Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data

Berninger, Anna; Lohberger, Sandra; Zhang, Devin; Siegert, Florian

doi:10.3390/rs11182105

Cited by 18 publications

(9 citation statements)

References 66 publications

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“…Linear regression between the lidar-based and PolInSAR-model-based vegetation height for the temperate and tropical forest showed a 0.89 coefficient of determination with 2.3 m RMSE and a 0.98 coefficient of determination with 2.1 m RMSE [81]. Several other studies were also conducted in which highly accurate results were reported by the researchers [68,[82][83][84][85].…”

Section: Discussionmentioning

confidence: 82%

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: 82%

Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

et al. 2020

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Section: Estimating Forest Stand Height With Remote Sensingmentioning

confidence: 99%

“…InSAR techniques have not been extensively applied to tropical regions, although a few recent examples exist [40,41]. One study achieved an R 2 equal to 0.54 to 0.69 and an RMSE of 4.65 to 8.44 m at 3 to 12 m over tropical forest [40]. However, it is essential to prioritize the investigation of methods taking advantage of data that are openly accessible when considering the needs of end users.…”

Section: Estimating Forest Stand Height With Remote Sensingmentioning

confidence: 99%

Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

et al. 2021

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Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above-ground biomass for greenhouse gas emissions reporting and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) is applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.

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“…In [1,2], methods were developed for determining above-ground biomass, the first being based on water cloud modelling (WCM) from quad-polarised L-band (PALSAR) data on the Advanced Land Observing Satellite-2 (ALOS-2), and the second from dual-polarised X-band TerraSAR-X and quad-pol-InSAR C-band data from RADARSAT-2 data. The concept of water cloud modelling (WCM) was developed in [3], in which a vegetation canopy was represented by a water cloud, based on a number of parameters which were obtained through regression analysis of the radar cross section data for ground truth data based on four crop types.…”

Section: Overview Of Contributionsmentioning

confidence: 99%

“…In [2], the authors determined canopy height and above-ground biomass in a peat swamp tropical forest, with an area of 4340 ha, in central Kalimantan, on the island of Borneo, Indonesia, using pol-InSAR data. Airborne lidar data, with a point spacing of 10.7 points/m 2 and drone photography with a ground sampling distance of 5 cm, were derived over all field inventory areas, where DBH, tree height, and species of sample trees were determined.…”

Section: Overview Of Contributionsmentioning

confidence: 99%

Editorial for Special Issue “Applications of Synthetic Aperture Radar (SAR) for Land Cover Analysis”

Trinder¹

2020

Remote Sensing

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Synthetic aperture radar (SAR) imaging systems derive microwave data, from space or airborne (piloted and remote piloted), that provide opportunities for the interpretation of many characteristics of the terrain surface. The increasing number of satellites equipped with SAR data acquisition systems that are being launched with a range of wavelengths, polarizations, and operating characteristics are enabling a better understanding of the earth’s environment, for such activities as vegetation analysis, forest inventories, land subsidence, and urban analysis. In addition, airborne systems for remote piloted systems and ground-based systems are available. This Special Issue presents six quality scientific papers on typical applications of SAR technologies. They include methods for the determination of above ground biomass (AGB), crop mapping using data from an advanced X-band system developed in Japan, analysis of natural and human-induced slow-rate ground deformations in the region of Campania, in Italy, the location of landslides caused by natural phenomena based on SAR images derived from the Japanese high-resolution Advanced Land Observing Satellite-2 (ALOS-2), and monitoring the size of refugee camps and their environmental impacts caused by the displacement of people from Myanmar to the Cox’s Bazar District, around Kutupalong, in Bangladesh. The paper concludes with some comments on the future directions of developments in SAR systems.

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Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data

Cited by 18 publications

References 66 publications

Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

Editorial for Special Issue “Applications of Synthetic Aperture Radar (SAR) for Land Cover Analysis”

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