{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T15:52:41Z","timestamp":1778860361633,"version":"3.51.4"},"reference-count":57,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,11]],"date-time":"2020-09-11T00:00:00Z","timestamp":1599782400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2017R1C1B2005744"],"award-info":[{"award-number":["2017R1C1B2005744"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Change detection (CD) is an important tool in remote sensing. CD can be categorized into pixel-based change detection (PBCD) and object-based change detection (OBCD). PBCD is traditionally used because of its simple and straightforward algorithms. However, with increasing interest in very-high-resolution (VHR) imagery and determining changes in small and complex objects such as buildings or roads, traditional methods showed limitations, for example, the large number of false alarms or noise in the results. Thus, researchers have focused on extending PBCD to OBCD. In this study, we proposed a method for detecting the newly built-up areas by extending PBCD results into an OBCD result through the Dempster\u2013Shafer (D\u2013S) theory. To this end, the morphological building index (MBI) was used to extract built-up areas in multitemporal VHR imagery. Then, three PBCD algorithms, change vector analysis, principal component analysis, and iteratively reweighted multivariate alteration detection, were applied to the MBI images. For the final CD result, the three binary change images were fused with the segmented image using the D\u2013S theory. The results obtained from the proposed method were compared with those of PBCD, OBCD, and OBCD results generated by fusing the three binary change images using the major voting technique. Based on the accuracy assessment, the proposed method produced the highest F1-score and kappa values compared with other CD results. The proposed method can be used for detecting new buildings in built-up areas as well as changes related to demolished buildings with a low rate of false alarms and missed detections compared with other existing CD methods.<\/jats:p>","DOI":"10.3390\/rs12182952","type":"journal-article","created":{"date-parts":[[2020,9,11]],"date-time":"2020-09-11T09:05:16Z","timestamp":1599815116000},"page":"2952","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Object-Based Building Change Detection by Fusing Pixel-Level Change Detection Results Generated from Morphological Building Index"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7694-6957","authenticated-orcid":false,"given":"Aisha","family":"Javed","sequence":"first","affiliation":[{"name":"Department of Convergence &amp; Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sejung","family":"Jung","sequence":"additional","affiliation":[{"name":"Department of Spatial Information, Kyungpook National University, Daegu 41566, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Won Hee","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Convergence &amp; Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6586-8503","authenticated-orcid":false,"given":"Youkyung","family":"Han","sequence":"additional","affiliation":[{"name":"School of Convergence &amp; Fusion System Engineering, Kyungpook National University, Sangju 37224, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1038\/509158a","article-title":"Society: Realizing China\u2019s urban dream","volume":"509","author":"Bai","year":"2014","journal-title":"Nat. News"},{"key":"ref_2","unstructured":"Grubler, A., Bai, X., Buettner, T., Dhakal, S., Fisk, D.J., Ichinose, T., Keirstead, J.E., Sammer, G., Satterthwaite, D., and Schulz, N.B. (2012). Chapter 18-Urban Energy Systems. Global Energy Assessment, International Institute for Applied Systems Analysis."},{"key":"ref_3","unstructured":"Seto, K.C., Dhakal, S., Bigio, A., Blanco, H., Delgado, G.C., Dewar, D., Huang, L., Inaba, A., Kansal, A., and Lwasa, S. (2014). Human Settlements, Infrastructure and Spatial Planning, Cambridge University Press."},{"key":"ref_4","unstructured":"United Nations Development Program (UNDP) (2016). UNDP Support to the Implementation of the 2030 Agenda for Sustainable Development, UNDP Policy and Programme Brief."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1002\/sd.1582","article-title":"Towards integration at last? The sustainable development goals as a network of targets","volume":"23","year":"2015","journal-title":"Sustain. Dev."},{"key":"ref_6","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_7","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1080\/01431168908903939","article-title":"Review article digital change detection techniques using remotely-sensed data","volume":"10","author":"Singh","year":"1989","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/LGRS.2008.917726","article-title":"An unsupervised technique based on morphological filters for change detection in very high resolution images","volume":"5","author":"Benediktsson","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1109\/LGRS.2012.2222340","article-title":"Change detection in VHR images based on morphological attribute profiles","volume":"10","author":"Falco","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3578","DOI":"10.1109\/JSTARS.2019.2929514","article-title":"Unsupervised change detection in multispectral remote sensing images via spectral-spatial band expansion","volume":"12","author":"Liu","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1109\/TGRS.2006.885408","article-title":"A theoretical framework