{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T13:34:45Z","timestamp":1769693685834,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Re-search Foundation of Korea","award":["NRF-2020R1I1A3061750"],"award-info":[{"award-number":["NRF-2020R1I1A3061750"]}]},{"name":"National Re-search Foundation of Korea","award":["NRF-2021R1A5A8033165"],"award-info":[{"award-number":["NRF-2021R1A5A8033165"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-rise buildings (HRBs) as modern and visually unique land use continue to increase due to urbanization. Therefore, large-scale monitoring of HRB is very important for urban planning and environmental protection. This paper performed object-based HRB detection using high-resolution satellite image and digital map. Three study areas were acquired from KOMPSAT-3A, KOMPSAT-3, and WorldView-3, and object-based HRB detection was performed using the direction according to relief displacement by satellite image. Object-based multiresolution segmentation images were generated, focusing on HRB in each satellite image, and then combined with pixel-based building detection results obtained from MBI through majority voting to derive object-based building detection results. After that, to remove objects misdetected by HRB, the direction between HRB in the polygon layer of the digital map HRB and the HRB in the object-based building detection result was calculated. It was confirmed that the direction between the two calculated using the centroid coordinates of each building object converged with the azimuth angle of the satellite image, and results outside the error range were removed from the object-based HRB results. The HRBs in satellite images were defined as reference data, and the performance of the results obtained through the proposed method was analyzed. In addition, to evaluate the efficiency of the proposed technique, it was confirmed that the proposed method provides relatively good performance compared to the results of object-based HRB detection using shadows.<\/jats:p>","DOI":"10.3390\/rs14020330","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T20:33:04Z","timestamp":1641933184000},"page":"330","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Object-Based High-Rise Building Detection Using Morphological Building Index and Digital Map"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7025-6616","authenticated-orcid":false,"given":"Sejung","family":"Jung","sequence":"first","affiliation":[{"name":"Department of Convergence and Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3638-3715","authenticated-orcid":false,"given":"Kirim","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Spatial Information, Kyungpook National University, Daegu 41566, Korea"}]},{"given":"Won Hee","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Convergence and Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,11]]},"reference":[{"key":"ref_1","unstructured":"UN Organization (2018). World Urbanization Prospects."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1016\/j.proenv.2012.01.087","article-title":"Assess the effect of different degrees of urbanization on land surface temperature using remote sensing images","volume":"13","author":"Guo","year":"2012","journal-title":"Procedia Environ. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.ssci.2018.10.027","article-title":"Performance modeling of an intelligent emergency evacuation system in buildings on accidental fire occurrence","volume":"112","author":"Sheeba","year":"2019","journal-title":"Saf. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.rse.2005.01.002","article-title":"Spectral mixture analysis for subpixel vegetation fractions in the urban environment: How to incorporate endmember variability?","volume":"95","author":"Song","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.14358\/PERS.69.9.1003","article-title":"Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data","volume":"69","author":"Yang","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.isprsjprs.2017.10.012","article-title":"Breaking new ground in mapping human settlements from space\u2014The Global Urban Footprint","volume":"134","author":"Esch","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.rse.2011.09.015","article-title":"Monitoring urbanization in mega cities from space","volume":"117","author":"Esch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2015.12.027","article-title":"Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover","volume":"175","author":"Song","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"519","DOI":"10.14358\/PERS.80.6.519-528","article-title":"Performance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery","volume":"80","author":"Khosravi","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2354","DOI":"10.1109\/TGRS.2003.815972","article-title":"A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas","volume":"41","author":"Shackelford","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hu, L., Zheng, J., and Gao, F. (2011). A building extraction method using shadow in high resolution multispectral images. Int. Geosci. Remote Sens. Symp., 1862\u20131865.","DOI":"10.1109\/IGARSS.2011.6049486"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2003","DOI":"10.1007\/s12524-018-0868-x","article-title":"Building Extraction from High-Resolution Remotely Sensed Imagery Based on Multi-subgraph Matching","volume":"46","author":"Shi","year":"2018","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2587","DOI":"10.1109\/TGRS.2006.875360","article-title":"A multilevel context-based system for classification of very high spatial resolution images","volume":"44","author":"Carlin","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"You, Y., Wang, S., Ma, Y., Chen, G., Wang, B., Shen, M., and Liu, W. (2018). Building detection from VHR remote sensing imagery based on the morphological building index. Remote Sens., 10.","DOI":"10.3390\/rs10081287"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.isprsjprs.2003.09.002","article-title":"Object extraction and revision by image analysis using existing geodata and knowledge: Current status and steps towards operational systems","volume":"58","author":"Baltsavias","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1016\/j.isprsjprs.2010.09.006","article-title":"An update on automatic 3D building reconstruction","volume":"65","author":"Haala","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1109\/36.905239","article-title":"A new approach for the morphological segmentation of high-resolution satellite imagery","volume":"39","author":"Pesaresi","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1940","DOI":"10.1109\/TGRS.2003.814625","article-title":"Classification and feature extraction for remote sensing images from urban areas based on morphological transformations","volume":"41","author":"Benediktsson","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3804","DOI":"10.1109\/TGRS.2008.922034","article-title":"Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles","volume":"46","author":"Fauvel","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.1016\/j.proeng.2017.04.308","article-title":"Building Classification from Lidar Data for Spatio-temporal Assessment of 3D Urban Developments","volume":"180","author":"Shirowzhan","year":"2017","journal-title":"Procedia Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jweia.2014.10.018","article-title":"Cyclone damage detection on building structures from pre- and post-satellite images using wavelet based pattern recognition","volume":"136","author":"Radhika","year":"2015","journal-title":"J. Wind Eng. Ind. Aerodyn."