- Title
- Tanintharyi Region Land Cover - March 2016 (Improved)
- License
- Creative Commons By Attribution (CC-BY)
-
+ You are free to:
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+ Share — copy and redistribute the material in any medium or format
+ Adapt — remix, transform, and build upon the material
+ for any purpose, even commercially.
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+ The licensor cannot revoke these freedoms as long as you follow the license terms.
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+ Under the following terms:
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+ Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
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+ No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
+ For more info see https://creativecommons.org/licenses/by/4.0/legalcode. - Abstract
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 hum...
- Revision Date
- Dec. 13, 2016, 12:43 a.m.
- Type
- Raster Data
- Keywords
- tanintharyi
- Owner
- mimu
- Maintenance Frequency
- There Are No Plans To Update The Data
- Restrictions
- You are free: - To Share: To copy, distribute and use the database. - To Create: To produce works from the database. - To Adapt: To modify, transform and build upon the database. As long as you: - Attribute: You must attribute any public use of the database, or works produced from the database. For any use or redistribution of the database, or works produced from it, you must make clear to others the license of the database and keep intact any notices on the original database. 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.
- Edition
- Manually Improved
- Purpose
Land Cover Classification:
1 - Water (ocean, rivers, lakes, reservoirs, flooded areas)
2 - Degraded Mangrove Forest (mangrove cover <80%; evi...- Language
- English
- Data Quality
- Mean per-class producer's accuracy estimated at 76.8% based on validation dataset. Forest/non-forest accuracy estimated at 95.5%. See original publication for further details. This REVISED version of the dataset incorporates a number of manual edits with unknown effects on map accuracy.
- Supplemental Information
No information provided
- Spatial Representation Type
- grid data is used to represent geographic data
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