for unsupervised change detection based on change vector analysis in the polar domain","volume":"45","author":"Bovolo","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/S0034-4257(97)00112-0","article-title":"A comparison of four algorithms for change detection in an urban environment","volume":"63","author":"Ridd","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1109\/MGRS.2019.2898520","article-title":"A review of change detection in multitemporal hyperspectral images: Current techniques, applications, and challenges","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2473","DOI":"10.3390\/rs3112473","article-title":"A new approach to change vector analysis using distance and similarity measures","volume":"3","author":"Gillespie","year":"2011","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3486","DOI":"10.1109\/JSTARS.2015.2416635","article-title":"Improving pixel-based change detection accuracy using an object-based approach in multitemporal SAR Flood Images","volume":"8","author":"Lu","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4434","DOI":"10.1080\/01431161.2011.648285","article-title":"Object-based change detection","volume":"33","author":"Chen","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2658","DOI":"10.1109\/TGRS.2009.2017014","article-title":"Analysis and adaptive estimation of the registration noise distribution in multitemporal VHR images","volume":"47","author":"Bovolo","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zhou, Z., Ma, L., Fu, T., Zhang, G., Yao, M., and Li, M. (2018). Change detection in coral reef environment using high-resolution images: Comparison of object-based and pixel-based paradigms. ISPRS Int. J. Geo Inf., 7.","DOI":"10.3390\/ijgi7110441"},{"key":"ref_19","first-page":"1","article-title":"A comparative analysis of pixel-and object-based detection of landslides from very high-resolution images","volume":"64","author":"Keyport","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5719","DOI":"10.1080\/01431161.2010.507263","article-title":"Object-oriented change detection based on the Kolmogorov\u2013Smirnov test using high-resolution multispectral imagery","volume":"32","author":"Tang","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ma, L., Li, M., Blaschke, T., Ma, X., Tiede, D., Cheng, L., Chen, Z., and Chen, D. (2016). Object-based change detection in urban areas: The effects of segmentation strategy, scale, and feature space on unsupervised methods. Remote Sens., 8.","DOI":"10.3390\/rs8090761"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Cui, G., Lv, Z., Li, G., Atli Benediktsson, J., and Lu, Y. (2018). Refining land cover classification maps based on dual-adaptive majority voting strategy for very high resolution remote sensing images. Remote Sens., 10.","DOI":"10.3390\/rs10081238"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5457","DOI":"10.1080\/01431161.2016.1232871","article-title":"Object-oriented change detection method based on adaptive multi-method combination for remote-sensing images","volume":"37","author":"Cai","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Rasti, B., Hong, D., Hang, R., Ghamisi, P., Kang, X., Chanussot, J., and Benediktsson, J. (2020). Feature extraction for hyperspectral imagery: The evolution from shallow to deep (overview and toolbox). IEEE Geosci. Remote Sens. Mag.","DOI":"10.1109\/MGRS.2020.2979764"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.1109\/TIP.2018.2878958","article-title":"An augmented linear mixing model to address spectral variability for hyperspectral unmixing","volume":"28","author":"Hong","year":"2019","journal-title":"IEEE Trans. on Image Proces."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1080\/2150704X.2020.1716407","article-title":"An adaptively weighted multi-feature method for object-based change detection in high spatial resolution remote sensing images","volume":"11","author":"Wu","year":"2020","journal-title":"Remote Sens. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.isprsjprs.2016.07.003","article-title":"Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition","volume":"119","author":"Xiao","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Lv, Z., Liu, T., Wan, Y., Benediktsson, J.A., and Zhang, X. (2018). Post-processing approach for refining raw land cover change detection of very-high-resolution remote sensing images. Remote Sens., 10.","DOI":"10.3390\/rs10030472"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Cao, J., Lv, Z., and Benediktsson, J.A. (2019). Spatial\u2013spectral feature fusion coupled with multi-scale segmentation voting decision for detecting land cover change with VHR remote sensing images. Remote Sens., 11.","DOI":"10.3390\/rs11161903"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Luo, H., Liu, C., Wu, C., and Guo, X. (2018). Urban change detection based on dempster\u2013shafer theory for multitemporal very-high-resolution imagery. Remote Sens., 10.","DOI":"10.3390\/rs10070980"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Han, Y., Javed, A., Jung, S., and Liu, S. (2020). Object-Based Change Detection of Very High Resolution Images by Fusing Pixel-Based Change Detection Results Using Weighted Dempster\u2013Shafer Theory. Remote Sens., 12.","DOI":"10.3390\/rs12060983"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Liu, H., Yang, M., Chen, J., Hou, J., and Deng, M. (2018). Line-constrained shape feature for building change detection in VHR remote sensing imagery. