Quantification of the above ground carbon stock (AGC) is important in sustainable forest management
and policy advice on climate change mitigation. Remote sensing when combined with few ground
collected data has the potential of improving forest resource assessment even though this opportunity
has not well been utilised. In this study, we mapped AGC through combination of ground survey data
collected from 51 permanent sapling plots with Normalized Difference Vegetation Index (NDVI)
derived from Landsat 5 Thematic Mapper image. Linkage of the two data sources was made during a
training stage of supervised classification. The overall classification accuracy was 98%, suggesting
that reliable estimate of AGC for a large area can be made through combination of medium resolution
satellite imagery and few samples from the ground.
Author (s) Details
Mr. Lesika Basalumi
Department of Ecosystems and Conservation, Sokoine University of Agriculture, Morogoro, Tanzania and Department of Forestry and Range Resources, Gaborone, Botswana.
Charles Joseph Kilawe
Department of Ecosystems and Conservation, Sokoine University of Agriculture, Morogoro, Tanzania.
Ernest William Mauya
Forest Engineering and Wood Science, Sokoine University of Agriculture, Morogoro, Tanzania.
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