The effects of radiometric terrain flattening on SAR-based forest mapping and classification

Dostálová, Alena; Navacchi, Claudio; Greimeister-Pfeil, Isabella; Small, David; Wagner, Wolfgang

doi:10.1080/2150704x.2022.2092911

Cited by 10 publications

(3 citation statements)

References 16 publications

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“…In GEE, angular corrections are also available [20], [38]. The Radiometric Terrain Correction (RTC) [18] has gained much interest in recent times for reducing topographic effects using the illuminated pixel area (IPA) to calculate γ 0 RTC , with more notable effect in mountainous areas [39]. For example, the RTC renders intensity information more comparable to combining overlapping relative orbits as temporal composites [40].…”

Section: Radiometric Corrections In Forestsmentioning

confidence: 99%

Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency

Zehner,

Dubois,

Thiel

et al. 2023

IEEE Trans. Geosci. Remote Sensing

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Microwave scattering from forests generates pixel geolocation shifts in Synthetic aperture radar (SAR) data that require an adequate representation within digital elevation models (DEM) for preprocessing. We analyze the impact of DEM properties on the radiometry and geolocation of radiometric terrain corrected (RTC) Copernicus Sentinel-1 imagery of forests to improve consistency in backscatter intensities for time series analyses. To account for the penetration depth of the C-Band sensor, we approximate the structure of stands in a temperate deciduous forest using height percentiles from Aerial Laser Scanning (ALS) point clouds in the Hainich National Park, Germany. Comparing the RTC results obtained using DEMs of SRTM, Copernicus, and ALS DEMs, the latter reduces topographically induced errors, resulting in visibly smaller effects from topography and spatially shifted information. Based on the P50 ALS vegetation elevation, results show homogeneous intensities within the same orbit and reduce variance from 2.4 dB 2 to 1.2 dB 2 in the difference of midrange data from ascending and descending azimuth directions. Over forest, we observe lower intensities on sensor-facing and increased intensities on away-facing slopes and correlations with the illuminated pixel area (IPA) and local incidence angle. We reduce this bias with linear regressions of intensity on IPA. ALS DEMs in RTC and the proposed regression correction increase the consistency of images across orbits, measured by the interorbit range, throughout the selected year at our study site. We suggest the proposed method applies to other areas, requiring further testing under different forest types and topography.

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Section: Radiometric Corrections In Forestsmentioning

confidence: 99%

Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency

Zehner,

Dubois,

Thiel

et al. 2023

IEEE Trans. Geosci. Remote Sensing

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“…However, in terms of ESAC, the cross-sectional area of radar scattering is only applicable to a single scattering target (the target object is smaller than the irradiation range), and the scattered signal of the resolution unit for distributed scatterers (such as forests) is the result of coherent superposition of the scattered signal of each single scatterer, so the backscattering coefficient is commonly used to describe the scattering ability of ground objects based on statistical methods. Three different backscattering coefficients can be defined according to the area of the effective scattering element: the backscattering coefficient of the imaging surface (β 0 ), the backscattering coefficient of the ground regardless of the terrain (σ 0 ), and the backscattering coefficient of the isophase surface (γ 0 ) [55,66]. When ESAC's object is σ 0 , it essentially converts σ 0 to γ 0 in relation to the topographic factor.…”

Section: Introductionmentioning

confidence: 99%

Inversion of Forest above Ground Biomass in Mountainous Region Based on PolSAR Data after Terrain Correction: A Case Study from Saihanba, China

Nie,

Hu,

et al. 2024

Remote Sensing

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Accurate retrieval of forest above ground biomass (AGB) based on full-polarization synthetic aperture radar (PolSAR) data is still challenging for complex surface regions with fluctuating terrain. In this study, the three-step process of radiometric terrain correction (RTC), which includes polarization orientation angle correction (POAC), effective scattering area correction (ESAC), and angular variation effect correction (AVEC), is adopted as the technical framework. In the ESAC stage, a normalized correction factor is introduced based on local incidence angle and radar incidence angle to achieve accurate correction of PolSAR data information and improve the inversion accuracy of forest AGB. In order to verify the validity and robustness of this research method, the full-polarization SAR data of ALOS-2 and the ground measured AGB data collected in the Saihanba research area in 2020 were used for experiments. Our findings revealed that in the ESAC phase, the introduction of the normalized correction factor can effectively eliminate the ESA phenomenon and improve the correlation coefficients of the backscatter coefficient and AGB. Taking the data of 25 July 2020 as an example, ESAC increases the correlation coefficients between AGB and the backscattering coefficients of HH, HV, and VV polarization channels by 0.343, 0.296, and 0.382, respectively. In addition, the RTC process has strong robustness in different AGB statistical models and different date PolSAR data.

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“…A milestone in overcoming this limitation was achieved by [14], who presented a method for computing a terrain flattened normalised radar backscatter coefficient, i.e., Radiometric Terrain Corrected (RTC) gamma nought γ 0 T . In recent years, γ 0 T has been more and more widely used for improving the use of SAR data in undulated terrain [15,16] or across different orbits [17,18]. These achievements motivated the Committee on Earth Observation Satellites (CEOS) to select γ 0 T as a standard for analysis-ready Data (ARD) [19].…”

Section: Introductionmentioning

confidence: 99%

Utilising Sentinel-1’s Orbital Stability for Efficient Pre-Processing of Radiometric Terrain Corrected Gamma Nought Backscatter

Navacchi

Cao²,

Bauer-Marschallinger

et al. 2023

Sensors

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Radiometric Terrain Corrected (RTC) gamma nought backscatter, which was introduced around a decade ago, has evolved into the standard for analysis-ready Synthetic Aperture Radar (SAR) data. While working with RTC backscatter data is particularly advantageous over undulated terrain, it requires substantial computing resources given that the terrain flattening is more computationally demanding than simple orthorectification. The extra computation may become problematic when working with large SAR datasets such as the one provided by the Sentinel-1 mission. In this study, we examine existing Sentinel-1 RTC pre-processing workflows and assess ways to reduce processing and storage overheads by considering the satellite’s high orbital stability. By propagating Sentinel-1’s orbital deviations through the complete pre-processing chain, we show that the local contributing area and the shadow mask can be assumed to be static for each relative orbit. Providing them as a combined external static layer to the pre-processing workflow, and streamlining the transformations between ground and orbit geometry, reduces the overall processing times by half. We conducted our experiments with our in-house developed toolbox named wizsard, which allowed us to analyse various aspects of RTC, specifically run time performance, oversampling, and radiometric quality. Compared to the Sentinel Application Platform (SNAP) this implementation allowed speeding up processing by factors of 10–50. The findings of this study are not just relevant for Sentinel-1 but for all SAR missions with high spatio-temporal coverage and orbital stability.

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The effects of radiometric terrain flattening on SAR-based forest mapping and classification

Cited by 10 publications

References 16 publications

Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency

Accounting for Deciduous Forest Structure and Viewing Geometry Effects Improves Sentinel-1 Time Series Image Consistency

Inversion of Forest above Ground Biomass in Mountainous Region Based on PolSAR Data after Terrain Correction: A Case Study from Saihanba, China

Utilising Sentinel-1’s Orbital Stability for Efficient Pre-Processing of Radiometric Terrain Corrected Gamma Nought Backscatter

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