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UBC Theses and Dissertations

Evaluation of Landsat thematic mapper data for reforestation assessment Bansal, Arun Kumar


Forests are important natural resources of Canada. Their renewal has been recognized to be important for continued wood supply and for other benefits. Consequently, the major emphasis of forest management activities focuses upon restocking clearcut forest lands. Effective planning and successful implementation of reforestation programs require efficient techniques for obtaining timely and accurate information regarding restocking status over cutover forest lands. In this thesis the potential of Landsat thematic mapper (TM) data for monitoring reforesting clearcuts was investigated. Landsat-5 TM data covering clearcut forest lands reforesting with lodgepole pine (Pinus contorta Dougl.) were analyzed. To assess spectral separability of various restocking classes and classifying reforestation areas according to their stocking status multivariate distance measures were employed to select the optimum three band subset from six reflective TM bands. Three commonly used vegetation indices, namely the ratio vegetation index, the normalized difference vegetation index, and the infrared index, were also studied for quantitative assessment of vegetation. The main conclusion of the study is that TM bands 3, 4, and 5 are the best for discriminating various restocking classes. The classification accuracy was estimated to be approximately 90 percent. The infrared index appears to be the most suitable vegetation index for quantitative assessment of reforestation.

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