Abstract
This paper investigates the potential of the time-frequency optimization on the basis of the sublook decomposition for forest height estimation. The optimization is deemed to be capable of extracting a relatively accurate volume contribution when P-band polarimetric interferometric synthetic aperture radar (Pol-InSAR) systems are adopted to observe forest-covered areas. The highest and the lowest phase centers acquired by the time-frequency optimization modify the conventional three-stage inversion process. This paper presents, for the first time, a performance assessment of the time-frequency optimization on P-band Pol-InSAR data over boreal forests. Simultaneously, to alleviate the model inversion errors caused by topographic fluctuations, forest height is estimated based on the sloped Random Volume over Ground (S-RVoG) model in which the incidence angle is corrected with the terrain slope. The E-SAR P-band Pol-InSAR data acquired during the BIOSAR 2008 campaign in Northern Sweden is utilized to evaluate the performance of the proposed method. From the results of the forest height estimation preprocessed with time-frequency optimization, the root mean square error (RMSE) of Random Volume over Ground (RVoG) and S-RVoG model on negative slope are 5.09 m and 4.71 m, respectively. It is concluded that the time-frequency processing and negative terrain slope compensation improve the inversion performance by 41 . 49 % and 11 . 96 % , respectively.
Highlights
On account of the significant penetration of P-band polarimetric interferometric synthetic aperture radar (Pol-InSAR) systems, all polarimetric channels contain a non-ignorable ground contribution [1,2,3,4,5], generally leading to an underestimation of forest height in view of the Random Volume over Ground (RVoG) model [3,6]
(3) Forest height estimation: Assuming that the ground-to-volume ratio (GVR) of a polarimetric channel is sufficiently low, in accordance with Equation (4), the volume coherence can be expressed as e−jφ0 γPDHigh, and the forest height is extracted by a two-dimensional look-up table set up in the light of Equation (5)
Since the underlying topography over the forest area commonly takes on certain fluctuations, the forest height inversion on the basis of the traditional RVoG model under the flat ground hypothesis reckons to be susceptible to the terrain slope [6,27,28,29,30,31,32]
Summary
On account of the significant penetration of P-band polarimetric interferometric synthetic aperture radar (Pol-InSAR) systems, all polarimetric channels contain a non-ignorable ground contribution [1,2,3,4,5], generally leading to an underestimation of forest height in view of the Random Volume over Ground (RVoG) model [3,6]. To overcome the above limitations, the time-frequency optimization was developed as a method independent of the above two strategies, allowing a separation of the canopy and ground contributions with single-baseline Pol-InSAR data [2]. The ground coherence is not constrained to equal one, as the lowest phase estimated by time-frequency optimization is directly regarded as being related to the ground level contribution This processing yields a highly accurate forest height inversion for the RAMSES data [2]. With the aim of obtaining a relatively precise volume coherence and simultaneously retaining the advantages of the single-baseline for inversion efficiency, this paper took advantage of the time-frequency optimization to separate ground and canopy contributions.
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