NOVA FCSH), Universidade NOVA de Lisboa, Av. de Berna, 26-C, 1069-061 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3047-0807","authenticated-orcid":false,"given":"Jos\u00e9 Ant\u00f3nio","family":"Tened\u00f3rio","sequence":"additional","affiliation":[{"name":"Interdisciplinary Centre of Social Sciences (CICS.NOVA), Faculty of Social Sciences and Humanities, (NOVA FCSH), Universidade NOVA de Lisboa, Av. de Berna, 26-C, 1069-061 Lisboa, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1080\/1357480032000155141","article-title":"Measuring Urbanism: Issues in Smart Growth Research","volume":"8","author":"Talen","year":"2003","journal-title":"J. Urban Des."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1559\/152304001782173727","article-title":"Dasymetric Mapping and Areal Interpolation: Implementation and Evaluation","volume":"28","author":"Eicher","year":"2001","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1559\/1523040041649407","article-title":"Dasymetric Estimation of Population Density and Areal Interpolation of Census Data","volume":"31","author":"Holt","year":"2004","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Liu, L., Peng, Z., Wu, H., Jiao, H., and Yu, Y. (2018). Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method. Sustainability, 10.","DOI":"10.3390\/su10072432"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1068\/a250383","article-title":"A framework for the areal interpolation of socioeconomic data","volume":"25","author":"Goodchild","year":"1993","journal-title":"Environ. Plan. A Econ. Space"},{"key":"ref_6","first-page":"565","article-title":"Land-Use Dynamics at the Micro Level: Constructing and Analyzing Historical Datasets for the Portuguese Census Tracts","volume":"Volume 7334","author":"Murgante","year":"2012","journal-title":"Computational Science and Its Applications"},{"key":"ref_7","first-page":"4027","article-title":"Ecological Inference and the Ecological Fallacy","volume":"Volume 6","author":"Smelser","year":"2001","journal-title":"International Encyclopedia of the Social & Behavioral Sciences"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1068\/a231025","article-title":"The Modifiable Areal Unit Problem in Multivariate Statistical Analysis","volume":"23","author":"Fotheringham","year":"1991","journal-title":"Environ. Plan. A Econ. Space"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Hecht, R., Herold, H., Behnisch, M., and Jehling, M. (2018). Mapping Long-Term Dynamics of Population and Dwellings Based on a Multi-Temporal Analysis of Urban Morphologies. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8010002"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Weiss, M., and Baret, F. (2017). Using 3D Point Clouds Derived from UAV RGB Imagery to Describe Vineyard 3D Macro-Structure. Remote Sens., 9.","DOI":"10.3390\/rs9020111"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Crommelinck, S., Bennett, R., Gerke, M., Nex, F., Yang, M.Y., and Vosselman, G. (2016). Review of Automatic Feature Extraction from High-Resolution Optical Sensor Data for UAV-Based Cadastral Mapping. Remote Sens., 8.","DOI":"10.3390\/rs8080689"},{"key":"ref_12","unstructured":"Toro, F.G., and Tsourdos, A. (2018). UAV or Drones for Remote Sensing Applications. Sensors, 2."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Pinto, N., Tened\u00f3rio, J., Antunes, A., and Cladera, J. (2013). New Developments in Geographical Information Technology for Urban and Spatial Planning. Technologies for Urban and Spatial Planning: Virtual Cities and Territories, IGI Global.","DOI":"10.4018\/978-1-4666-4349-9"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Gervasi, B., Murgante, O., Misra, B., Gavrilova, S., Rocha, M., Torre, A., Taniar, C., and Apduhan, D. (2015). Building 3D City Models: Testing and Comparing Laser Scanning and Low-Cost UAV Data Using FOSS Technologies. Computational Science and Its Applications\u2014ICCSA 2015, Springer.","DOI":"10.1007\/978-3-319-21407-8"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lemmens, M. (2011). Geo-Information, Technologies, Applications and the Environment, Springer.","DOI":"10.1007\/978-94-007-1667-4"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"125","DOI":"10.5194\/isprsarchives-XXXVIII-1-C22-125-2011","article-title":"The accuracy