{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T12:12:28Z","timestamp":1762863148044,"version":"build-2065373602"},"reference-count":76,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,26]],"date-time":"2021-08-26T00:00:00Z","timestamp":1629936000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["NNX13AB72G"],"award-info":[{"award-number":["NNX13AB72G"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>While remotely sensed images of various resolutions have been widely used in identifying changes in urban and peri-urban environments, only very high resolution (VHR) imagery is capable of providing the information needed for understanding the changes taking place in remote rural environments, due to the small footprints and low density of man-made structures in these settings. However, limited by data availability, mapping man-made structures and conducting subsequent change detections in remote areas are typically challenging and thus require a certain level of flexibility in algorithm design that takes into account the specific environmental and image conditions. In this study, we mapped all buildings and corrals for two remote villages in Mozambique based on two single-date VHR images that were taken in 2004 and 2012, respectively. Our algorithm takes advantage of the presence of shadows and, through a fusion of both spectra- and object-based analysis techniques, is able to differentiate buildings with metal and thatch roofs with high accuracy (overall accuracy of 86% and 94% for 2004 and 2012, respectively). The comparison of the mapping results between 2004 and 2012 reveals multiple lines of evidence suggesting that both villages, while differing in many aspects, have experienced substantial increases in the economic status. As a case study, our project demonstrates the capability of a coupling of VHR imagery with locally adjusted classification algorithms to infer the economic development of small, remote rural settlements.<\/jats:p>","DOI":"10.3390\/rs13173385","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T21:59:45Z","timestamp":1630447185000},"page":"3385","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Characterizing Small-Town Development Using Very High Resolution Imagery within Remote Rural Settings of Mozambique"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5295-9657","authenticated-orcid":false,"given":"Dong","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Tatiana V.","family":"Loboda","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Julie A.","family":"Silva","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Maria R.","family":"Tonellato","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.14358\/PERS.69.12.1377","article-title":"Mapping urban areas by fusing multiple sources of coarse resolution remotely sensed data","volume":"69","author":"Schneider","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/S0034-4257(02)00078-0","article-title":"Global land cover mapping from MODIS: Algorithms and early results","volume":"83","author":"Friedl","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1733","DOI":"10.1016\/j.rse.2010.03.003","article-title":"Mapping global urban areas using MODIS 500-m data: New methods and datasets based on \u2018urban ecoregions\u2019","volume":"114","author":"Schneider","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_5","first-page":"629","article-title":"Detecting residential land-use development at the urban fringe","volume":"48","author":"Jensen","year":"1982","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1501","DOI":"10.1080\/014311698215315","article-title":"Principal component analysis of stacked multi-temporal images for the monitoring of rapid urban expansion in the Pearl River Delta","volume":"19","author":"Li","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1080\/01431160117207","article-title":"Monitoring urban expansion with remote sensing in China","volume":"22","author":"Ji","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1676","DOI":"10.1016\/j.rse.2010.02.018","article-title":"Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods","volume":"114","author":"Xian","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.rse.2012.06.006","article-title":"Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach","volume":"124","author":"Schneider","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_10","unstructured":"Rose, A.N., and Bright, E.A. (2014, January 1\u20133). The LandScan Global Population Distribution Project: Current State of the Art and Prospective Innovation. Proceedings of the Population Association of America Annual Meeting, Boston, MA, USA."},{"key":"ref_11","unstructured":"Brown de Colstoun, E.C., Huang, C., Wang, P., Tilton, J.C., Tan, B., Phillips, J., Niemczura, S., Ling, P.-Y., and Wolfe, R.E. (2017). Global Man-Made Impervious Surface (GMIS) Dataset from Landsat, NASA Socioeconomic Data and Applications Center (SEDAC)."},{"key":"ref_12","unstructured":"Wang, P., Huang, C., Brown de Colstoun, E.C., Tilton, J.C., and Tan, B. (2017). Global Human Built-Up and Settlement Extent (HBASE) Dataset from Landsat, NASA Socioeconomic Data and Applications Center (SEDAC)."