Sub-pixel precision image matching for measuring surface displacements on mass movements using normalized cross-correlation

Debella-Gilo, Misganu; Kääb, Andreas

doi:10.1016/j.rse.2010.08.012

Cited by 308 publications

(159 citation statements)

References 107 publications

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“…Two primary methods exist to increase the accuracy of the alignment to subpixel values. The first is curve-fitting the correlation surface to find the function's maximum [23,24]. This method can require iteratively curve-fitting a function (usually parabolic or Gaussian) to the correlation in the spatial domain and can be made arbitrarily accurate, but is computationally intensive.…”

Section: Methods For Determining Diffraction Disk Positionsmentioning

confidence: 99%

Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

et al. 2017

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Scanning nanobeam electron diffraction strain mapping is a technique by which the positions of diffracted disks sampled at the nanoscale over a crystalline sample can be used to reconstruct a strain map over a large area. However, it is important that the disk positions are measured accurately, as their positions relative to a reference are directly used to calculate strain. In this study, we compare several correlation methods using both simulated and experimental data in order to directly probe susceptibility to measurement error due to non-uniform diffracted disk illumination structure. We found that prefiltering the diffraction patterns with a Sobel filter before performing cross correlation or performing a square-root magnitude weighted phase correlation returned the best results when inner disk structure was present. We have tested these methods both on simulated datasets, and experimental data from unstrained silicon as well as a twin grain boundary in 304 stainless steel.

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Section: Methods For Determining Diffraction Disk Positionsmentioning

confidence: 99%

Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

et al. 2017

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“…For this study, we calculated LST from Landsat ETM+ and TM thermal band spectral data (method after Barsi et al, 2005;explained in Hall et al, 2008) using a dirty ice emissivity of 0.96 after (Qunzhu et al, 1985). Glacier surface velocity, or horizontal surface displacements were derived using normalized cross-correlation repeat Landsat TM near-infrared band and repeat ETM+ pan data (methods detailed in Kääb and Vollmer, 2000;Debella-Gilo and Kääb, 2011). With the assumption that the calculated velocity field…”

Section: Complementary Supraglacial Debrismapping Methodsmentioning

confidence: 99%

Geochemical characterization of supraglacial debris via in situ and optical remote sensing methods: a case study in Khumbu Himalaya, Nepal

2012

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Abstract. Surface glacier debris samples and field spectra were collected from the ablation zones of Nepal Himalaya Ngozumpa and Khumbu glaciers in November and December 2009. Geochemical and mineral compositions of supraglacial debris were determined by X-ray diffraction and X-ray fluorescence spectroscopy. This composition data was used as ground truth in evaluating field spectra and satellite supraglacial debris composition and mapping methods. Satellite remote sensing methods for characterizing glacial surface debris include visible to thermal infrared hyper-and multispectral reflectance and emission signature identification, semi-quantitative mineral abundance indicies and spectral image composites. Satellite derived supraglacial debris mineral maps displayed the predominance of layered silicates, hydroxyl-bearing and calcite minerals on Khumbu Himalayan glaciers. Supraglacial mineral maps compared with satellite thermal data revealed correlations between glacier surface composition and glacier surface temperature. Glacier velocity displacement fields and shortwave, thermal infrared false color composites indicated the magnitude of mass flux at glacier confluences. The supraglacial debris mapping methods presented in this study can be used on a broader scale to improve, supplement and potentially reduce errors associated with glacier debris radiative property, composition, areal extent and mass flux quantifications.

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“…The analysis of optical imagery for landslide mapping can be performed through (i) visual interpretation of single and stereoscopic images ; (ii) image classification with semi-automated pixel-based methods (Borghuis et al, 2007;Marcelino et al, 2009); (iii) image classification with semi-automated object-oriented methods (Martha et al, 2010;Lu et al, 2011;Stumpf and Kerle, 2011); (iv) change detection techniques (Nichol and Wong, 2005;Weirich and Blesius, 2007;Tsai et al, 2010); and (v) correlation of optical images (Delacourt et al, 2007;Leprince et al, 2007;Debella-Gilo and Kääb, 2011).…”

Section: Tofani Et Al: Use Of Remote Sensing For Landslide Studiementioning

confidence: 99%

Technical Note: Use of remote sensing for landslide studies in Europe

Tofani

Segoni

Agostini

et al. 2013

Nat. Hazards Earth Syst. Sci.

127

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Abstract. Within the framework of FP7, an EU-funded SafeLand project, a questionnaire was prepared to collect information about the use of remote sensing for landslide study and to evaluate its actual application in landslide detection, mapping and monitoring. The questionnaire was designed using a Google form and was disseminated among end-users and researchers involved in landslide studies in Europe. In total, 49 answers from 17 different European countries were collected. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000–1:25 000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. According to the research and working experience of the compilers, remote sensing is generally considered to have a medium effectiveness/reliability for landslide studies. The results of the questionnaire can contribute to an overall sketch of the use of remote sensing in current landslide studies and show that remote sensing can be considered a powerful and well-established instrument for landslide mapping, monitoring and hazard analysis.

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Sub-pixel precision image matching for measuring surface displacements on mass movements using normalized cross-correlation

Cited by 308 publications

References 107 publications

Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

Geochemical characterization of supraglacial debris via in situ and optical remote sensing methods: a case study in Khumbu Himalaya, Nepal

Technical Note: Use of remote sensing for landslide studies in Europe

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