Abstract
This work introduces an innovative radiometric terrain correction algorithm using PolInSAR imagery for improving forest vertical structure parameter estimation. The variance of radar backscattering caused by terrain undulation has been considered in this research by exploiting an iteration optimization procedure to improve the backscattering estimation for a Synthetic Aperture Radar (SAR) image. To eliminate the variance of backscatter coefficients caused by the local incident angle, a radiometric normalization algorithm has been investigated to compensate the influence of terrain on backscattering values, which hinders forest vertical parameter estimation. In vertical parameter estimation, species diversity and the spatial distribution of different vegetation have been modeled. Then, a combination of Fisher’s Alpha-Diversity model parameter estimation and the three-stage inversion method was designed for the vertical structure parameter. To demonstrate the efficiency of the proposed method in forest height estimation, the classical phase difference and three-stage inversion approach have been performed for the purpose of comparison. The proposed algorithm is tested on ALOS PALSAR (Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 (Radio Direction and Range Satellite 2) data sets for the Great Xing’an Mountain area and BioSAR (Biomass Synthetic Aperture Radar) 2007 data sets for the Remningstorp area. Height estimation results have also been validated using in-situ measurements. Experiments indicate the proposed method has the ability to compensate the influence of terrain undulation and improving the accuracy of forest vertical structure parameter estimation.
Highlights
Forest parameters, in particular vertical structure parameters, are the prerequisite of dynamic analysis of the carbon cycle and water cycle [1,2], which play an important role in research regarding environmental protection and the global climate system [3]
This paper presents a radiometric terrain correction method and forest vertical structure parameter estimation approach in PolInSAR imagery
In the forest height estimation procedure, the species diversity factor is exploited in the inversion model to describe the spatial distribution as well as the scattering variance of different species
Summary
In particular vertical structure parameters, are the prerequisite of dynamic analysis of the carbon cycle and water cycle [1,2], which play an important role in research regarding environmental protection and the global climate system [3]. Forest height is one of the most essential parameters of forest information. Terrain variance poses a challenge for parameter inversion based on PolInSAR imagery because undulation may make the vegetation backscatters more complex. Polarimetric Interferometry SAR (PolInSAR) remote sensing technology has potential in forest parameter estimation since it has sufficient penetration ability to extract the ground and canopy information of the forest. Large-scale and long time series observation of the scene can be provided to model the dynamical information of the forest area. Forest height estimation is a hot topic in PolInSAR remote sensing
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