{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:23:35Z","timestamp":1781367815903,"version":"3.54.1"},"reference-count":37,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2011,11,18]],"date-time":"2011-11-18T00:00:00Z","timestamp":1321574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The need to monitor the Earth\u2019s surface over a range of spatial and temporal scales is fundamental in ecosystems planning and management. Change-Vector Analysis (CVA) is a bi-temporal method of change detection that considers the magnitude and direction of change vector. However, many multispectral applications do not make use of the direction component. The procedure most used to calculate the direction component using multiband data is the direction cosine, but the number of output direction cosine images is equal to the number of original bands and has a complex interpretation. This paper proposes a new approach to calculate the spectral direction of change, using the Spectral Angle Mapper and Spectral Correlation Mapper spectral-similarity measures. The chief advantage of this approach is that it generates a single image of change information insensitive to illumination variation. In this paper the magnitude component of the spectral similarity was calculated in two ways: as the standard Euclidean distance and as the Mahalanobis distance. In this test the best magnitude measure was the Euclidean distance and the best similarity measure was Spectral Angle Mapper. The results show that the distance and similarity measures are complementary and need to be applied together.<\/jats:p>","DOI":"10.3390\/rs3112473","type":"journal-article","created":{"date-parts":[[2011,11,18]],"date-time":"2011-11-18T11:18:42Z","timestamp":1321615122000},"page":"2473-2493","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":156,"title":["A New Approach to Change Vector Analysis Using Distance and Similarity Measures"],"prefix":"10.3390","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0346-1684","authenticated-orcid":false,"given":"Osmar A.","family":"Carvalho J\u00fanior","sequence":"first","affiliation":[{"name":"Departamento de Geografia, Universidade de Bras\u00edlia (UnB), Campus Universit\u00e1rio Darcy Ribeiro, Asa Norte, Bras\u00edlia, DF CEP. 70910-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9555-043X","authenticated-orcid":false,"given":"Renato F.","family":"Guimar\u00e3es","sequence":"additional","affiliation":[{"name":"Departamento de Geografia, Universidade de Bras\u00edlia (UnB), Campus Universit\u00e1rio Darcy Ribeiro, Asa Norte, Bras\u00edlia, DF CEP. 70910-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan R.","family":"Gillespie","sequence":"additional","affiliation":[{"name":"Department of Earth and Space Sciences, University of Washington, Seattle, WA 98195, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nilton C.","family":"Silva","sequence":"additional","affiliation":[{"name":"Centro Universit\u00e1rio de An\u00e1polis (Unievang\u00e9lica), Avenida Universit\u00e1ria km 3,5, Cidade Universit\u00e1ria, An\u00e1polis, GO CEP. 75083-515, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto A. T.","family":"Gomes","sequence":"additional","affiliation":[{"name":"Departamento de Geografia, Universidade de Bras\u00edlia (UnB), Campus Universit\u00e1rio Darcy Ribeiro, Asa Norte, Bras\u00edlia, DF CEP. 70910-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2011,11,18]]},"reference":[{"key":"ref_1","unstructured":"Malila, W.A. (1980, January 3\u20136). Change Vector Analysis: An Approach for Detecting Forest Changes with Landsat. Proceedings of 6th Annual Symposium on Machine Processing of Remotely Sensed Data Soil Information Systems and Remote Sensing and Soil Survey, West Lafayette, IN, USA."},{"key":"ref_2","first-page":"343","article-title":"Application of the Tasseled Cap concept to simulated thematic mapper data","volume":"50","author":"Crist","year":"1984","journal-title":"Photogramm. Eng. 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