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Chen, D., Shevade, V., Baer, A., He, J., Hoffman-Hall, A., Ying, Q., Li, Y., and Loboda, T.V. (2021). A disease control-oriented land cover land use map for Myanmar. Data, 6.","DOI":"10.3390\/data6060063"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4054","DOI":"10.1080\/01431161.2015.1073862","article-title":"A dynamic model for population mapping: A methodology integrating a Monte Carlo simulation with vegetation-adjusted night-time light images","volume":"36","author":"Song","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/S0924-2716(01)00040-5","article-title":"Night-time lights of the world: 1994\u20131995","volume":"56","author":"Elvidge","year":"2001","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1080\/01431160500181861","article-title":"DMSP\/OLS night-time light imagery for urban population estimates in the Brazilian Amazon","volume":"27","author":"Amaral","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1080\/01431161.2011.616550","article-title":"Estimation of urban population in Indo-Gangetic Plains using night-time OLS data","volume":"33","author":"Maithani","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2583","DOI":"10.1038\/s41467-020-16185-w","article-title":"Using publicly available satellite imagery and deep learning to understand economic well-being in Africa","volume":"11","author":"Yeh","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wang, R., Wan, B., Guo, Q., Hu, M., and Zhou, S. (2017). Mapping Regional Urban Extent Using NPP-VIIRS DNB and MODIS NDVI Data. Remote Sens., 9.","DOI":"10.3390\/rs9080862"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1080\/2150704X.2014.905728","article-title":"Evaluation of NPP-VIIRS night-time light composite data for extracting built-up urban areas","volume":"5","author":"Shi","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"12459","DOI":"10.3390\/rs70912459","article-title":"Mapping Impervious Surface Distribution with Integration of SNNP VIIRS-DNB and MODIS NDVI Data","volume":"7","author":"Guo","year":"2015","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1080\/17538947.2016.1168879","article-title":"Global mapping of urban built-up areas of year 2014 by combining MODIS multispectral data with VIIRS nighttime light data","volume":"9","author":"Sharma","year":"2016","journal-title":"Int. J. Digit. Earth"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1257\/aer.102.2.994","article-title":"Measuring economic growth from outer space","volume":"102","author":"Henderson","year":"2012","journal-title":"Am. Econ. Rev."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zhang, G., Guo, X., Li, D., and Jiang, B. (2019). Evaluating the potential of LJ1-01 nighttime light data for modeling socio-economic parameters. Sensors, 19.","DOI":"10.3390\/s19061465"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Proville, J., Zavala-Araiza, D., and Wagner, G. (2017). Night-time lights: A global, long term look at links to socio-economic trends. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0174610"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Zhao, M., Zhou, Y., Li, X., Cao, W., He, C., Yu, B., Li, X., Elvidge, C.D., Cheng, W., and Zhou, C. (2019). Applications of satellite remote sensing of nighttime light observations: Advances, challenges, and perspectives. Remote Sens., 11.","DOI":"10.3390\/rs11171971"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1016\/j.isprsjprs.2010.10.010","article-title":"Detection of impervious surface change with multitemporal Landsat images in an urban\u2013rural frontier","volume":"66","author":"Lu","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.1080\/01431161.2015.1007250","article-title":"Application of a normalized difference impervious index (NDII) to extract urban impervious surface features based on Landsat TM images","volume":"36","author":"Wang","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1109\/LGRS.2009.2023825","article-title":"Evaluation of the surface temperature variation with surface settings on the urban heat island in Seoul, Korea, using Landsat-7 ETM+ and SPOT","volume":"6","author":"Bhang","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1080\/2150704X.2014.890758","article-title":"Responses of Suomi-NPP VIIRS-derived nighttime lights to socioeconomic activity in China\u2019s cities","volume":"5","author":"Ma","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.rse.2005.02.002","article-title":"Spatial analysis of global urban extent from DMSP-OLS night lights","volume":"96","author":"Small","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"7840","DOI":"10.3390\/rs6087840","article-title":"Comparative estimation of urban development in China\u2019s cities using socioeconomic and DMSP\/OLS night light data","volume":"6","author":"Fan","year":"2014","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"111386","DOI":"10.1016\/j.rse.2019.111386","article-title":"Mapping remote rural settlements at 30 m spatial resolution using geospatial data-fusion","volume":"233","author":"Loboda","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_34","unstructured":"United Nations (2016). New Urban Agenda, United Nations Conference on Housing and Sustainable Urban Development (Habitat III)."