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In the context of developing a practicable and cost effective method for obtaining a country’s forest area by remote sensing, the computer processing of NOAA AVHRR HRPT data covering Liberia was investigated. The only cloud-free scene then recorded turned out to be severely and unevenly affected by atmospheric haze. To mitigate the effects of this, the country was divided into six areas (strata) of more uniform haze conditions. Pixel DN values were obtained for forest and adjoining formations on transects within each stratum, for the first four AVHRR channels and three transforms: NDVI (2-1/2 + 1), IND3 (3-2/3 + 2), IND4(4-2/4 + 2). After analyzing the transects and comparing them with the available reference data (a mixture of large scale colour composite Landsat TM and MSS images for 1989 and 1986 respectively), channels 2, 3, 4 and IND3 were retained for processing. This was done by applying three methods to each stratum - thresholding, maximum likelihood classification using clustering signatures (hybrid), m.l.c. using training area signatures - and directed at separating the 5 main classes distinguishable on the Landsat images: Closed forest, Disturbed forest, Shifting cultivation and regrowth, Cultivation and Other.
