Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar’s Tanintharyi Region

Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar’s Tanintharyi Region

We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and hu...

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Bibliographic Details
Main Authors: Grant Connette, Patrick Oswald, Melissa Songer, Peter Leimgruber
Format: Article
Language:English
Published: MDPI AG 2016-10-01
Series:Remote Sensing
Subjects:
remote sensing
forest types
forest classification
Landsat 8 OLI
satellite imagery
wildlife habitat
tropical forest
mangrove
Online Access:http://www.mdpi.com/2072-4292/8/11/882

Internet

http://www.mdpi.com/2072-4292/8/11/882

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