Remote Sensing for Timber Volume Estimation

This study compares the remote sensing data having different spatial resolutions to estimate the timber volume of forest stands. The study comprises mainly the stratification of forest from the input of classified satellite data, measurement of timber volume in the field, extraction of the pixel information for the plots, preparation of a continuous volume map and its comparison among different outputs. The Preprocessing includes layer stacking, image registration, PAN sharpening and classification of the images, which results as forest type maps. Post processing includes layover of sample plots over the image, extraction of pixel information for all sample plots and preparation of continuous volume maps from all sets of data. The plot-wise timber volume, extracted pixel information; stratification information and the geographical information have been tabulated and were analyzed with regression analysis to find the best-fit regression equations in all sets of data. Later multiplied by corresponding best-fit linear regression equations to prepare continuous volume maps from different satellite data.

Autorentext

Mr. Shrestha has earned M.Sc. Geoinformatics degree in 2003. Currently, He has commenced for his PhD in Kathmandu University. He is also associated with International Center for Integrated Mountain Development (ICIMOD). His core area of interest to work is the application of Geoinformatics for forestry with bunch of experiences in the field.