{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T09:50:06Z","timestamp":1776160206268,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,2,8]],"date-time":"2019-02-08T00:00:00Z","timestamp":1549584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The National key R &amp; D Program","award":["2018YFD1100405"],"award-info":[{"award-number":["2018YFD1100405"]}]},{"DOI":"10.13039\/501100001809","name":"The National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41701382"],"award-info":[{"award-number":["41701382"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hubei Provincial Natural Science Foundation Project","award":["220100039"],"award-info":[{"award-number":["220100039"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A new morphological attribute building index (MABI) and shadow index (MASI) are proposed here for automatically extracting building features from very high-resolution (VHR) remote sensing satellite images. By investigating the associated attributes in morphological attribute filters (AFs), the proposed method establishes a relationship between AFs and the characteristics of buildings\/shadows in VHR images (e.g., high local contrast, internal homogeneity, shape, and size). In the pre-processing step of the proposed work, attribute filtering was conducted on the original VHR spectral reflectance data to obtain the input, which has a high homogeneity, and to suppress elongated objects (potential non-buildings). Then, the MABI and MASI were calculated by taking the obtained input as a base image. The dark buildings were considered separately in the MABI to reduce the omission of the dark roofs. To better detect buildings from the MABI feature image, an object-oriented analysis and building-shadow concurrence relationships were utilized to further filter out non-building land covers, such as roads and bare ground, that are confused for buildings. Three VHR datasets from two satellite sensors, i.e., Worldview-2 and QuickBird, were tested to determine the detection performance. In view of both the visual inspection and quantitative assessment, the results of the proposed work are superior to recent automatic building index and supervised binary classification approach results.<\/jats:p>","DOI":"10.3390\/rs11030337","type":"journal-article","created":{"date-parts":[[2019,2,11]],"date-time":"2019-02-11T03:26:01Z","timestamp":1549855561000},"page":"337","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["An Automatic Morphological Attribute Building Extraction Approach for Satellite High Spatial Resolution Imagery"],"prefix":"10.3390","volume":"11","author":[{"given":"Weixuan","family":"Ma","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Youchuan","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sa","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mingwei","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Geological Survey, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2102","DOI":"10.1109\/JSTARS.2013.2271445","article-title":"A Global Human Settlement Layer From Optical HR\/VHR RS Data: Concept and First Results","volume":"6","author":"Pesaresi","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_2","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: Monitoring, Synthesis and Modeling in the Urban Environment, John Wiley & Sons, Ltd.","DOI":"10.1002\/9780470979563.ch3"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3873","DOI":"10.1080\/014311697216694","article-title":"Fine spatial resolution satellite sensors for the next decade","volume":"18","author":"Aplin","year":"1997","journal-title":"Int. Remote Sens."},{"key":"ref_4","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":"Bruzzone","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/TGRS.2012.2202912","article-title":"An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery","volume":"51","author":"Huang","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.isprsjprs.2013.05.008","article-title":"Classifying a high resolution image of an urban area using super-object information","volume":"83","author":"Johnson","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yan, W.Y., Shaker, A., and Zou, W. (2009, January 26\u201327). Panchromatic IKONOS Image Classification using Wavelet Based Features. Proceedings of the 2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH), Toronto, ON, Canada.","DOI":"10.1109\/TIC-STH.2009.5444455"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.proenv.2011.07.027","article-title":"Urban Morphology of Unplanned Settlements: The Use of Spatial Metrics in VHR Remotely Sensed Images","volume":"7","author":"Kuffer","year":"2011","journal-title":"Procedia Environ. Sci."},{"key":"ref_9","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_10","doi-asserted-by":"crossref","first-page":"133","DOI":"10.14358\/PERS.69.2.133","article-title":"Retrieving Urban Objects Using a Wavelet Transform Approach","volume":"69","author":"Bian","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1109\/LGRS.2006.890540","article-title":"Classification and Extraction of Spatial Features in Urban Areas Using High-Resolution Multispectral Imagery","volume":"4","author":"Huang","year":"2007","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Vakalopoulou, M., Karantzalos, K., Komodakis, N., and Paragios, N. (2015, January 26\u201331). Building Detection in Very High Resolution Multispectral Data with Deep Learning Features. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7326158"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/S0924-2716(98)00027-6","article-title":"Optimisation of building detection in satellite images by combining multispectral classification and texture filtering","volume":"54","author":"Zhang","year":"1999","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_14","first-page":"150","article-title":"Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours","volume":"12","author":"Ahmadi","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.isprsjprs.2009.10.002","article-title":"Automatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge","volume":"65","author":"Bouziani","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.isprsjprs.2007.01.001","article-title":"Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction","volume":"62","author":"Sohn","year":"2007","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1109\/JSTARS.2008.2002869","article-title":"A Robust Built-Up Area Presence Index by Anisotropic Rotation-Invariant Textural Measure","volume":"1","author":"Pesaresi","year":"2009","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Aytekin, O., Ulusoy, I., Erener, A., and Duzgun, H.S.B. (2009, January 11\u201313). Automatic and unsupervised building extraction in complex urban environments from multi spectral satellite imagery. Proceedings of the International Conference on Recent Advances in Space Technologies, Istanbul, Turkey.","DOI":"10.1109\/RAST.2009.5158214"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_20","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_21","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_22","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_23","first-page":"309","article-title":"A new approach for the morphological segmentation of high-resolution satellite imagery","volume":"39","author":"Chuvpilo","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","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_25","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1109\/JSTARS.2016.2587324","article-title":"A New Building Extraction Postprocessing Framework for High-Spatial-Resolution Remote-Sensing Imagery","volume":"10","author":"Huang","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1109\/LGRS.2016.2590481","article-title":"A Morphological Building Detection Framework for High-Resolution Optical Imagery Over Urban Areas","volume":"13","author":"Zhang","year":"2016","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3747","DOI":"10.1109\/TGRS.2010.2048116","article-title":"Morphological Attribute Profiles for the Analysis of Very High Resolution Images","volume":"48","author":"Mura","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1109\/TGRS.2014.2358934","article-title":"A Survey on Spectral\u2014Spatial Classification Techniques Based on Attribute Profiles","volume":"53","author":"Ghamisi","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","unstructured":"Mura, M.D., Benediktsson, J.A., and Bruzzone, L. (September, January 31). Modeling structural information for building extraction with morphological attribute filters. Proceedings of the SPIE\u2014The International Society for Optical Engineering, Berlin, Germany."},{"key":"ref_30","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":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1006\/cviu.1996.0066","article-title":"Attribute Openings, Thinnings, and Granulometries","volume":"64","author":"Breen","year":"1996","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1109\/83.663500","article-title":"Antiextensive connected operators for image and sequence processing","volume":"7","author":"Salembier","year":"1998","journal-title":"IEEE Trans. Image Process."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Ouzounis, G.K., and Soille, P. (2010, January 23\u201326). Differential Area Profiles. Proceedings of the 20th International Conference on Pattern Recognition, Istanbul, Turkey.","DOI":"10.1109\/ICPR.2010.993"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2943","DOI":"10.1109\/TIP.2007.909317","article-title":"Volumetric attribute filtering and interactive visualization using the Max-Tree representation","volume":"16","author":"Westenberg","year":"2007","journal-title":"IEEE Trans. Image Process."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1109\/LGRS.2012.2203784","article-title":"Automatic Generation of Standard Deviation Attribute Profiles for Spectral-Spatial Classification of Remote Sensing Data","volume":"10","author":"Marpu","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1109\/TIT.1962.1057692","article-title":"Visual pattern recognition by moment invariants","volume":"8","author":"Hu","year":"1962","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_37","unstructured":"Gonzalez, R.C., and Woods, R.E. (1987). Digital Image Processing, Addison-Wesley Longman Publishing Co.. [2nd ed.]."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1109\/34.1000236","article-title":"Mean shift: A robust approach toward feature space analysis","volume":"24","author":"Comaniciu","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1351","DOI":"10.1109\/TGRS.2005.846154","article-title":"Kernel-based methods for hyperspectral image classification","volume":"43","author":"Bruzzone","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1080\/01431160412331269698","article-title":"Random forest classifier for remote sensing classification","volume":"26","author":"Pal","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","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_42","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1111\/j.1477-9730.2010.00574_2.x","article-title":"Assessing the Accuracy of Remotely Sensed Data: Principles and Practices","volume":"25","author":"Foody","year":"2010","journal-title":"Photogramm. Rec."},{"key":"ref_43","first-page":"270","article-title":"A review of assessing the accuracy of classifications of remotely sensed data","volume":"37","author":"Congalton","year":"1998","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/3\/337\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:30:42Z","timestamp":1760185842000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/3\/337"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,8]]},"references-count":43,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["rs11030337"],"URL":"https:\/\/doi.org\/10.3390\/rs11030337","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,2,8]]}}}