Abstract
Abstract. Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.
Highlights
Forest ecosystems play an important role in global change on the earth
A various group of approaches aims at the physical extraction of forest parameters that can be related to biomass via so-called allometric equations, such as crown size estimations, stem counting, diameter at breast height (DBH) or height estimations
There have been plenty of researches on the retrieval of forest height by single baseline PolInSAR
Summary
Forest ecosystems play an important role in global change on the earth. Current concerns for ecosystem functioning require accurate biomass estimation and examination of its dynamics. Most direct biomass estimations by means of remote sensing make use of regression because the complexity of forest structure These regressions are often only accurate for a certain region or forest type. A various group of approaches aims at the physical extraction of forest parameters that can be related to biomass via so-called allometric equations, such as crown size estimations, stem counting, diameter at breast height (DBH) or height estimations. These methods focus on forest height to estimate biomass (Boscolo, Powell et al 2000)
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