Modeling of Polarimetric SAR and InSAR for Forest Structure Estimation

Paul Robert Siqueira, University of Massachusetts, siqueira@ecs.umass.edu (Presenter)
Dustin Lagoy, University of Massachusetts, dustin.lagoy@gmail.com

Use of remote sensing for making quantitative estimates of vegetation structure or other ecological parameters of interest is a difficult process, in part, because there are few remote sensing measurements that are direct measurements of the quantities of interest. For instance, while lidar might provide a direct measurement of vegetation height, the relationship between the tree height, or other waveform-derived parameters, to something like Biomass, or equivalent carbon content, is an empirical one, likely to change depending on variations in regional land cover types, growing conditions and wood densities. A similar situation exists for the use of microwave (SAR and/or InSAR) measurements.

In this poster, we present an approach under development to make best-use out of vegetation growth simulation algorithms (such as provided by USFS or the ED2 model), to create ecologically informed versions of potential vegetation states for a region and to use available remote sensing to determine which versions of the ecologic model (based on possible development trajectories) are most likely for the current state of the region under study. By following this approach, combination of disparate data sets, such as lidar and radar, is achieved through the ecologic model. Further, physical characteristics, such as biomass, can be directly determined from the ecological model, thereby avoiding the empirical nature of how many of these measures are often made.

Presentation Type:  Poster

Session:  General Contributions   (Tue 4:35 PM)

Associated Project(s): 

• Siqueira, Paul: Modeling and Evaluation of Polarimetric SAR and InSAR for Forest Structure Estimation ...details

Poster Location ID: 223