Myanmar Information Management Unit (MIMU)

Low-lying Areas below 5 meters elevation. This dataset is derived from the Multi-Error-Removed Improved-Terrain / MERIT DEM.

Geotiff download link: http://bit.ly/2ToMIjL This dataset is the result of a land cover analysis for Myanmar's Tanintharyi Region based on March, 2016 Landsat 8 OLI imagery. The primary purpose of the study was to map natural forest for each of four ecological forest types (Mangrove, Mixed Deciduous, Lowland Evergreen, Upland Evergreen). A number of other land use/land cover types are also included in the dataset, including human settlement areas, rice paddyfields, and agroforestry plantations. This dataset is a REVISED version of the land cover map generated according to the methodology outlined in the corresponding manuscript (see below for citation). This version has been manually edited to fill cloud holes using 2015 data and to fix a number of obvious mis-classifications, particularly for oil palm and settlement areas. [Citation: Connette, G., P. Oswald, M. Songer, and P. Leimgruber. 2016. Mapping distinct forest types improves overall forest identification based on multi-spectral Landsat imagery. Remote Sensing 8: 882.] [Spatial reference: WGS84 UTM47N] Original dataset title: Tanintharyi Region Land Cover - March 2016 (Improved)

Geotiff download link: http://bit.ly/2IjLZtw This dataset is the result of a land cover analysis for Myanmar's Tanintharyi Region based on March, 2016 Landsat 8 OLI imagery. The primary purpose of the study was to map natural forest for each of four ecological forest types (Mangrove, Mixed Deciduous, Lowland Evergreen, Upland Evergreen). A number of other land use/land cover types are also included in the dataset, including human settlement areas, rice paddyfields, and agroforestry plantations. This dataset is the original version generated according to the methodology outlined in the corresponding manuscript. [Citation: Connette, G., P. Oswald, M. Songer, and P. Leimgruber. 2016. Mapping distinct forest types improves overall forest identification based on multi-spectral Landsat imagery. Remote Sensing 8: 882.] [Spatial reference: WGS84 UTM47N] Original dataset title: Tanintharyi Region Land Cover - March 2016 (Original)

Geotiff download link : http://bit.ly/2PHtJyf This is a Landsat 8-based classification of the extent and condition of mangrove forests in Tanintharyi Region. The classification is derived from satellite images which were acquired in 2014. The classification is based on ground truth data, which was collected in May and June 2015. In addition, further training polygons were digitized based on high-resolution Google Maps and Bing Maps data. This dataset is a filtered version of the initial classification result. The classified mangrove classes are ‘Intact to slightly degraded mangroves’, ‘Degraded mangroves’, ‘Heavily degraded mangroves’ and ‘Nipa monoculture’. suggested citiation: Stephani, A.; Oswald, P.; Koellner, T.; Wegmann, M., 2016. Tanintharyi Region Mangrove Forest dataset (2014). Point of contact: annastephani@gmx.de and patrickoswald@fauna-flora.org

Geotiff download link : http://bit.ly/2wq7KFy Metadata download link: http://geonode.themimu.info/documents/26 A Landsat-based classification of forest cover in Tanintharyi Region with a focus on changes in intact forest between 2002 and 2014. This dataset expands upon the Myanmar 2002-2014 Forest Cover Change raster*, by differentiating oil palm plantations from other plantations. Developed by: ALARM, Smithsonian Institution, GMAP and American Museum of Natural History *http://geonode.themimu.info/layers/geonode%3Amyanmar_forestcoverchange See the recommended style file (.txt) in the documents section for associating raster values and creating the legend. Original dataset title: Tanintharyi Region 2002-2014 Forest Cover Change

Geotiff download link : http://bit.ly/2VOvrlD Metadata Download link: http://geonode.themimu.info/documents/27 A Landsat-based classification of forest cover in Kachin State and Sagaing Region with a focus on changes in intact forest between 2002 and 2014. This dataset expands upon the Myanmar 2002-2014 Forest Cover Change raster*, by differentiating mining from other non-forest land cover classes. Developed by: ALARM, Smithsonian Institution, GMAP and American Museum of Natural History *http://geonode.themimu.info/layers/geonode%3Amyanmar_forestcoverchange See the recommended style file (.txt) in the documents section for associating raster values and creating the legend. Original dataset title: Kachin State and Sagaing Region 2002-2014 Forest Cover Change