Height Estimation of Boreal Forest: Interferometric Model-Based Inversion at L- and X-Band Versus HUTSCAT Profiling Scatterometer

Praks, Jaan; Kugler, Florian; Papathanassiou, K.; Hajnsek, Irena; Hallikainen, M.

doi:10.1109/lgrs.2007.898083

Cited by 83 publications

(46 citation statements)

References 12 publications

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“…To overcome this difficulty and obtain height estimates using dual-polarization (dual-pol) or even single-polarization (single-pol) InSAR data [31,34], additional assumptions, auxiliary data or further regularization are needed. Including the auxiliary Digital Terrain Model (DTM) representing ground surface, fixing the phase center height location, discarding the ground scattering contribution and fixing the forest extinction to a predefined value are among the commonly-used solutions [31,33,34,40].…”

Section: Rvog Coherence Modelmentioning

confidence: 99%

Interferometric SAR Coherence Models for Characterization of Hemiboreal Forests Using TanDEM-X Data

et al. 2016

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Abstract:In this study, four models describing the interferometric coherence of the forest vegetation layer are proposed and compared with the TanDEM-X data. Our focus is on developing tools for hemiboreal forest height estimation from single-pol interferometric SAR measurements, suitable for wide area forest mapping with limited a priori information. The multi-temporal set of 19 TanDEM-X interferometric pairs and the 90th percentile forest height maps are derived from Airborne LiDAR Scanning (ALS), covering an area of 2211 ha of forests over Estonia. Three semi-empirical models along with the Random Volume over Ground (RVoG) model are examined for applicable parameter ranges and model performance under various conditions for over 3000 forest stands. This study shows that all four models performed well in describing the relationship between forest height and interferometric coherence. Use of an advanced model with multiple parameters is not always justified when modeling the volume decorrelation in the boreal and hemiboreal forests. The proposed set of semi-empirical models, show higher robustness compared to a more advanced RVoG model under a range of seasonal and environmental conditions during data acquisition. We also examine the dynamic range of parameters that different models can take and propose optimal conditions for forest stand height inversion for operationally-feasible scenarios.

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Section: Rvog Coherence Modelmentioning

confidence: 99%

Interferometric SAR Coherence Models for Characterization of Hemiboreal Forests Using TanDEM-X Data

et al. 2016

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“…The forested areas have been considered in previous investigations for the retrieval of forest biophysical parameters using SAR remote sensing techniques [6,[32][33][34][35][36][37]. During the past 15 years, much effort has been made in regard to the forestry applications using PolInSAR (Polarimetric Interferometry SAR) techniques [38][39][40][41]. However, in this study we solely concentrate on the polarimetric information.…”

Section: Motivation and Scopementioning

confidence: 99%

Polarimetric Parameters for Growing Stock Volume Estimation Using ALOS PALSAR L-Band Data over Siberian Forests

et al. 2013

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Abstract:In order to assess the potentiality of ALOS L-band fully polarimetric radar data for forestry applications, we investigated a four-component decomposition method to characterize the polarization response of Siberian forest. The decomposition powers of surface scattering, double-bounce and volume scattering, derived with and without rotation of coherency matrix, were compared with Growing Stock Volume (GSV). To compensate for topographic effects an adaptive rotation of the coherency matrix was accomplished. After the rotation, the correlation between GSV and double-bounce increased significantly. Volume scattering remained same and the surface scattering power decreased slightly. The volume scattering power and double-bounce power increased as the GSV increased, whereas the surface scattering power decreased. In sparse forest, at unfrozen conditions the surface scattering was higher than volume scattering, while volume scattering was dominant in dense forest. The scenario was different at frozen conditions for dense forest where the surface scattering was higher than volume scattering. Moreover, a slight impact of tree species on polarimetric decomposition powers has been observed. Larch was differed from aspen, birch and pine by +2 dB surface scattering power and also by −1.5 dB and −1.2 dB volume scattering power and double-bounce scattering power respectively at unfrozen conditions. OPEN ACCESSRemote Sens. 2013, 5 5726

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“…Therefore, the truncation parameter k which determines the preserved large singular values and truncated small singular values is a key factor for TSVD to reduce the MSE. The method that is commonly used for the determination of the truncation parameter is related to the condition number, i.e., λ 1 /λ i , as defined in Equation (15). If the condition number is larger than the given upper limit, the singular value λ i should be truncated [28][29][30].…”

Section: Estimation Of Pure Volume Coherence From the Complex Interfementioning

confidence: 99%

“…The complex interferometric coherence of the observed PolInSAR data has been related to the vertical distribution of the vegetation scattering [10][11][12]. In a number of PolInSAR campaigns, the random volume over ground (RVoG) model [6,10] has been used to extract vegetation height from the complex interferometric coherence [15][16][17]. The RVoG model is a physical PolInSAR model that integrates the complex coherence and the biophysical parameters.…”

Section: Introductionmentioning

confidence: 99%

A TSVD-Based Method for Forest Height Inversion from Single-Baseline PolInSAR Data

Lin

Zhu

et al. 2017

Applied Sciences

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Abstract:The random volume over ground (RVoG) model associates vegetation vertical structure parameters with multiple complex interferometric coherence observables. In this paper, on the basis of the RVoG model, a truncated singular value decomposition (TSVD)-based method is proposed for forest height inversion from single-baseline polarimetric interferometric synthetic aperture radar (PolInSAR) data. In addition, in order to improve the applicability of TSVD for this issue, a new truncation method is proposed for TSVD. Differing from the traditional three-stage method, the TSVD-based inversion method estimates the pure volume coherence directly from the complex interferometric coherence, and estimates the forest height from the estimated pure volume coherence with a least-squares method. As a result, the TSVD-based method can adjust the contributions of the polarizations in the estimation of the model parameters and avoid the null ground-to-volume ratio assumption. The simulated experiments undertaken in this study confirmed that the TSVD-based method performs better than the three-stage method in forest height inversion. The TSVD-based method was also applied to E-SAR P-band data acquired over the Krycklan Catchment, Sweden, which is covered with mixed pine forest. The results showed that the TSVD-based method improves the root-mean-square error by 48.6% when compared to the three-stage method, which further validates the performance of the TSVD-based method.

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Height Estimation of Boreal Forest: Interferometric Model-Based Inversion at L- and X-Band Versus HUTSCAT Profiling Scatterometer

Cited by 83 publications

References 12 publications

Interferometric SAR Coherence Models for Characterization of Hemiboreal Forests Using TanDEM-X Data

Interferometric SAR Coherence Models for Characterization of Hemiboreal Forests Using TanDEM-X Data

Polarimetric Parameters for Growing Stock Volume Estimation Using ALOS PALSAR L-Band Data over Siberian Forests

A TSVD-Based Method for Forest Height Inversion from Single-Baseline PolInSAR Data

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