{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T11:15:51Z","timestamp":1772795751878,"version":"3.50.1"},"reference-count":91,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,12,11]],"date-time":"2018-12-11T00:00:00Z","timestamp":1544486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Vertical urban growth in the form of urban volume or building height is increasingly being seen as a significant indicator and constituent of the urban environment. Although high-resolution digital surface models can provide valuable information, various places lack access to such resources. The objective of this study is to explore the feasibility of using open digital surface models (DSMs), such as the AW3D30, ASTER, and SRTM datasets, for extracting digital building height models (DBHs) and comparing their accuracy. A multidirectional processing and slope-dependent filtering approach for DBH extraction was used. Yangon was chosen as the study location since it represents a rapidly developing Asian city where urban changes can be observed during the acquisition period of the aforementioned open DSM datasets (2001\u20132011). The effect of resolution degradation on the accuracy of the coarse AW3D30 DBH with respect to the high-resolution AW3D5 DBH was also examined. It is concluded that AW3D30 is the most suitable open DSM for DBH generation and for observing buildings taller than 9 m. Furthermore, the AW3D30 DBH, ASTER DBH, and SRTM DBH are suitable for observing vertical changes in urban structures.<\/jats:p>","DOI":"10.3390\/rs10122008","type":"journal-article","created":{"date-parts":[[2018,12,12]],"date-time":"2018-12-12T03:27:49Z","timestamp":1544585269000},"page":"2008","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Comparison of Digital Building Height Models Extracted from AW3D, TanDEM-X, ASTER, and SRTM Digital Surface Models over Yangon City"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0180-4900","authenticated-orcid":false,"given":"Prakhar","family":"Misra","sequence":"first","affiliation":[{"name":"Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3653-5771","authenticated-orcid":false,"given":"Ram","family":"Avtar","sequence":"additional","affiliation":[{"name":"Graduate School of Environmental Earth Science, Hokkaido University, Sapporo 060-0808, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9138-6601","authenticated-orcid":false,"given":"Wataru","family":"Takeuchi","sequence":"additional","affiliation":[{"name":"Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,11]]},"reference":[{"key":"ref_1","unstructured":"UN Habitat (2018, November 19). Resilience. Available online: https:\/\/unhabitat.org\/urban-themes\/resilience\/."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1016\/j.scs.2017.10.017","article-title":"Estimation of built-up and green volume using geospatial techniques: A case study of Surabaya, Indonesia","volume":"37","author":"Handayani","year":"2018","journal-title":"Sustain. Cities Soc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1007\/s11442-007-0469-z","article-title":"Measuring urban sprawl in Beijing with geo-spatial indices","volume":"17","author":"Jiang","year":"2007","journal-title":"J. Geogr. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s11769-009-0291-x","article-title":"Urban three-dimensional expansion and its driving forces\u2014A case study of Shanghai, China","volume":"19","author":"Shi","year":"2009","journal-title":"Chin. Geogr. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1080\/136588198241617","article-title":"Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington\/Baltimore","volume":"12","author":"Clarke","year":"1998","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/S0924-2716(99)00010-6","article-title":"Extraction of buildings and trees in urban environments","volume":"54","author":"Haala","year":"1999","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1023\/A:1021380611553","article-title":"Analysis of 3-D urban databases with respect to pollution dispersion for a number of European and American cities","volume":"2","author":"Ratti","year":"2002","journal-title":"Water Air Soil Pollut. Focus"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"762","DOI":"10.1016\/j.enbuild.2004.10.010","article-title":"Energy consumption and urban texture","volume":"37","author":"Ratti","year":"2005","journal-title":"Energy Build."