Estimation of Above Ground Forest Biomass in a Tiger Habitat of the Western Nepal using ALOS Data and Field Inventory

The ALOS/PALSAR data were processed in order to derive backscatter coefficient in decibel values. The following processing steps were carried out including terrain correction, co-registration, radiometric calibration and adaptive filtering. With the use of 90m resolution of DEM (Digital Elevation Model) from SRTM (Shuttle Radar Topography Mission), terrain correction was done in ASF MapReady software to reduce the effects of the illuminated target area caused by topography and SAR image geometry. For multi-temporal processing and analysis, co-registration was performed in order to align the images on pixel level and remove shifts between images on different dates. The relationships between the resulted radar backscatter values and the AGB values from field measurement were analyzed over a grid with a cell size of 9 by 9 pixels (approximately 1 hectare), to match the scale of the regression model. Then, a non-linear regression approach was used to develop a biomass model. Finally, a biomass map of the study area was produced using the best-fit biomass model. The results successfully produced a biomass map, however, like any other similar research using RADAR backscatter coefficient of L-band, it has constraint in terms of biomass saturation at around 100 t/ha. 
An attempt to extract information on forest tree height from ALOS/PRISM triplet images was made to produce a tree height map. However, an important consideration here would be vertical as well as horizontal accuracy of the elevations. A profile analysis shows that there is good agreement between elevations derived from ALOS/PRISM and DEM from the Survey department in open areas (approximately within 5m accuracy). To incorporate the height information into the biomass model, further research is needed to improve the accuracy.