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1038\/s41586-019-1050-5","article-title":"Mapping changes in housing in sub-Saharan Africa from 2000 to 2015","volume":"568","author":"Tusting","year":"2019","journal-title":"Nature"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"7770","DOI":"10.1038\/s41598-019-43816-0","article-title":"Reduced mosquito survival in metal-roof houses may contribute to a decline in malaria transmission in sub-Saharan Africa","volume":"9","author":"Lindsay","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1007\/BF02217292","article-title":"Livestock in africa: The economics of ownership and production, and the potential for improvement","volume":"12","author":"Meltzer","year":"1995","journal-title":"Agric. Hum. Values"},{"key":"ref_38","first-page":"611","article-title":"Remote sensing of urban\/suburban infrastructure and socio-economic attributes","volume":"65","author":"Jensen","year":"1999","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Gamba, P., Dell\u2019Acqua, F., Stasolla, M., Trianni, G., and Lisini, G. (2011). Limits and challenges of optical very-high-spatial-resolution satellite remote sensing for urban applications. Urban Remote Sensing, John Wiley & Sons, Ltd.","DOI":"10.1002\/9780470979563.ch3"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/j.rse.2010.12.017","article-title":"Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery","volume":"115","author":"Myint","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1244","DOI":"10.1109\/36.763282","article-title":"Updating land-cover maps by using texture information from very high-resolution space-borne imagery","volume":"37","author":"Smits","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sensing"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.isprsjprs.2017.08.011","article-title":"Contextually guided very-high-resolution imagery classification with semantic segments","volume":"132","author":"Zhao","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Mahabir, R., Croitoru, A., Crooks, A.T., Agouris, P., and Stefanidis, A. (2018). A critical review of high and very high-resolution remote sensing approaches for detecting and mapping slums: Trends, challenges and emerging opportunities. Urban Sci., 2.","DOI":"10.3390\/urbansci2010008"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1109\/TGE.1976.294460","article-title":"Classification of multispectral image data by extraction and classification of homogeneous objects","volume":"14","author":"Kettig","year":"1976","journal-title":"IEEE Trans. Geosci. Electron."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G.J. (2008). Object-based image analysis for remote sensing applications: Modeling reality\u2014dealing with complexity. Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.isprsjprs.2017.06.001","article-title":"A review of supervised object-based land-cover image classification","volume":"130","author":"Ma","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.landurbplan.2004.12.005","article-title":"Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing","volume":"75","author":"Xiao","year":"2006","journal-title":"Landsc. Urban Plan."},{"key":"ref_48","unstructured":"Chunyang, H., Jing, L., JinShui, Z., Yaozhong, P., and YunHao, C. (2005, January 29). Dynamic monitor on urban expansion based on a object-oriented approach. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS \u201805, Seoul, Korea."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"2831","DOI":"10.1080\/01431160500117865","article-title":"Analysis of land use\/cover changes and urban expansion of Nairobi city using remote sensing and GIS","volume":"26","author":"Mundia","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.gloenvcha.2018.04.013","article-title":"Examining aspiration\u2019s imprint on the landscape: Lessons from Mozambique\u2019s Limpopo National Park","volume":"51","author":"Silva","year":"2018","journal-title":"Glob. Environ. Chang."},{"key":"ref_51","unstructured":"Peace Parks Foundation (2021, July 21). Great Limpopo. Available online: https:\/\/www.peaceparks.org\/tfcas\/great-limpopo\/."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.3390\/rs4092661","article-title":"Tree species classification with random forest using very high spatial resolution 8-band Worldview-2 satellite data","volume":"4","author":"Immitzer","year":"2012","journal-title":"Remote Sens."},{"key":"ref_54","first-page":"18","article-title":"Classification and regression by randomForest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_55","unstructured":"R Core Team (2012). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_56","unstructured":"ESRI (2017). ArcGIS Desktop: Release 10.6, Environmental Systems Research Institute."