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2206","DOI":"10.1016\/j.renene.2009.02.021","article-title":"Assessment of photovoltaic potential in urban areas using open-source solar radiation tools","volume":"34","author":"Hofierka","year":"2009","journal-title":"Renew. Energy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/s10980-009-9402-4","article-title":"Urban heat islands and landscape heterogeneity: Linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns","volume":"25","author":"Buyantuyev","year":"2010","journal-title":"Landsc. Ecol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1016\/j.enggeo.2009.12.006","article-title":"Urban flood hazard zoning in Tucum\u00e1n Province, Argentina, using GIS and multicriteria decision analysis","volume":"111","author":"Lutz","year":"2010","journal-title":"Eng. Geol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1109\/TITS.2011.2122258","article-title":"Simulation of the effects of different urban environments on gps performance using digital elevation models and building databases","volume":"12","author":"Costa","year":"2011","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3704","DOI":"10.1080\/01431161.2017.1302113","article-title":"Detecting horizontal and vertical urban growth from medium resolution imagery and its relationships with major socioeconomic factors","volume":"38","author":"Zhang","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","first-page":"463","article-title":"Automatic Generation of Digital Building Models for Complex Structures From Lidar Data","volume":"37","author":"Kim","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/JSTARS.2011.2178399","article-title":"Performance evaluation for 3-{D} city model generation of six different DSMs from air-and spaceborne sensors","volume":"5","author":"Sirmacek","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1109\/36.823956","article-title":"Detection and extraction of buildings from interferometric SAR data","volume":"38","author":"Gamba","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","first-page":"475","article-title":"Change Detection of Building Footprints from Airborne Laser Scanning Acquired in Short Time Intervals","volume":"Volume XXXVIII","author":"Wagner","year":"2010","journal-title":"ISPRS Technical Commission VII Symposium\u2014100 Years ISPRS"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Wu, B., Yu, B., Wu, Q., Yao, S., Zhao, F., Mao, W., and Wu, J. (2017). A graph-based approach for 3d building model reconstruction from airborne lidar point clouds. Remote Sens., 9.","DOI":"10.3390\/rs9010092"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zhang, X., Zhao, X., and Xin, Q. (2018). Extracting building boundaries from high resolution optical images and LiDAR data by integrating the convolutional neural network and the active contour model. Remote Sens., 10.","DOI":"10.3390\/rs10091459"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.compenvurbsys.2018.09.004","article-title":"Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data","volume":"73","author":"Bonczak","year":"2018","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.autcon.2018.05.009","article-title":"Automatic building information model reconstruction in high-density urban areas: Augmenting multi-source data with architectural knowledge","volume":"93","author":"Chen","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"04015049","DOI":"10.1061\/(ASCE)CP.1943-5487.0000524","article-title":"Big-Data Approach for Three-Dimensional Building Extraction from Aerial Laser Scanning","volume":"30","author":"Aljumaily","year":"2016","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3826","DOI":"10.3390\/rs70403826","article-title":"Building extraction from Airborne Laser Scanning data: An analysis of the state of the art","volume":"7","author":"Tomljenovic","year":"2015","journal-title":"Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.14358\/PERS.76.9.1041","article-title":"Comparison of Matching Algorithms for DSM Generation in Urban Areas from Ikonos Imagery","volume":"76","author":"Alobeid","year":"2010","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1109\/TGRS.2013.2240692","article-title":"Building Change Detection Based on Satellite Stereo Imagery and Digital Surface Models","volume":"52","author":"Tian","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/S0065-308X(05)62004-0","article-title":"Determining Global Population Distribution: Methods, Applications and Data","volume":"62","author":"Balk","year":"2006","journal-title":"Adv. Parasitol."},{"key":"ref_27","unstructured":"Center for International Earth Science Information Network\u2014CIESIN\u2014Columbia University, International Food Policy Research Institute (IFPRI), The World Bank, and Centro Internacional de Agricultura Tropical (2011). Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Urban Extents Grid, NASA Socioeconomic Data and Applications Center (SEDAC)."},{"key":"ref_28","unstructured":"Center for International Earth Science Information Network\u2014CIESIN\u2014Columbia University (2016). Global Urban Heat Island (UHI) Data Set, 2013, NASA Socioeconomic Data and Applications Center (SEDAC)."