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1080\/2150704X.2017.1402384","article-title":"A morphology-based method for building change detection using multi-temporal airborne LiDAR data","volume":"9","author":"Xi","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.isprsjprs.2017.06.005","article-title":"Automatic building extraction from LiDAR data fusion of point and grid-based features","volume":"130","author":"Du","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yan, Y., Tan, Z., Su, N., and Zhao, C. (2017). Building extraction based on an optimized stacked sparse autoencoder of structure and training samples using LIDAR DSM and optical images. Sensors, 17.","DOI":"10.3390\/s17091957"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1109\/TGRS.2020.3000296","article-title":"Building Change Detection in VHR SAR Images via Unsupervised Deep Transcoding","volume":"59","author":"Saha","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1186\/1687-6180-2013-56","article-title":"Building detection from urban SAR image using building characteristics and contextual information","volume":"2013","author":"Zhao","year":"2013","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"107447","DOI":"10.1016\/j.patcog.2020.107447","article-title":"Building outline extraction from als point clouds using medial axis transform descriptors","volume":"106","author":"Widyaningrum","year":"2020","journal-title":"Pattern Recognit."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1109\/LGRS.2014.2386878","article-title":"Object-based change detection of very high resolution satellite imagery using the cross-sharpening of multitemporal data","volume":"12","author":"Wang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"7068349","DOI":"10.1155\/2018\/7068349","article-title":"Deep Learning for Computer Vision: A Brief Review","volume":"2018","author":"Voulodimos","year":"2018","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Park, H., Choi, J., Park, W., and Park, H. (2018). Modified S2CVA algorithm using cross-sharpened images for unsupervised change detection. Sustainability, 10.","DOI":"10.3390\/su10093301"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Gharibbafghi, Z., Tian, J., and Reinartz, P. (2018). Modified superpixel segmentation for digital surface model refinement and building extraction from satellite stereo imagery. Remote Sens., 10.","DOI":"10.3390\/rs10111824"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1016\/j.buildenv.2015.09.026","article-title":"The airborne transmission of infection between flats in high-rise residential buildings: A review","volume":"94","author":"Mao","year":"2015","journal-title":"Build. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1111\/ina.12712","article-title":"Inter-zonal airflow in multi-unit residential buildings: A review of the magnitude and interaction of driving forces, measurement techniques and magnitudes, and its impact on building performance","volume":"30","author":"Lozinsky","year":"2020","journal-title":"Indoor Air"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1007\/s12524-020-01161-0","article-title":"Extraction of Buildings in Urban Area for Surface Area Assessment from Satellite Imagery based on Morphological Building Index using SVM Classifier","volume":"48","author":"Avudaiammal","year":"2020","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.rse.2011.11.020","article-title":"A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery","volume":"118","author":"Duro","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.isprsjprs.2013.03.006","article-title":"Change detection from remotely sensed images: From pixel-based to object-based approaches","volume":"80","author":"Hussain","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.14358\/PERS.78.10.1029","article-title":"A supervised and fuzzy-based approach to determine optimal multi-resolution image segmentation parameters","volume":"78","author":"Tong","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1109\/JSTARS.2013.2252423","article-title":"Building change detection from multitemporal high-resolution remotely sensed images based on a morphological building index","volume":"7","author":"Huang","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"721","DOI":"10.14358\/PERS.77.7.721","article-title":"A multidirectional and multiscale morphological index for automatic building extraction from multispectralgeoeye-1 imagery","volume":"77","author":"Huang","year":"2011","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1109\/JSTARS.2011.2168195","article-title":"Morphological building\/shadow index for building extraction from high-resolution imagery over urban areas","volume":"5","author":"Huang","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1109\/34.969120","article-title":"Directional morphological filtering","volume":"23","author":"Soille","year":"2001","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Jung, S., Lee, W.H., and Han, Y. (2021). Change detection of building objects in high-resolution single-sensor and multi-sensor imagery considering the sun and sensor\u2019s elevation and azimuth angles. Remote Sens., 13.","DOI":"10.3390\/rs13183660"},{"key":"ref_43","first-page":"1","article-title":"Building extraction using object-based classification and shadow information in very high resolution multispectral images, a case study: Tetuan, Morocco","volume":"4","author":"Benarchid","year":"2013","journal-title":"Can. J. Image Process. Comput. Vis."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"159","DOI":"10.2307\/2529310","article-title":"The Measurement of Observer Agreement for Categorical Data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/2\/330\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:02:03Z","timestamp":1760364123000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/2\/330"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,11]]},"references-count":44,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14020330"],"URL":"https:\/\/doi.org\/10.3390\/rs14020330","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,11]]}}}