Bistatic PolInSAR Inversion Modelling for Plant Height Retrieval in a Tropical Forest

Kumar, Shashi; Garg, Rahul; Kushwaha, S. P. S.; Jayawardhana, W. G. N. N.; Agarwal, Sudhir

doi:10.1007/s40010-017-0451-9

Cited by 12 publications

(6 citation statements)

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“…Several studies have been carried out for SAR image-based forest height estimation and most successfully demonstrated airborne systems [42,77,78]. Very few studies have studied spaceborne SAR for forest height retrieval compared to aerial SAR systems [48,55,58]. An automated framework was proposed by Lie et al (2021) to retrieve the vegetation height of a tropical forest using spaceborne TanDEM-X SAR interferometry with 2-3 m accuracy [79].…”

Section: Discussionmentioning

confidence: 99%

“…The Barkot and Thano Forests are covered by dense Sal (Shorea robusta), Khair-Sissoo/Sisham (Acacia catechu Dalbergia sissoo), and mixed miscellaneous forests. Field-collected forest tree heights from 100 locations in the Barkot and Thano Forests [48,58] were used for validation of the PolInSAR-based modelled vegetation height map. Square plots of 12.5 m 2 size were made for the field-based forest height measurement.…”

Section: Study Area and Datasetmentioning

confidence: 99%

“…The TSI model is an extension of the fully polarimetric SAR data-based expression of a two-layer model [66] to estimate the vertical structure of tree species [41]. The PolInSAR-based TSI model is very popular for forest height retrieval [49,58,[67][68][69][70]. The TSI model includes the identification of the ground phase and volumetric coherence of the effective scattering center of forest vegetation for inversion-based forest height retrieval.…”

Section: Three-stage Inversion (Tsi) Modellingmentioning

confidence: 99%

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Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

et al. 2020

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Spaceborne and airborne polarimetric synthetic-aperture radar interferometry (PolInSAR) data have been extensively used for forest parameter retrieval. The PolInSAR models have proven their potential in the accurate measurement of forest vegetation height. Spaceborne monostatic multifrequency data of different SAR missions and the Global Ecosystem Dynamics Investigation (GEDI)-derived forest canopy height map were used in this study for vegetation height retrieval. This study tested the performance of PolInSAR complex coherence-based inversion models for estimating the vegetation height of the forest ranges of Doon Valley, Uttarakhand, India. The inversion-based forest height obtained from the three-stage inversion (TSI) model had higher accuracy than the coherence amplitude inversion (CAI) model-based estimates. The vegetation height values of GEDI-derived canopy height map did not show good relation with field-measured forest height values. It was found that, at several locations, GEDI-derived forest height values underestimated the vegetation height. The statistical analysis of the GEDI-derived estimates with field-measured height showed a high root mean square error (RMSE; 5.82 m) and standard error (SE; 5.33 m) with a very low coefficient of determination (R2; 0.0022). An analysis of the spaceborne-mission-based forest height values suggested that the L-band SAR has great potential in forest height retrieval. TSI-model-based forest height values showed lower p-values, which indicates the significant relation between modelled and field-measured forest height values. A comparison of the results obtained from different SAR systems is discussed, and it is observed that the L-band-based PolInSAR inversion gives the most reliable result with low RMSE (2.87 m) and relatively higher R2 (0.53) for the linear regression analysis between the modelled tree height and the field data. These results indicate that higher wavelength PolInSAR datasets are more suitable for tree canopy height estimation using the PolInSAR inversion technique.

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Section: Discussionmentioning

confidence: 99%

Section: Study Area and Datasetmentioning

confidence: 99%

Section: Three-stage Inversion (Tsi) Modellingmentioning

confidence: 99%

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Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

et al. 2020

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“…Few studies have been reported on height estimation in Indian forests using TanDEM-X PolInSAR data (Khati and Singh, 2015;Khati et al, 2017Khati et al, , 2018Kumar et al, 2017aKumar et al, ,b, 2020. Most of the analysis has been carried out on subtropical forest sites in Uttarakhand, India (Khati et al, 2018;Kumar et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Bhanu Prakash and Kumar (2021) proposed and validated a model based polarimetric decomposition using PolInSAR decorrelation on spaceborne multifrequency SAR datasets (Xband TanDEM-X, C-band Radarsat-2, and L-band PALSAR-2) for the Dehradun region of Uttarakhand, India. Kumar et al (2017a) utilized bistatic PolInSAR data for forest height retrieval in the Barkot and Thano forest ranges in Uttarakhand state, India. The forest test site used in this study, the Shimoga Forest range, is located in the Western Ghats region of Karnataka, which is one of the important biodiversity hotspots of India.…”

Section: Introductionmentioning

confidence: 99%

Use of TanDEM-X PolInSAR for canopy height retrieval over tropical forests in the Western Ghats, India

Raveendrakumar¹,

Khati²,

Musthafa³

et al. 2022

Front. For. Glob. Change

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Canopy height is a critical parameter in quantifying the vertical structure of forests. Polarimetric SAR Interferometry (PolInSAR) is a radar remote sensing technique that makes use of polarimetric separation of scattering phase centers obtained from interferometry to estimate height. This article discusses the potential of the X-band PolInSAR pair for forest height retrieval over tropical forests in the Western ghats. A total of 19 fully polarimetric datasets with various spatial baselines acquired from November 2015 to February 2016 in bistatic mode are utilized in this study. After compensating for all possible non-volumetric decorrelations in the data-sets, the remaining volume decorrelation is modeled using a Random Volume Over Ground (RVoG) model to invert height from PolInSAR data. A modified three-stage algorithm developed by Cloude and Papathanassiou (2003) is adopted for height inversion. PolInSAR derived heights were cross-validated against reference height data measured during a field survey conducted in March 2019. RMSE values of all TerraSAR-X/TanDEM-X PolInSAR heights with respect to field measured heights range from 3.3 to 13.8 m and the correlation coefficient r2 varies between 0.16 and 0.79. The results suggest that the use of a dataset with optimal wavenumber can improve the tree height estimation process. The best performance was achieved for the dataset acquired on 11 December 2015 with RMSE = 3.4 m and r2 = 0.79. Furthermore, the effects of parameters such as angle of incidence, precipitation, and forest biomass on height inversion accuracy are assessed. A large-scale Shimoga Forest height map was generated using multiple TanDEM-X acquisitions with the best correlation results. To improve the accuracy of the height estimation, a merged height approach is explored. The best height estimates among all PolInSAR estimates for a given field plot are chosen in this regard. The merged height approach gave rise to an improved inversion accuracy with RMSE = 1.9 m and r2 = 0.92. The primary objective of this study was to demonstrate the ability of spaceborne X-band data to estimate height with maximum accuracy over natural forests in India, in which height retrieval research has seldom been done.

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Geospatial Data for the Himalayan Region: Requirements, Availability, and Challenges

Agrawal

Raghavendra

Kumar

et al. 2018

Remote Sensing of Northwest Himalayan Ecosystems

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Bistatic PolInSAR Inversion Modelling for Plant Height Retrieval in a Tropical Forest

Cited by 12 publications

References 33 publications

Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

Use of TanDEM-X PolInSAR for canopy height retrieval over tropical forests in the Western Ghats, India

Geospatial Data for the Himalayan Region: Requirements, Availability, and Challenges

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