VALUE OF LANDSATTM DATA FOR MANAGEMENT OF UPCOUNTRY PLANTATIONS IN SRI LANKA

Abstract

This study investigates the potential use of Landsat TM data for the discrimination of forestcover types and to find whether relationship exists with forest stand parameters. In the studydifferent Landsat TM data bands (except thennaI band) and image transformations were used.The different image transformations used in the study are Vegetation Index (VI), StructuralIndex (SI), Normalized Vegetation Index (NDVI), Tasselled Cap transformation for greenessand first principal component analysis with variance of 82.4 percentage. Multispectralclassification using the ILWIS GIS was used in the study. Multispectral classification is aninformation extraction process which analyses the spectral signatures ( spectral reflectancecharacteristics) and then assigns pixels to categories based on similar characterisics. From theboxed classification ( parellelpiped classification ) and the maximum-likelihood classificationapplied it was found that maximum-likelihood classification gave the best results. Studiesindicate that the most suitable combinations of bands to discriminate most of the cover types is acombination ofTM 2,3,4,5. However, this composite image cannot be be used to discriminatedifferent cover types especially in shadow areas due to variable illumination. TIle confusionmatrix indicated an overall accuracy of 93 % which is higher than that recorded for theclassification offorest classes of the entire country.

From the different TM bands and image transformations used TM 5 and first principalcomponent gave the highest relationship. Poor relationship was recorded for the vegetationindices. The studies indicate that forest stand parameters can be estimated up to a certain criticallimit beyond which spectral saturation seems to be a limiting factor.