Knowledge of the global biomass distribution is essential in monitoring the carbon cycle budget and the climate change. In addition to limited field inventory data, researchers have been developing remote sensing techniques (e.g., LiDAR, SAR backscatter, InSAR phase and/or correlation magnitude) to derive biomass maps. Most of the techniques seek for empirical relationships between biomass and remote sensing measures; however, lack of a direct physical interpretation of the measurement constrains the utility and understanding of remote sensing data sensitivity to the forest characteristics of interest. In this paper, we explore the use of InSAR correlation magnitude to invert for the tree height through use of a physical scattering model . The inversion algorithm, along with the estimates of the tree heights, will be cross-compared with itself over our test area: the Injune region (ILCP) in Australia.
|Journal||International Geoscience and Remote Sensing Symposium|
|Publication status||Published - 12 Nov 2012|
- tree heights