Vegetation characteristics and underlying topography from interferometric radar

Abstract

This paper formulates and demonstrates methods for extracting vegetation characteristics and underlying ground surface topography from interferometric synthetic aperture radar (INSAR) data. The electromagnetic scattering and radar processing, which produce the INSAR observations, are modeled, vegetation and topographic parameters are identified for estimation, the parameter errors are assessed in terms of INSAR instrumental performance, and the parameter estimation is demonstrated on INSAR data and compared to ground truth. The fundamental observations from which vegetation and surface topographic parameters are estimated are (1) the cross-correlation amplitude, (2) the cross-correlation phase, and (3) the synthetic aperture radar (SAR) backscattered power. A calculation based on scattering from vegetation treated as a random medium, including the effects of refractivity and absorption in the vegetation, yields expressions for the complex cross correlation and backscattered power in terms of vegetation characteristics. These expressions lead to the identification of a minimal set of four parameters describing the vegetation and surface topography: (1) the vegetation layer depth, (2) the vegetation extinction coefficient (power loss per unit length), (3) a parameter involving the product of the average backscattering amplitude and scatterer number density, and (4) the height of the underlying ground surface. The accuracy of vegetation and ground surface parameters, as a function of INSAR observation accuracy, is evaluated for aircraft INSAR, which is characterized by a 2.5-m baseline, an altitude of about 8 km, and a wavelength of 5.6 cm. It is found that for •0.5% accuracy in the INSAR normalized cross-correlation amplitude and •5 ø accuracy in the interferometric phase, few-meter vegetation layer depths and ground surface heights can be determined from INSAR for many types of vegetation layers. With the same observational accuracies, extinction coefficients can be estimated at the 0.1-dB/m level. Because the number of parameters exceeds the number of observations for current INSAR data sets, external extinction coefficient data are used to demonstrate the estimation of the vegetation layer depth and ground surface height from INSAR data taken at the Bonanza Creek Experimental Forest in Alaska. This demonstration shows approximately 5-m average ground truth agreement for vegetation layer depths and ground-surface heights, with a clear dependence of error on stand height. These errors suggest refinements in INSAR data acquisition and analysis techniques which will potentially yield few-meter accuracies. The information in the INSAR parameters is applicable to a variety of ecological modeling issues including the successional modeling of forested ecosystems.

Vertical structure of vegetated land surfaces from interferometric and polarimetric radar

“…Treuhaft et al [1996] by introducing a ground surface and explicitly accounting for the vector nature of the fields. After deriving a general expression for the cross correlation, the specific model cross correlations will be Table 2 is a list of observations and the parameters on which they depend for each model scenario.…”

Model-Based Biomass Estimation of a Hemi-Boreal Forest from Multitemporal TanDEM-X Acquisitions

“…For this, single polarized (VV), bistatic interferometric TanDEM-X data acquired between June 2011 and August 2012 over Remningstorp, a hemi-boreal test site situated in southern Sweden, were used. Three InSAR models were employed and evaluated: Interferometric Water Cloud Model (IWCM) [11][12][13][14], Random Volume over Ground model (RVoG) [15][16][17] and a simple model based on the penetration depth (PD) of X-band microwaves. As reference, biomass estimates derived from LiDAR scanning data acquired during the BioSAR 2010 campaign [18,19], performed within the BIOMASS phase-A study [20] were used.…”

Characterizing 3D vegetation structure from space: Mission requirements

“…In just the last two decades, advances in the use of interferometric radar 520 techniques utilizing multiple L or C-band pol-SAR (pol-InSAR) images acquired nearly 521 simultaneously at two or more view geometries from aircraft have demonstrated a 522 capability to map the 3D structure of forests (Treuhaft et al 1996, Cloude and 523 Papathanassiou 1998, Treuhaft and Siqueira 2000, Papathanassiou and Cloude 2001, 524 Neef et al 2005. L-band pol-inSAR has also shown promise to map structure in higher 525 density regions of the tropics (Hajnsek et al 2009).…”