Fusing interferometric radar and laser altimeter data to estimate surface topography and vegetation heights

Interferometric synthetic aperture radar (INSAR) and laser altimeter (LIDAR ) systems are both widely used for mapping topography. INSAR can map extend ed areas but accuracies are limited over vegetated regions, primarily becau se the observations are not measurements of true surface topography. The me asurements correspond to a height above the true surface that depends on bo th the sensor and the vegetation. Conversely, topography from LIDAR is very accurate, but coverage is limited to smaller regions. We demonstrate how t hese technologies can be used synergistically. First, we determine surface elevations and vegetation heights from dual-bas eline INSAR data by inverting an INSAR scattering model. We then combine sp arse LIDAR observations with the INSAR inversion results to improve the est imates of ground elevations and vegetation heights. This is accomplished vi a a multiresolution Kalman Filter that provides both the estimates and a me asure of their uncertainty at each location. Combining data from the two se nsors provides estimates that are more accurate than those obtained from IN SAR alone yet have dense, extensive coverage, which is difficult to obtain with LIDAR. Contributions of this work include 1) combining physical modeli ng with multiscale estimation to accommodate nonlinear measurement-state re lationships and 2) improving estimates of ground elevations and vegetation heights for remote sensing applications.