{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T13:43:24Z","timestamp":1772891004909,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2016,10,25]],"date-time":"2016-10-25T00:00:00Z","timestamp":1477353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007028","name":"Leona M. and Harry B. Helmsley Charitable Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007028","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar\u2019s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while considering scenarios with all natural forest classes grouped into a single intact or degraded category. Overall, classification accuracy increased for the multivariate Gaussian model with the partitioning of intact and degraded forest into separate forest cover classes but slightly decreased based on the Random Forest classifier. Natural forest cover was estimated to be 80.7% of total area in Tanintharyi. The most prevalent forest types are upland evergreen forest (42.3% of area) and lowland evergreen forest (21.6%). However, while just 27.1% of upland evergreen forest was classified as degraded (on the basis of canopy cover &lt;80%), 66.0% of mangrove forest and 47.5% of the region\u2019s biologically-rich lowland evergreen forest were classified as degraded. This information on the current status of Tanintharyi\u2019s unique forest ecosystems and patterns of human land use is critical to effective conservation strategies and land-use planning.<\/jats:p>","DOI":"10.3390\/rs8110882","type":"journal-article","created":{"date-parts":[[2016,10,25]],"date-time":"2016-10-25T10:28:49Z","timestamp":1477391329000},"page":"882","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar\u2019s Tanintharyi Region"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9424-6591","authenticated-orcid":false,"given":"Grant","family":"Connette","sequence":"first","affiliation":[{"name":"Conservation Ecology Center\/Myanmar Program, Smithsonian Conservation Biology Institute, 1500 Remount Road, Front Royal, VA 22630, USA"}]},{"given":"Patrick","family":"Oswald","sequence":"additional","affiliation":[{"name":"Fauna &amp; Flora International, 35 Shan Kone Street, San Chaung Township, Yangon 11111, Myanmar"}]},{"given":"Melissa","family":"Songer","sequence":"additional","affiliation":[{"name":"Conservation Ecology Center\/Myanmar Program, Smithsonian Conservation Biology Institute, 1500 Remount Road, Front Royal, VA 22630, USA"}]},{"given":"Peter","family":"Leimgruber","sequence":"additional","affiliation":[{"name":"Conservation Ecology Center\/Myanmar Program, Smithsonian Conservation Biology Institute, 1500 Remount Road, Front Royal, VA 22630, USA"}]}],"member":"1968","published-online":{"date-parts":[[2016,10,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1093\/sysbio\/syu047","article-title":"Borneo and Indochina are major evolutionary hotspots for Southeast Asian biodiversity","volume":"63","author":"Stelbrink","year":"2014","journal-title":"Syst. 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