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7100410"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1080\/01431160601075582","article-title":"Object-based change detection using correlation image analysis and image segmentation","volume":"29","author":"Im","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","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":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"640","DOI":"10.1080\/2150704X.2020.1750729","article-title":"Automatic building detection from very high-resolution images using multiscale morphological attribute profiles","volume":"11","author":"Li","year":"2020","journal-title":"Remote Sens. Lett."},{"key":"ref_36","first-page":"15","article-title":"Unsupervised change detection in VHR remote sensing imagery\u2013an object-based clustering approach in a dynamic urban environment","volume":"54","author":"Leichtle","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.isprsjprs.2020.06.020","article-title":"Multi-level monitoring of three-dimensional building changes for megacities: Trajectory, morphology, and landscape","volume":"167","author":"Cao","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Awrangjeb, M., Gilani, S.A.N., and Siddiqui, F.U. (2018). An effective data-driven method for 3-d building roof reconstruction and robust change detection. Remote Sens., 10.","DOI":"10.3390\/rs10101512"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.rse.2017.09.022","article-title":"Separate segmentation of multi-temporal high-resolution remote sensing images for object-based change detection in urban area","volume":"201","author":"Zhang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1080\/2150704X.2014.963732","article-title":"A novel building change index for automatic building change detection from high-resolution remote sensing imagery","volume":"5","author":"Huang","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1109\/TGRS.2015.2463075","article-title":"A novel automatic change detection method for urban high-resolution remotely sensed imagery based on multiindex scene representation","volume":"54","author":"Wen","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1850031","DOI":"10.1142\/S0218213018500318","article-title":"A multi-level approach for change detection of buildings using satellite imagery","volume":"27","author":"Sheikh","year":"2018","journal-title":"Int. J. Artif. Intell. Tools"},{"key":"ref_43","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 multispectral GeoEye-1 imagery","volume":"77","author":"Huang","year":"2011","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1109\/LGRS.2009.2025059","article-title":"Unsupervised change detection in satellite images using principal component analysis and K-means clustering","volume":"6","author":"Celik","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1109\/TIP.2006.888195","article-title":"The regularized iteratively reweighted MAD method for change detection in multi-and hyperspectral data","volume":"16","author":"Nielsen","year":"2007","journal-title":"IEEE Trans. Image Process."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"503","DOI":"10.7848\/ksgpc.2013.31.6-1.503","article-title":"Positioning accuracy analysis of KOMPSAT-3 satellite imagery by RPC adjustment","volume":"31","author":"Lee","year":"2013","journal-title":"J. Korean Soc. Surv. Geod. Photogramm. Cartogr."},{"key":"ref_47","first-page":"C7","article-title":"Multiresolution segmentation: A parallel approach for high resolution image segmentation in multicore architectures","volume":"38","author":"Happ","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_48","unstructured":"Zhang, Y., Maxwell, T., Tong, H., and Dey, V. (2010, January 5\u20137). Development of a Supervised Software Tool for Automated Determination of Optimal Segmentation Parameters for Ecognition. Proceedings of the ISPRS TC VII symposium-100 Years ISPRS, Vienna, Austria."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.isprsjprs.2014.07.002","article-title":"Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery","volume":"96","author":"Belgiu","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2013.11.018","article-title":"Automated parameterisation for multi-scale image segmentation on multiple layers","volume":"88","author":"Csillik","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_51","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_52","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":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_53","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_54","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_55","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_56","first-page":"330","article-title":"Dempster-shafer theory","volume":"1","author":"Shafer","year":"1992","journal-title":"Encycl. Artif. Intell."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Han, Y., Kim, T., and Yeom, J. (2019). Improved piecewise linear transformation for precise warping of very-high-resolution remote sensing images. Remote Sens., 11.","DOI":"10.3390\/rs11192235"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/18\/2952\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:09:05Z","timestamp":1760177345000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/18\/2952"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,11]]},"references-count":57,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["rs12182952"],"URL":"https:\/\/doi.org\/10.3390\/rs12182952","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,11]]}}}