Speakers
Description
Forest are one of the important part of ecosystem. They play a crucial role in the carbon cycle. A significant amount of the carbon is stored in the form of the forest biomass. These forest cover areas and their stored carbon stock are affected by various natural and anthropogenic factors. In the recent years, due to the various factors such as forest fires, climate change, and forests encroachments there has been a continuous depletion in the forest cover. Hence, in this present scenario regular monitoring of the forest areas is an urgent need. This study focuses on the utilization of PolInSAR and SAR Tomography technique for the forest biophysical parameters retrieval. UAVSAR datasets of AfriSAR mission operating in L-band (1.5 GHz) frequency region with the azimuth resolution of 1.5m* 12m. The used datasets were acquired on the date 15 June 2015 for the Rabi forest area of Gabon in Africa. Using these datasets the coherence optimization was done and the effect of the spatial baseline and interferometric wave number (Kz) was analyzed on the forest estimation. The three-stage inversion technique was implemented for this PolInSAR based height inversion. The appropriate baseline estimation for the correct forest height estimation was done. Also, the SAR Tomography based forest height parameter retrieval was also implemented. The aperture synthesis in the radar cross range direction was able to resolve the forest heights in the vertical direction. The Beamforming and Capon based spectral estimation technique was used for tomographic implementation. The phase calibration was done to remove the interferometric errors. The comparative analysis of the PolInSAR band SAR Tomography based retrieved forest heights was done. The mean forest height retrieved using these technique was 31m. The DSM of the forest area was generated using airborne Land,Vegetation, and Ice Sensor (LVIS) based airborne LIDAR point cloud datasets which was used for the forest hight validation. High accuracy was achieved using SAR Tomography technique estimation. The Capon based technique was giving highest accuracy in the height estimation.
Key words: SAR Remote Sensing, PolInSAR, Forest biophysical parameters retrieval, UAVSAR
Summary
The study uses the Multibaseline PolInSAR and the SAR Tomography based techniques for the retrieval of the forest height estimation. This forest height is one of the important parameter utilized for the total forest biomass. The variation in the net forest biomass can be estimated applying these techniques.