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1038\/s41586-018-0676-z","article-title":"Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston","volume":"563","author":"Zhang","year":"2018","journal-title":"Nature"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Murayama, Y., and Thapa, R. (2011). Estimation of Building Population from LIDAR Derived Digital Volume Model. Spatial Analysis and Modeling in Geographical Transformation Process, Springer.","DOI":"10.1007\/978-94-007-0671-2"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"5844","DOI":"10.1002\/2017GL072874","article-title":"A high-accuracy map of global terrain elevations","volume":"44","author":"Yamazaki","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"149","DOI":"10.5194\/isprs-archives-XLI-B4-149-2016","article-title":"Vertical accuracy assessment of 30-M resolution ALOS, ASTER, and SRTM global DEMS over Northeastern Mindanao, Philippines","volume":"41","author":"Santillan","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1237","DOI":"10.1080\/10106049.2017.1343392","article-title":"Vertical accuracy evaluation of SRTM-GL1, GDEM-V2, AW3D30 and CartoDEM-V3.1 of 30-m resolution with dual frequency GNSS for lower Tapi Basin India","volume":"33","author":"Jain","year":"2018","journal-title":"Geocarto Int."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"211","DOI":"10.5194\/esurf-5-211-2017","article-title":"Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau","volume":"5","author":"Purinton","year":"2017","journal-title":"Earth Surf. Dyn."},{"key":"ref_35","first-page":"17","article-title":"Comparative Analysis of Digital Elevation Models between AW3D30, SRTM30 and Airborne LiDAR: A case of Chuncheon, South Korea","volume":"36","author":"Acharya","year":"2018","journal-title":"J. Korean Soc. Surv. Geod. Photogramm. Cartogr."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Alganci, U., Besol, B., and Sertel, E. (2018). Accuracy Assessment of Different Digital Surface Models. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7030114"},{"key":"ref_37","unstructured":"Nghiem, S., Balk, D., Small, C., Deichmann, U., Wannebo, A., Blom, R., Sutton, P., Yetman, G., Chen, R., and Rodriguez, E. (2001). Global Infrastructure: The Potential of SRTM Data to Break New Ground, NASA-JPL and CIESIN: Columbia University. White Paper."},{"key":"ref_38","first-page":"55","article-title":"SRTM data Characterization in urban areas","volume":"34","author":"Gamba","year":"2002","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1976","DOI":"10.1109\/TGRS.2003.814630","article-title":"Information fusion for scene understanding from interferometric SAR data in urban environments","volume":"41","author":"Quartulli","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1177\/0042098007087340","article-title":"Compact, dispersed, fragmented, extensive? A comparison of urban growth in twenty-five global cities using remotely sensed data, pattern metrics and census information","volume":"45","author":"Schneider","year":"2008","journal-title":"Urban Stud."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Seto, K.C., Fragkias, M., G\u00fcneralp, B., and Reilly, M.K. (2011). A Meta-Analysis of Global Urban Land Expansion. PLoS ONE, 6.","DOI":"10.1371\/journal.pone.0023777"},{"key":"ref_42","first-page":"40","article-title":"Night on earth: Mapping decadal changes of anthropogenic night light in Asia","volume":"22","author":"Small","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_43","unstructured":"Wang, P., Huang, C., and Tilton, J.C. (arXiv, 2018). Mapping Three-dimensional Urban Structure by Fusing Landsat and Global Elevation Data, arXiv."},{"key":"ref_44","unstructured":"Department of Population (2015). The 2014 Myanmar Population and Housing Census, Ministry of Immigration and Population. The Union Report, Census Report Volume 2."},{"key":"ref_45","first-page":"248","article-title":"Urban Growth Modeling based on the Multi-centers of the Urban Areas and Land Cover Change in Yangon, Myanmar","volume":"37","author":"Sritarapipat","year":"2017","journal-title":"J. Remote Sens. Soc. Jpn."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"50","DOI":"10.20965\/jdr.2018.p0050","article-title":"Land Cover Change Simulations in Yangon Under Several Scenarios of Flood and Earthquake Vulnerabilities with Master Plan","volume":"13","author":"Sritarapipat","year":"2018","journal-title":"J. Disaster Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2005RG000183","article-title":"The shuttle radar topography mission","volume":"45","author":"Farr","year":"2007","journal-title":"Rev. Geophys."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"249","DOI":"10.14358\/PERS.72.3.249","article-title":"A Global Assessment of the SRTM Performance","volume":"72","author":"Morris","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_50","unstructured":"U.S. Geological Survey (2018, November 19). Societal Benefits of Higher Resolution SRTM Products, Available online: https:\/\/lpdaac.usgs.gov\/societal_benefits_higher_resolution_srtm_products."