Aboveground biomass estimation of tropical forest from Envisat advanced synthetic aperture radar data using modeling approach

Kumar, Shashi; Pandey, Uttara; Kushwaha, S. P. S.; Chatterjee, R. S.; Bijker, W.

doi:10.1117/1.jrs.6.063588

Cited by 47 publications

(21 citation statements)

References 9 publications

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“…The model with fused-image band-8 input has the highest prediction accuracy (R 2 = 0.79, RMSE = 22.82 g m −2 ), which is more accurate in biomass prediction with less uncertainty in an area with a low vegetation cover. This can be ascribed to the ability of that model to accurately detect nonvegetated areas (which are smooth for radar waves) and with a low backscatter coefficient compared to the vegetated areas [48]. The Sentinel-1 C-band SAR is the preferred dataset for biomass analysis in low-biomass sites such as grasslands and forest regeneration sites.…”

Section: The Accuracy and Uncertainty Of The Agb Estimation Modelmentioning

confidence: 99%

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

Bao

et al. 2019

Remote Sensing

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The surface mining activities in grassland and rangeland zones directly affect the livestock production, forage quality, and regional grassland resources. Mine rehabilitation is necessary for accelerating the recovery of the grassland ecosystem. In this work, we investigate the integration of data obtained via a synthetic aperture radar (Sentinel-1 SAR) with data obtained by optical remote sensing (Worldview-3, WV-3) in order to monitor the conditions of a vegetation area rehabilitated after coal mining in North China. The above-ground biomass (AGB) is used as an indicator of the rehabilitated vegetation conditions and the success of mine rehabilitation. The wavelet principal component analysis is used for the fusion of the WV-3 and Sentinel-1 SAR images. Furthermore, a multiple linear regression model is applied based on the relationship between the remote sensing features and the AGB field measurements. Our results show that WV-3 enhanced vegetation indices (EVI), mean texture from band8 (near infrared band2, NIR2), the SAR vertical and horizon (VH) polarization, and band 8 (NIR2) from the fused image have higher correlation coefficient value with the field-measured AGB. The proposed AGB estimation model combining WV-3 and Sentinel 1A SAR imagery yields higher model accuracy (R 2 = 0.79 and RMSE = 22.82 g/m 2 ) compared to that obtained with any of the two datasets only. Besides improving AGB estimation, the proposed model can also reduce the uncertainty range by 7 g m −2 on average. These results demonstrate the potential of new multispectral high-resolution datasets, such as Sentinel-1 SAR and Worldview-3, in providing timely and accurate AGB estimation for mine rehabilitation planning and management.

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Section: The Accuracy and Uncertainty Of The Agb Estimation Modelmentioning

confidence: 99%

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

Bao

et al. 2019

Remote Sensing

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“…Forest vertical structure is regarded as the major element for forest biomass assessment. Various SAR processing techniques have been widely exploited and implemented to retrieve forest height 3 and its biomass 4,5 . InSAR (SAR Interferometry) takes into account the phase difference between the two SAR images which estimate the average height of all backscattering contribution and hence does not serve the purpose 6,7 .…”

Section: Introductionmentioning

confidence: 99%

PolInSAR tomography for vertical profile retrieval of forest vegetation using spaceborne SAR data

et al. 2016

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Forest height plays a crucial role to investigate the bio-physical parameters of forest and the terrestrial carbon. PolInSAR based inversion modeling has been successfully implemented on airborne and spaceborne SAR data. SAR tomography, which is an extension of cross-track interferometric processing is a recent approach to separate scatterers in cross range direction, thus generates its vertical profile. This study highlighted the potential of tomographic processing of fully polarimetric Radarsat-2 SAR system to retrieve backscatter power at different height levels. Eucalyptus patch of Haldwani forest division of Uttarakhand state in India was chosen as the test site. Since SAR tomography is a spectral estimation problem, Fourier transform and beamforming based spectral estimations were applied on the dataset to obtain their vertical profiles. Fourier severely suffered from high sidelobes which was drastically reduced by implementing beamforming by taking into account the multilooking effect at the expense of radiometric accuracy. Backscattered power values were found to be different at different height levels of the forest vegetation. Vertical profile for Fourier as well as beamforming were also retrieved.

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“…Previous studies for AGB and stem volume retrieval from SAR-backscatter-based WCM used single-polarized or dual-polarized data to retrieve the backscatter contribution of forest vegetation and the ground surface as model parameters [25,34,35]. Estimation of backscatter contribution due to forest vegetation and the ground surface was mathematically rigorous and less reliable due to the use of single or dual-pol SAR data [36][37][38][39]. The measurement of model parameters has shown dependency on field-measured data to get a reliable output through a modeling approach.…”

Section: Introductionmentioning

confidence: 99%

PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation

et al. 2019

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Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR resolution cell. A methodology for a PolSAR-based extended water cloud model (EWCM) has been proposed and evaluated in this study. Fully polarimetric phased array type L-band synthetic aperture radar (PALSAR) data of advanced land observing satellite (ALOS) was used in this study for forest aboveground biomass (AGB) retrieval of Dudhwa National Park, India. The shift in the polarization orientation angle (POA) is a major problem that affects the PolSAR-based scattering information. The two sources of POA shift are Faraday rotation angle (FRA) and structural properties of the scatterer. Analysis was carried out to explore the effect of FRA in the SAR data. Deorientation of PolSAR data was implemented to minimize any ambiguity in the scattering retrieval of model-based decomposition. After POA compensation of the coherency matrix, a decrease in the power of volume scattering elements was observed for the forest patches. This study proposed a framework to extend the water cloud model for AGB retrieval. The proposed PolSAR-based EWCM showed less dependency on field data for model parameters retrieval. The PolSAR-based scattering was used as input model parameters to derive AGB for the forest area. Regression between PolSAR-decomposition-based volume scattering and AGB was performed. Without deorientation of the PolSAR coherency matrix, EWCM showed a modeled AGB of 92.90 t ha−1, and a 0.36 R2 was recorded through linear regression between the field-measured AGB and the modeled output. After deorientation of the PolSAR data, an increased R2 (0.78) with lower RMSE (59.77 t ha−1) was obtained from EWCM. The study proves the potential of a PolSAR-based semiempirical model for forest AGB retrieval. This study strongly recommends the POA compensation of the coherency matrix for PolSAR-scattering-based semiempirical modeling for forest AGB retrieval.

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Aboveground biomass estimation of tropical forest from Envisat advanced synthetic aperture radar data using modeling approach

Cited by 47 publications

References 9 publications

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

PolInSAR tomography for vertical profile retrieval of forest vegetation using spaceborne SAR data

PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation

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