{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T10:05:39Z","timestamp":1760609139514,"version":"build-2065373602"},"reference-count":65,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T00:00:00Z","timestamp":1552003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Change detection methods are often incapable of accurately detecting changes within time series that are heavily influenced by seasonal variations. Techniques for de-seasoning time series or methods that apply the spatial context have been used to improve the results of change detection. However, few studies have explored Landsat\u2019s shortwave infrared channel (SWIR 2) to discriminate between seasonal changes and land use\/land cover changes (LULCC). Here, we explored the effectiveness of Operational Land Imager (OLI) spectral bands and vegetation indices for detecting deforestation in highly seasonal areas of Brazilian savannas. We adopted object-based image analysis (OBIA), applying a multidate segmentation to an OLI time series to generate input data for discrimination of deforestation from seasonal changes using the Random Forest (RF) algorithm. We found adequate separability between deforested objects and seasonal changes using SWIR 2. Using spectral indices computed from SWIR 2, the RF algorithm generated a change map with an overall accuracy of 88.3%. For deforestation, the producer\u2019s accuracy was 88.0% and the user\u2019s accuracy was 84.6%. The SWIR 2 channel as well as the mid-infrared burn index presented the highest importance among spectral variables computed by the RF average impurity decrease measure. Our results give support to further change detection studies regarding to suitable spectral channels and provided a useful foundation for savanna change detection using an object-based method applied to Landsat time series.<\/jats:p>","DOI":"10.3390\/rs11050570","type":"journal-article","created":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T11:21:59Z","timestamp":1552044119000},"page":"570","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Object-Based Change Detection in the Cerrado Biome Using Landsat Time Series"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6662-3396","authenticated-orcid":false,"given":"Inacio T.","family":"Bueno","sequence":"first","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]},{"given":"Fausto W.","family":"Acerbi J\u00fanior","sequence":"additional","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1015-4973","authenticated-orcid":false,"given":"Eduarda M. O.","family":"Silveira","sequence":"additional","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]},{"given":"Jos\u00e9 M.","family":"Mello","sequence":"additional","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]},{"given":"Lu\u00eds M. T.","family":"Carvalho","sequence":"additional","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]},{"given":"Lucas R.","family":"Gomide","sequence":"additional","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9550-4249","authenticated-orcid":false,"given":"Kieran","family":"Withey","sequence":"additional","affiliation":[{"name":"Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK"}]},{"given":"Jos\u00e9 Roberto S.","family":"Scolforo","sequence":"additional","affiliation":[{"name":"Forest Science Department, Federal University of Lavras, Lavras 37200-000, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"874","DOI":"10.1080\/01431161.2016.1271959","article-title":"Relationships between vegetation indices, fractional cover retrievals and the structure and composition of Brazilian Cerrado natural vegetation","volume":"38","author":"Hill","year":"2017","journal-title":"Int. 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