Title
Malawi Land Cover 2000 Scheme I
License
Public Domain (PD)
+ Works in the public domain may be used freely without the permission of the former copyright owner.

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Abstract

Land Cover maps were developed for Green Houses gases Inventories to provide baseline data for Land use, land-use change and forestry (LULUCF)sector.

The coverage for the Land Cover maps is NINE Eastern and Southern Africa (ESA) countries namely: Ethiopia, Botswana, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, and Zambia.

The Land Cover maps have been developed from LandSat Imagery (30m by 30m) resolution using supervised classification. Image interpretation was done...

Publication Date
March 7, 2015, 2:06 p.m.
Type
Raster Data
Keywords
geo-climate geo-agriculture geossNoMonetaryCharge servir-ast geo-ecosystem servircat geo-biodiversity geossDataCore rcmrd-servir
Category
Environment
environmental resources, protection and conservation. Examples: environmental pollution, waste storage and treatment, environmental impact assessment, monitoring environmental risk, nature reserves, landscape
Regions
Malawi
Owner
rcmrd
More info
-
Maintenance Frequency
Data Is Updated As Deemed Necessary
Restrictions
The SERVIR Project, NASA, USAID and RCMRD make no express or implied warranty of this data as to the merchantability or fitness for a particular purpose. Neither the US Government nor RCMRD shall be liable for special, consequential or incidental damages attributed to this data.
Purpose

Support ESA Country teams in developing and implementing land cover mapping efforts for Agriculture, Forestry and Land Use (AFOLU) sector in the developme...

Language
English
Data Quality
This land cover products were generated from LandSat thematic mapper (LandSat 5) data using supervised classification method. It involves the generation of training areas and then use maximum likelihood classification method to develop the land cover products. Other post classification procedures such as filtering, pixel/cell editing, density slicing etc. are used to refined the classification to generate final products. Accuracy assessment is conducted using actual field data and point interpretation from LandSat imagery which are randomly generated. The two most commonly used indices for assessing the map accuracy were the Overall accuracy and the KAPPA coefficient. The accuracy assessment results obtained for Malawi 2000 Scheme I were as follows: Overall Accuracy = 84.8789%, Kappa Coefficient = 0.7945.
Supplemental Information

Users are advised to read and understand the metadata before access and use of the resources.

Spatial Representation Type
grid data is used to represent geographic data
Attribute Name Label Description Range Average Median Standard Deviation
PALETTE_INDEX NA

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