Introductory Digital Image Processing: A Remote Sensing Perspective
Introductory Digital Image Processing: A Remote Sensing Perspective
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Indian Earth Observation Satellite Cartosat-1 data were evaluated for the estimation of biophysical variables, including as tree height, crown diameter, canopy density and canopy gap, that are crucial for the estimation of stand volume, biomass and generation of site index (an indicator of site quality of growing stock). Investigations were carried out at a site covering the major dominant forest species grown in India. Cartosat-1 stereo data were analysed in conjunction with differential global positioning system (DGPS) measurements to generate a digital elevation model (DEM) and an orthoimage, which were used to estimate the biophysical variables. Analysis using grey-level co-occurrence texture measures was performed for separation of forest species, homogeneity of the classes of forest stands, stratification and measurement of crown area, canopy gap and stand density. Field measurements of tree height, diameter at breast height (DBH), stand density, age and crown diameter were conducted for each stand. Empirical models for the estimation of DBH were developed and validated with Cartosat-1-derived height and crown diameter. Measured and estimated values were found to be in close proximity to each other. A local contrast co-occurrence measure (contrast, mean and variance) was suitable for the estimation of average crown diameter, stand density and canopy gap area for each forest stand class. The texture image provided information on structural attributes (i.e. stand density, crown diameter and canopy gap of the forest tree stands). The results presented in this study show that the Cartosat-1-derived DEM and orthoimage have potential for the estimation of stem volume, growing stock conditions, and biomass and site index for important timber species.