{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:25:47Z","timestamp":1783009547057,"version":"3.54.5"},"reference-count":43,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,15]],"date-time":"2018-11-15T00:00:00Z","timestamp":1542240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701396"],"award-info":[{"award-number":["61701396"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Shaan Xi Province","award":["2017JQ4006"],"award-info":[{"award-number":["2017JQ4006"]}]},{"name":"Open Fund of Key Laboratory of Geospatial Big Data Mining and Application, Hunan Province","award":["201802"],"award-info":[{"award-number":["201802"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To improve the performance of land-cover change detection (LCCD) using remote sensing images, this study utilises spatial information in an adaptive and multi-scale manner. It proposes a novel multi-scale object histogram distance (MOHD) to measure the change magnitude between bi-temporal remote sensing images. Three major steps are related to the proposed MOHD. Firstly, multi-scale objects for the post-event image are extracted through a widely used algorithm called the fractional net evaluation approach. The pixels within a segmental object are taken to construct the pairwise frequency distribution histograms. An arithmetic frequency-mean feature is then defined from the red, green and blue band histogram. Secondly, bin-to-bin distance is adapted to measure the change magnitude between the pairwise objects of bi-temporal images. The change magnitude image (CMI) of the bi-temporal images can be generated through object-by-object. Finally, the classical binary method Otsu is used to divide the CMI to a binary change detection map. Experimental results based on two real datasets with different land-cover change scenes demonstrate the effectiveness of the proposed MOHD approach in detecting land-cover change compared with three widely used existing approaches.<\/jats:p>","DOI":"10.3390\/rs10111809","type":"journal-article","created":{"date-parts":[[2018,11,15]],"date-time":"2018-11-15T11:32:47Z","timestamp":1542281567000},"page":"1809","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Multi-Scale Object Histogram Distance for LCCD Using Bi-Temporal Very-High-Resolution Remote Sensing Images"],"prefix":"10.3390","volume":"10","author":[{"given":"ZhiYong","family":"Lv","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019An University of Technology, Xi\u2019an 710048, China"},{"name":"Key Laboratory of Geospatial Big Data Mining and Application, Changsha 410081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1394-4724","authenticated-orcid":false,"given":"TongFei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Xi\u2019An University of Technology, Xi\u2019an 710048, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0621-9647","authenticated-orcid":false,"given":"J\u00f3n","family":"Atli Benediktsson","sequence":"additional","affiliation":[{"name":"Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik IS 107, Iceland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Lei","sequence":"additional","affiliation":[{"name":"School of Electronical and Information Engineering, Shaanxi University of Science and Technology, Xi\u2019an 710021, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7346-3442","authenticated-orcid":false,"given":"YiLiang","family":"Wan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Geospatial Big Data Mining and Application, Changsha 410081, China"},{"name":"College of Resources and Environmental Sciences, Hunan Normal University, Changsha 410081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,15]]},"reference":[{"key":"ref_1","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. 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