Determination of Glacier Surface Area Using Spaceborne Sar Imagery

Li, Fang; Maksymiuk, Oliver; Schmitt, Michael; Stilla, Uwe

doi:10.5194/isprsarchives-xl-1-w1-105-2013

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…In the case studies performed in cryospheric regions, we can conclude that HR RS data is the best fit for the information extraction. CSIR [45] [58] [71]- [81], ensemble classifiers [38], RF [68] and spectral-shape approach based on OOC methods [60] are the best suited methods as compared to traditional classification approaches. The accuracy shown by these classifiers ranges between 85% and 97% (approximately).…”

Section: Summary and Discussionmentioning

confidence: 99%

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

Jawak¹,

Devliyal²,

Luis³

2015

ARS

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Image classification is one of the most basic operations of digital image processing. The present review focuses on the strengths and weaknesses of traditional pixel-based classification (PBC) and the advances of object-oriented classification (OOC) algorithms employed for the extraction of information from remotely sensed satellite imageries. The state-of-the-art classifiers are reviewed for their potential usage in urban remote sensing (RS), with a special focus on cryospheric applications. Generally, classifiers for information extraction can be divided into three catalogues: 1) based on the type of learning (supervised and unsupervised), 2) based on assumptions on data distribution (parametric and non-parametric) and, 3) based on the number of outputs for each spatial unit (hard and soft). The classification methods are broadly based on the PBC or the OOC approaches. Both methods have their own advantages and disadvantages depending upon their area of application and most importantly the RS datasets that are used for information extraction. Classification algorithms are variedly explored in the cryosphere for extracting geospatial information for various logistic and scientific applications, such as to understand temporal changes in geographical phenomena. Information extraction in cryospheric regions is challenging, accounting to the very similar and conflicting spectral responses of the features present in the region. The spectral responses of snow and ice, water, and blue ice, rock and shadow are a big challenge for the pixel-based classifiers. Thus, in such cases, OOC approach is superior for extracting information from the cryospheric regions. Also, ensemble classifiers and customized spectral index ratios S. D. Jawak et al. 178 (CSIR) proved extremely good approaches for information extraction from cryospheric regions. The present review would be beneficial for developing new classifiers in the cryospheric environment for better understanding of spatial-temporal changes over long time scales.

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Section: Summary and Discussionmentioning

confidence: 99%

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

Jawak¹,

Devliyal²,

Luis³

2015

ARS

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“…Taking into account the small spatial scale of the image range, the decision tree classification algorithm was used for the fast and robust classification calculation. The classification results obtained from the RF decision tree algorithm (Fang et al 2013) are shown in Fig. 4a, and the area of glacier is about 943.4 km 2 .…”

Section: Insar Processingmentioning

confidence: 99%

Analysis of the melting glaciers in Southeast Tibet by ALOS-PALSAR data

Du¹,

Liu²,

Guo³

et al. 2019

Terr. Atmos. Ocean. Sci.

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Global warming has resulted in the melting of glaciers in the southeastern region of Tibet. This study used the InSAR time series obtained from ALOS PALSAR data to investigate the melting glacier over Southeast Tibet during 2007-2010 with the small baseline subset (SBAS) technique. Additionally, GRACE (Gravity Recovery and Climate Experiment) gravity field model issued by the Center for Space Research (CSR) was used to extract the equivalent water height (EWH) with the deduction of glacial isostatic adjustment (GIA). The results revealed that the monitoring results by InSAR were basically consistent with the EWHs from GRACE. The glacier deformation in the study area presents a downward trend overall. From the InSAR measurements, a 900km 2 area within the belt subsided-1.6 cm yr-1 during 2007-2010, and the subsidence exceeded-24 cm yr-1 in some regions. On the other hand, as an auxiliary data source, the monitoring result of GRACE is large space scale and comprehensive, the rate is about-0.01 cm yr-1 from GRACE. With the variations of glacier shape obtained from MODIS (moderate-resolution imaging spectroradiometer) data, the changing rate of surface temperature was about 0.014°C yr-1. The surface temperature change is negatively correlated with the rate of the glacial subsidence with the correlation coefficient of-0.237, which reflects that the melting glacier is influenced by the temperature rising to a certain extent.

