An evaluation of void‐filling interpolation methods for SRTM data

Reuter, H. I.; Nelson, Andrew; Jarvis, Andy

doi:10.1080/13658810601169899

Cited by 700 publications

(463 citation statements)

References 21 publications

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“…The SRTM DEM was acquired using radar interferometry (InSAR) (Farr et al, 2007), which is subject to data voids in rugged highmountain terrain due to radar shadow and layover effects. The Consultative Group for International Agriculture Research (CGIAR) compiled a void-free version (SRTM3v4) by interpolating the terrain in data voids based on information from other elevation datasets (Reuter et al, 2007). This void-free SRTM version has been used in numerous glaciological studies, mainly related to the assessment of ice volume variations with time (e.g.…”

Section: Digital Elevation Modelsmentioning

confidence: 99%

Compilation of a glacier inventory for the western Himalayas from satellite data: methods, challenges, and results

Frey

Paul

Strozzi

2012

Remote Sensing of Environment

204

150

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Due to their sensitive reaction to changes in climatic conditions, glaciers have been selected as an essential climate variable (ECV). Although a large amount of ice is located in the Himalayas, this region is yet only sparsely represented in global glacier databases. Accordingly, a sound and comprehensive change assessment or determination of water resources was not yet possible. In this study, we present a new glacier inventory for the western Himalayas, compiled from Landsat ETM+ scenes acquired between 2000 and 2002, coherence images from ALOS PALSAR image pairs, the SRTM digital elevation model (DEM) and the ASTER Global DEM (GDEM). Several specific challenges for glacier mapping were found in this region and addressed. They are related to debris cover, orographic clouds, locally variable snow conditions, and creeping permafrost features in cold-dry regions. Additional to seven topographic parameters that are obtained from the ASTER GDEM for each glacier, we also determined the relative amount of debris cover on the glacier surface. The inventory contains 11,400 glaciers larger than 0.02 km2, which cover a total area of 9,310 km2. Analysis of the inventory data revealed characteristic patterns of mean glacier elevation and relative debris cover amounts that might be related to the governing climatic conditions. The full dataset will be freely available in the GLIMS glacier database to foster further analyses and modeling of the glaciers in this region. AbstractDue to their sensitive reaction to changes in climatic conditions, glaciers have been selected as an essential climate variable (ECV). Although a large amount of ice is located in the Himalayas, this region is yet only sparsely represented in global glacier databases. Accordingly, a sound and comprehensive change assessment or determination of water resources was not yet possible. In this study, we present a new glacier inventory for the western Himalayas, compiled from Landsat ETM+ scenes acquired between 2000 and 2002, coherence images from ALOS PALSAR image pairs, the SRTM digital elevation model (DEM) and the ASTER Global DEM (GDEM). Several specific challenges for glacier mapping were found in this region and addressed. They are related to debris cover, orographic clouds, locally variable snow conditions, and creeping permafrost features in cold-dry regions. Additional to seven topographic parameters that are obtained from the ASTER GDEM for each glacier, we also determined the relative amount of debris cover on the glacier surface. The inventory contains 11,400 glaciers larger than 0.02 km 2 , which cover a total area of 9,310 km 2 . Analysis of the inventory data revealed characteristic patterns of mean glacier elevation and relative debris cover amounts that might be related to the governing climatic conditions. The full dataset will be freely available in the GLIMS glacier database to foster further analyses and modeling of the glaciers in this region.

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Section: Digital Elevation Modelsmentioning

confidence: 99%

Compilation of a glacier inventory for the western Himalayas from satellite data: methods, challenges, and results

Frey

Paul

Strozzi

2012

Remote Sensing of Environment

204

150

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“…The SRTM elevation data are available through the internet (http://hydrosheds.cr.usgs.gov). Raw SRTM elevation data includes void or holes ranging from one pixel to regions of 500 km 2 [13]. The existence of no-data in the SRTM-DEM can causes significant problems during derivation of hydrological products, which require continuous flow surfaces [14].…”

Section: Public Domain Satellite Demsmentioning

confidence: 99%

Application of Public Domain Satellite-Based DEMs in Natural Hazard Modeling

Akbari¹,

Ramli²,

Kong³

2016

IJESD

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“…Some known problems such as the data void due to shadowing and smooth surfaces, or weak penetration of the vegetation canopies were addressed to some extent in version 4 (Reuter et al, 2007).…”

Section: Input Data Setsmentioning

confidence: 99%

“…Statistical values of the observed (scattered) free-air gravity anomalies and normal heights at the 244009 measured points of the data set (Duquenne, 2007 Another type of data set are DEMs. For our computation, we used three DEMs: the SRTM3 version 4 (Werner, 2001;Rodriguez et al, 2005;Reuter et al, 2007), the ACE2 which is based on a combination of the SRTM and Satellite Radar Altimetry data (Berry et al, 2010) and a global DEM in the form of spherical harmonic coefficients of the JGP95 model (Lemoine et al, 1998). The SRTM3 model was used for representing a detailed topography on a grid of 3 × 3 spacing.…”

Section: Input Data Setsmentioning

confidence: 99%

Computation of precise geoid model of Auvergne using current UNB Stokes-Helmert’s approach

Janák

Vaníček

Foroughi

et al. 2017

Contributions to Geophysics and Geodesy

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Abstract:The aim of this paper is to show a present state-of-the-art precise gravimetric geoid determination using the UNB Stokes-Helmert's technique in a simple schematic way. A detailed description of a practical application of this technique in the Auvergne test area is also provided. In this paper, we discuss the most problematic parts of the solution: correct application of topographic and atmospheric effects including the lateral topographical density variations, downward continuation of gravity anomalies from the Earth surface to the geoid, and the optimal incorporation of the global gravity field into the final geoid model. The final model is tested on 75 GNSS/levelling points supplied with normal Molodenskij heights, which for this investigation are transformed to rigorous orthometric heights. The standard deviation of the computed geoid model is 3.3 cm without applying any artificial improvement which is the same as that of the most accurate quasigeoid.

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An evaluation of void‐filling interpolation methods for SRTM data

Cited by 700 publications

References 21 publications

Compilation of a glacier inventory for the western Himalayas from satellite data: methods, challenges, and results

Compilation of a glacier inventory for the western Himalayas from satellite data: methods, challenges, and results

Application of Public Domain Satellite-Based DEMs in Natural Hazard Modeling

Computation of precise geoid model of Auvergne using current UNB Stokes-Helmert’s approach

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