},{"key":"ref_57","first-page":"115","article-title":"Estimating wealth effects without expenditure data\u2014or tears: An application to educational enrollments in states of India","volume":"38","author":"Filmer","year":"2001","journal-title":"Demography"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1111\/j.0034-6586.2003.00100.x","article-title":"Exploring alternative measures of welfare in the absence of expenditure data","volume":"49","author":"Sahn","year":"2003","journal-title":"Rev. Income Wealth"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1080\/15481603.2018.1549819","article-title":"Linking remotely sensed Urban Green Space (UGS) distribution patterns and Socio-Economic Status (SES)\u2014A multi-scale probabilistic analysis based in Mumbai, India","volume":"56","author":"Sathyakumar","year":"2019","journal-title":"GISci. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/JSTARS.2008.2007513","article-title":"Integrative Assessment of Informal Settlements Using VHR Remote Sensing Data\u2014The Delhi Case Study","volume":"1","author":"Niebergall","year":"2008","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Warth, G., Braun, A., Assmann, O., Fleckenstein, K., and Hochschild, V. (2020). Prediction of socio-economic indicators for urban planning using VHR satellite imagery and spatial analysis. Remote Sens., 12.","DOI":"10.3390\/rs12111730"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.isprsjprs.2013.09.004","article-title":"Automated detection of buildings from single VHR multispectral images using shadow information and graph cuts","volume":"86","author":"Ok","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"22034","DOI":"10.1109\/ACCESS.2018.2819705","article-title":"Building extraction from RGB VHR images using Shifted Shadow algorithm","volume":"6","author":"Gao","year":"2018","journal-title":"IEEE Access"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Ngo, T., Collet, C., and Mazet, V. (2015, January 27\u201330). Automatic rectangular building detection from VHR aerial imagery using shadow and image segmentation. Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada.","DOI":"10.1109\/ICIP.2015.7351047"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/LGRS.2017.2762424","article-title":"A shadow-overlapping algorithm for estimating building heights from VHR satellite images","volume":"15","author":"Kadhim","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.isprsjprs.2015.05.004","article-title":"Understanding angular effects in VHR imagery and their significance for urban land-cover model portability: A study of two multi-angle in-track image sequences","volume":"107","author":"Matasci","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.isprsjprs.2019.02.009","article-title":"Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective","volume":"150","author":"Hossain","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2784","DOI":"10.1080\/01431161.2018.1433343","article-title":"Implementation of machine-learning classification in remote sensing: An applied review","volume":"39","author":"Maxwell","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Crommelinck, S., Bennett, R., Gerke, M., Nex, F., Yang, M., 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_71","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.culher.2019.12.013","article-title":"Pattern identification and analysis for the traditional village using low altitude UAV-borne remote sensing: Multifeatured geospatial data to support rural landscape investigation, documentation and management","volume":"44","author":"Liu","year":"2020","journal-title":"J. Cult. Herit."},{"key":"ref_72","unstructured":"Forte, M., and Campana, S. (2016). Applying UAS Photogrammetry to Analyze Spatial Patterns of Indigenous Settlement Sites in the Northern Dominican Republic. Digital Methods and Remote Sensing in Archaeology: Archaeology in the Age of Sensing, Springer International Publishing."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"St\u00f6cker, C., Ho, S., Nkerabigwi, P., Schmidt, C., Koeva, M., Bennett, R., and Zevenbergen, J. (2019). Unmanned Aerial System imagery, land data and user needs: A socio-technical assessment in Rwanda. Remote Sens., 11.","DOI":"10.3390\/rs11091035"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.compag.2017.07.008","article-title":"Crop height monitoring with digital imagery from Unmanned Aerial System (UAS)","volume":"141","author":"Chang","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"165","DOI":"10.5194\/isprs-archives-XLIV-4-W3-2020-165-2020","article-title":"Post-earthquake 3d building model (LOD2) generation from UAS imagery: The case of Vrisa Traditional Settlement, Lesvos, Greece","volume":"44","author":"Chaidas","year":"2020","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Partovi, T., Fraundorfer, F., Bahmanyar, R., Huang, H., and Reinartz, P. (2019). Automatic 3-D building model reconstruction from Very High Resolution stereo satellite imagery. Remote Sens., 11.","DOI":"10.3390\/rs11141660"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/17\/3385\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:52:29Z","timestamp":1760165549000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/17\/3385"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,26]]},"references-count":76,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["rs13173385"],"URL":"https:\/\/doi.org\/10.3390\/rs13173385","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,8,26]]}}}