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“…Unlike the passive visual spectrum sensors onboard the Landsat missions, synthetic aperture radar (SAR) actively detects microwave reflection signals that pierce through cloud cover and darkness [17][18][19], making it a useful tool in alpine and polar glacier velocity determination. Spaceborne SAR sensors onboard the European Space Agency's (ESA) ERS-1/2 missions launched in the 1990s created a tandem constellation of satellites that achieved sub-30 m spatial resolution with individual 35 day repeat cycles [20].…”

Section: Introductionmentioning

confidence: 99%

“…Both temporal and spatial resolution improved in the 2000s with the deployment of TerraSAR-X, granting a sub-16 m pixel SAR scanning mode and an 11-day repeat cycle [19]. In 2014 and 2015, the ESA launched the Sentinel-1a and Sentinel-1b (S1a/S1b) satellites, respectively, providing 10 m resolution coverage on a tandem repeat cycle of 6 days, further improving accuracy and precision [18]. Individual researchers can obtain SAR-based velocity fields using the ESA's SeNtinel Analysis Platform (SNAP).…”

Section: Introductionmentioning

confidence: 99%

Uncertainty of Satellite-Derived Glacier Flow Velocities in a Temperate Alpine Setting (Juneau Icefield, Alaska)

Kelly,

Hehlen,

McGee

2023

Remote Sensing

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Cross-correlation of image-pairs derived from both optical and synthetic aperture radar satellite imagery is the most common technique for measuring glacier flow velocity and quantifying the dynamics and discharge of glaciers. While the technique has been shown to be effective on polar ice sheets, the accuracy of satellite-derived velocities in temperate alpine regions is poorly constrained. Flow velocities were measured in situ using an RTK-GPS along four profiles on Taku, Matthes, Vaughan-Lewis, and Llewellyn Glaciers in southeast Alaska from 2016 through 2018. These GNSS-measured velocities were correlated against spatially coincident and contemporaneous satellite-derived velocity datasets, including both versions 1 and 2 of ITS_LIVE and velocities determined by offset tracking of SAR data in the Sentinel Application Platform (SNAP) and GAMMA (RETREAT dataset). Significant gaps in velocity maps derived from optical imagery (Landsat/Sentinel-2) were observed and determined to be due to low coherence rather than cloud contamination. Cross-correlation of SAR data (Sentinel-1) in SNAP and RETREAT achieved better accuracy compared to optical, although a strong dichotomy in performance was observed. SAR-derived velocities in the accumulation zone and transient snowline area showed overall poor correlation to GNSS-measured velocities that were likely due to significant shifts in the backscatter amplitude of the homogenous, snow-covered surface, although both SAR-derived SNAP and RETREAT velocities were anomalously accurate where GNSS velocities were below 0.10 m/day along the glacier margins. SNAP and RETREAT achieved the most accurate results in the study in the ablation zone of the Llewellyn Glacier where stable backscatter targets on the glacier surface (crevasses, supraglacial debris) facilitated high coherence in the cross-correlation procedure. SAR data are likely the most suitable for the derivation of satellite-derived velocities on temperate alpine glaciers, particularly in slow-moving and ablation zones, but should be subject to scrutiny for fast-flowing glaciers and those with an active hydrologic surface system.

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Determination of Glacier Surface Area Using Spaceborne Sar Imagery

Cited by 3 publications

References 10 publications

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

Analysis of the melting glaciers in Southeast Tibet by ALOS-PALSAR data

Uncertainty of Satellite-Derived Glacier Flow Velocities in a Temperate Alpine Setting (Juneau Icefield, Alaska)

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