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"909","DOI":"10.1007\/s12040-016-0716-8","article-title":"Accuracy analysis of the 2014\u20132015 global shuttle radar topography mission (SRTM) 1 arc-sec C-Band height model using international global navigation satellite system service (IGS) network","volume":"125","author":"Mukul","year":"2016","journal-title":"J. Earth Syst. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.isprsjprs.2016.09.003","article-title":"Absolute and relative height-pixel accuracy of SRTM-GL1 over the South American Andean Plateau","volume":"121","author":"Satge","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_53","unstructured":"U.S. Geological Survey (2018, November 19). USGS Earth Explorer, Available online: https:\/\/earthexplorer.usgs.gov\/."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Tachikawa, T., Hat, M., Kaku, M., and Iwasaki, A. (2011, January 24\u201329). Characteristics of ASTER GDEM version 2. Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6050017"},{"key":"ref_55","unstructured":"NASA JPL (2018, November 19). ASTER Global Digital Elevation Map Announcement, Available online: https:\/\/asterweb.jpl.nasa.gov\/gdem.asp."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1080\/17538947.2013.807307","article-title":"Comparison and validation of SRTM and ASTER GDEM for a subtropical landscape in Southeastern China","volume":"7","author":"Jing","year":"2014","journal-title":"Int. J. Digit. Earth"},{"key":"ref_57","unstructured":"Colosimo, G., Crespi, M., De Vendictis, L., and Jacobsen, K. (2009, January 15\u201318). Accuracy evaluation of SRTM and ASTER DSMs. Proceedings of the 29th EARSeL Symposium, Chania, Greece."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Marconcini, M., Marmanis, D., Esch, T., and Felbier, A. (2014, January 13\u201318). A novel method for building height estmation using TanDEM-X data. Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada.","DOI":"10.1109\/IGARSS.2014.6947569"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.isprsjprs.2018.02.017","article-title":"Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data","volume":"139","author":"Wessel","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.pce.2015.07.007","article-title":"Evaluation of DEM generation based on Interferometric SAR using TanDEM-X data in Tokyo","volume":"83\u201384","author":"Avtar","year":"2015","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"25","DOI":"10.5194\/isprs-annals-III-4-25-2016","article-title":"Validation of \u2019AW3D\u2019 Global DSM Generated From ALOS PRISM","volume":"III-4","author":"Takaku","year":"2016","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1080\/2150704X.2018.1453174","article-title":"On the vertical accuracy of the ALOS world 3D-30m digital elevation model","volume":"9","author":"Caglar","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_63","first-page":"13","article-title":"Validating ALOS PRISM DSM-derived surface feature height: Implications for urban volume estimation","volume":"13","author":"Estoque","year":"2017","journal-title":"Tsukuba Geoenviron. Sci."},{"key":"ref_64","unstructured":"NTT DATA, and RESTEC (2018, November 19). High-Resolution Digital 3D Map Covering the Entire Global Land Area. Available online: https:\/\/www.aw3d.jp\/en\/products\/standard\/."},{"key":"ref_65","unstructured":"Earth Obervation Research Center JAXA (2018, November 19). ALOS Global Digital Surface Model \u201cALOS World 3D\u201430m (AW3D30)\u201d. Available online: https:\/\/www.eorc.jaxa.jp\/ALOS\/en\/aw3d30\/."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.rse.2018.04.043","article-title":"Evaluation of TanDEM-X DEMs on selected Brazilian sites: comparison with SRTM, ASTER GDEM and ALOS AW3D30","volume":"212","author":"Grohmann","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.1109\/TGRS.2013.2249521","article-title":"Generation and Quality Assessment of Stereo-Extracted DSM From GeoEye-1 and WorldView-2 Imagery","volume":"52","author":"Aguilar","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"3477","DOI":"10.1080\/01431161.2016.1182666","article-title":"Digital terrain models derived from digital surface model uniform regions in urban areas","volume":"37","author":"Beumier","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"2860","DOI":"10.1080\/01431161.2018.1434327","article-title":"Ground filtering and DTM generation from DSM data using probabilistic voting and segmentation","volume":"39","author":"Reinartz","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Xu, Y., Wu, L., Xie, Z., and Chen, Z. (2018). Building extraction in very high resolution remote sensing imagery using deep learning and guided filters. Remote Sens., 10.","DOI":"10.3390\/rs10010144"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.isprsjprs.2018.06.001","article-title":"A deep learning approach to DTM extraction from imagery using rule-based training labels","volume":"142","author":"Gevaert","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"481","DOI":"10.5194\/isprs-archives-XLII-1-W1-481-2017","article-title":"Building extraction from remote sensing data using fully convolutional networks","volume":"42","author":"Bittner","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., and Darrell, T. (2015, January 7\u201312). Fully convolutional networks for semantic segmentation. Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.J., Li, K., and Li, F.-F. (2009, January 20\u201325). ImageNet: A large-scale hierarchical image database. Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"165","DOI":"10.5194\/isprsannals-II-3-W4-165-2015","article-title":"Advanced DTM generation from very high resolution satellite stereo images","volume":"II-3\/W4","author":"Perko","year":"2015","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.isprsjprs.2008.09.001","article-title":"A multi-directional ground filtering algorithm for airborne LIDAR","volume":"64","author":"Meng","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"75","DOI":"10.5194\/isprs-archives-XLII-1-W1-75-2017","article-title":"New DTM extraction approach from airborne images derived DSM","volume":"42","author":"Mousa","year":"2017","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. ISPRS Arch."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Auer, S., Schmitt, M., and Reinartz, P. (2017, January 23\u201328). Automatic alignment of high resolution optical and SAR images for urban areas. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8128241"},{"key":"ref_79","unstructured":"Jones, E., Olopihant, T., and Pearu, P. (2018, December 10). SciPy: Open Source Scientific Tools for Python. Available online: http:\/\/www.scipy.org\/."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"4184","DOI":"10.1109\/JSTARS.2014.2318694","article-title":"An automatic and threshold-free performance evaluation system for building extraction techniques from airborne LIDAR data","volume":"7","author":"Awrangjeb","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.cag.2015.03.001","article-title":"Quantitative evaluation strategies for urban 3D model generation from remote sensing data","volume":"49","author":"Laefer","year":"2015","journal-title":"Comput. Graph. (Pergamon)"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1109\/JSTARS.2009.2012488","article-title":"A Comparison of Evaluation Techniques for Building Extraction From Airborne Laser Scanning","volume":"2","author":"Rutzinger","year":"2009","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.isprsjprs.2013.08.006","article-title":"Urban DEM generation, analysis and enhancements using TanDEM-X","volume":"85","author":"Rossi","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_84","first-page":"41","article-title":"DSM generation from high resolution imagery: Applications with WorldView-1 and Geoeye-1","volume":"44","author":"Capaldo","year":"2012","journal-title":"Eur. J. Remote Sens."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"308","DOI":"10.5589\/m13-039","article-title":"A stereo image matching method to improve the DSM accuracy inside building boundaries","volume":"39","author":"Zeng","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_86","first-page":"356","article-title":"DEM Accuracy and the Base to Height (B\/H) Ratio of Stereo Images","volume":"33","author":"Hasegawa","year":"2000","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_87","unstructured":"Arai, X., Ozawa, M., and Terayama, Y. (1994, January 8\u201312). Optimization method for B\/H ratio determination taking occlusion effect and MTF degradation due to atmosphere into account. Proceedings of the IGARSS \u201994\u20141994 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.isprsjprs.2006.01.001","article-title":"Multi-image matching for DSM generation from IKONOS imagery","volume":"60","author":"Zhang","year":"2006","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"034002","DOI":"10.1088\/1748-9326\/10\/3\/034002","article-title":"A new urban landscape in East\u2013Southeast Asia, 2000\u20132010","volume":"10","author":"Schneider","year":"2015","journal-title":"Environ. Res. Lett."},{"key":"ref_90","unstructured":"DLR (2018, November 19). Tandem-L Mission Description. Available online: https:\/\/www.tandem-l.de\/mission-description\/."},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Misra, P., Fujikawa, A., and Takeuchi, W. (2017). Novel decomposition scheme for characterizing urban air quality with MODIS. Remote Sens., 9.","DOI":"10.3390\/rs9080812"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/2008\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:33:10Z","timestamp":1760196790000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/12\/2008"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12,11]]},"references-count":91,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["rs10122008"],"URL":"https:\/\/doi.org\/10.3390\/rs10122008","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,12,11]]}}}