of Automatic Photogrammetric Techniques on Ultra-Light UAV Imagery","volume":"XXXVIII-1\/C22","author":"Kung","year":"2011","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Benassi, F., Dall\u2019Asta, E., Diotri, F., Forlani, G., Cella, U.M., Roncella, R., and Santise, M. (2017). Testing Accuracy and Repeatability of UAV Blocks Oriented with GNSS-Supported Aerial Triangulation. Remote Sens., 9.","DOI":"10.3390\/rs9020172"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"57","DOI":"10.3390\/rs5010057","article-title":"A Sequential Aerial Triangulation Algorithm for Real- time Georeferencing of Image Sequences Acquired by an Airborne","volume":"5","author":"Choi","year":"2013","journal-title":"Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"387","DOI":"10.5194\/isprsarchives-XXXIX-B1-387-2012","article-title":"Dense Multiple Stereo Matching of Highly Overlapping UAV Imagery","volume":"XXXIX-B1","author":"Haala","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"73","DOI":"10.5194\/isprs-annals-IV-4-W6-73-2018","article-title":"A Photogrammetry-Based Structure from Motion Algorithm Using robust iterative bundle adjustment techniques","volume":"IV-4\/W6","author":"Verykokou","year":"2018","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wang, S., Tian, Y., Zhou, Y., Liu, W., and Lin, C. (2016). Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings. Sensors, 16.","DOI":"10.3390\/s16101755"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1559\/152304010792194949","article-title":"Spatial Autoregressive Models for Population Estimation at the Block Level Using LIDAR Derived Volume Information","volume":"37","author":"Qiu","year":"2010","journal-title":"Cartogr. Geogr. Inf. Sci."},{"key":"ref_23","unstructured":"Rebelo, C. (2016). 3D Point Clouds in Urban Planning: Developing and Releasing high-end Methodologies based on LiDAR and UAV data for the Extraction of Building Parameters. [Ph.D. Thesis, Faculdade de Ci\u00eancias Sociais da Universidade]."},{"key":"ref_24","unstructured":"(2019, January 12). FOSS. Available online: http:\/\/freeopensourcesoftware.org\/."},{"key":"ref_25","unstructured":"(2019, March 07). Censos. Available online: http:\/\/mapas.ine.pt\/download\/index2011.phtml."},{"key":"ref_26","unstructured":"(2019, June 25). G8 Open Data Charter National Action Plan, Available online: https:\/\/www.gov.uk\/government\/publications\/g8-open-data-charter-national-action-plan."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.geomorph.2016.11.021","article-title":"Optimising UAV topographic surveys processed with structure-from-motion: Ground control quality, quantity and bundle adjustment","volume":"280","author":"James","year":"2017","journal-title":"Geomorphology"},{"key":"ref_28","unstructured":"Gelsema, E.S., and Kanal, L.N. (1986). Clustering large data sets (with discussion). Pattern Recognition in Practice II, Elsevier."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/0377-0427(87)90125-7","article-title":"Silhouettes: A Graphical aid to the interpretation and validation of cluster analysis","volume":"20","author":"Rousseeuw","year":"1987","journal-title":"J. Comput. Appl. Math."},{"key":"ref_30","unstructured":"(2019, June 27). Package Cluster. Available online: https:\/\/cran.r-project.org\/web\/packages\/cluster\/cluster.pdf."},{"key":"ref_31","unstructured":"(2019, July 07). GRASS Development Team: Geographic Resources Analysis Support System (GRASS 7) Programmer\u2019s Manual. Open Source Geospatial Foundation. Available online: http:\/\/grass.osgeo.org\/programming7\/."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1068\/a270211","article-title":"Modelling the Errors in Areal Interpolation between Zonal Systems by Monte Carlo Simulation","volume":"27","author":"Fisher","year":"1995","journal-title":"Environ. Plan. A Econ. Space"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1716\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:07:43Z","timestamp":1760188063000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1716"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,19]]},"references-count":32,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["rs11141716"],"URL":"https:\/\/doi.org\/10.3390\/rs11141716","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,19]]}}}