Planimetric and volumetric glacier changes in the Khumbu Himal, Nepal, since 1962 using Corona, Landsat TM and ASTER data

Bolch, Tobias; Buchroithner, Manfred; Pieczonka, Tino; Kunert, André

doi:10.3189/002214308786570782

Cited by 353 publications

(305 citation statements)

References 27 publications

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“…And although melting is expected to be reduced under the debris cover on these lower glacier parts (e.g. Benn & Lehmkuhl, 2000), the surface properties possibly have only limited influence on the melting: In their study in the Himachal Pradesh, Berthier et al (2007) observed the strongest lowering of glacier surfaces at low elevations, independent of the amount of debris cover; Gardelle et al (2012) made similar findings in the Karakoram, Bolch et al (2008) in the Mt. Everest region, and Paul & Haeberli (2008) in the European Alps.…”

Section: Glacier Inventory Datasupporting

confidence: 49%

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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: Glacier Inventory Datasupporting

confidence: 49%

“…Bolch et al, 2008;Bhambri et al, 2011). In higher latitudes, illumination differences caused by the convex shape of the tongues or the break in slope at the contact to lateral moraines can be used to track glacier boundaries (cf.…”

Section: Mapping Of Debris-covered Glacier Partsmentioning

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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“…iteratively shifting one DEM to the other within a ±5 pixel window (Rodriguez et al, 2006;Berthier et al, 2007;Howat et al, 2008). Other studies have corrected DEMs using single or multiple linear regression corrections between elevation and the location and terrain parameters (Gorokhovich and Voustianiouk, 2006;Bolch et al, 2008;Peduzzi et al, 2010). In terrestrial and airborne laser scanning, 3-D Least Squares Matching (LSM) is used to minimize the Euclidean distances between the points of point clouds, often allowing not only for shifts but also for rotations and scales between the two or more datasets (Gruen and Akca, 2005;Miller et al, 2009).…”

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confidence: 99%

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

2011

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Abstract.There are an increasing number of digital elevation models (DEMs) available worldwide for deriving elevation differences over time, including vertical changes on glaciers. Most of these DEMs are heavily post-processed or merged, so that physical error modelling becomes difficult and statistical error modelling is required instead. We propose a three-step methodological framework for assessing and correcting DEMs to quantify glacier elevation changes: (i) remove DEM shifts, (ii) check for elevation-dependent biases, and (iii) check for higher-order, sensor-specific biases. A simple, analytic and robust method to co-register elevation data is presented in regions where stable terrain is either plentiful (case study New Zealand) or limited (case study Svalbard). The method is demonstrated using the three global elevation data sets available to date, SRTM, ICESat and the ASTER GDEM, and with automatically generated DEMs from satellite stereo instruments of ASTER and SPOT5-HRS. After 3-D co-registration, significant biases related to elevation were found in some of the stereoscopic DEMs. Biases related to the satellite acquisition geometry (along/cross track) were detected at two frequencies in the automatically generated ASTER DEMs. The higher frequency bias seems to be related to satellite jitter, most apparent in the backlooking pass of the satellite. The origins of the more significant lower frequency bias is uncertain. ICESat-derived elevations are found to be the most consistent globally available elevation data set available so far. Before performing regional-scale glacier elevation change studies or mosaicking DEMs from multiple individual tiles (e.g. ASTER GDEM), we recommend to co-register all elevation data to ICESat as a global vertical reference system.

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“…In the last decades, the availability of low-cost data from optical remote sensing platforms with global coverage provided opportunities for glacier mapping at regional scales. Remote sensing techniques have considerably helped improve estimates of glacier area changes (Bhambri et al, 2010;Bolch, 2007;Bajracharya et al, 2007;Kamp et al, 2011;Bolch et al, 2008a), glacier lake changes (Bajracharya et al, 2007;Bolch et al, 2008b;Gardelle et al, 2011;Wessels et al, 2002) and region-wide glacier mass balance Bolch et al, 2011;Gardelle et al, 2013;Kääb et al, 2012), but significant gaps do remain. The new global Randolph Glacier Inventory (RGI) v.4 (Pfeffer et al, 2014) provides a global data set of glacier outlines intended for largescale studies; however, in some regions the quality varies and the outlines may not be suitable for detailed regional analysis of glacier parameters.…”

Section: Introductionmentioning

confidence: 99%

Spatial patterns in glacier characteristics and area changes from 1962 to 2006 in the Kanchenjunga–Sikkim area, eastern Himalaya

et al. 2015

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Abstract. This study investigates spatial patterns in glacier characteristics and area changes at decadal scales in the eastern Himalaya -Nepal (Arun and Tamor basins), India (Teesta basin in Sikkim) and parts of China and Bhutan -based on various satellite imagery: Corona KH4 imagery, Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission Radiometer (ASTER), QuickBird (QB) and WorldView-2 (WV2). We compare and contrast glacier surface area changes over the period of 1962-2000/2006 and their dependency on glacier topography (elevation, slope, aspect, percent debris cover) and climate (solar radiation, precipitation) on the eastern side of the topographic barrier (Sikkim) versus the western side (Nepal).Glacier mapping from 2000 Landsat ASTER yielded 1463 ± 88 km 2 total glacierized area, of which 569 ± 34 km 2 was located in Sikkim and 488 ± 29 km 2 in eastern Nepal. Supraglacial debris covered 11 % of the total glacierized area, and supraglacial lakes covered about 5.8 % of the debris-covered glacier area alone. Glacier area loss (1962 to 2000) was 0.50 ± 0.2 % yr −1 , with little difference between Nepal (0.53 ± 0.2 % yr −1 ) and Sikkim (0.44 ± 0.2 % yr −1 ). Glacier area change was controlled mostly by glacier area, elevation, altitudinal range and, to a smaller extent, slope and aspect. In the Kanchenjunga-Sikkim area, we estimated a glacier area loss of 0.23 ± 0.08 % yr −1 from 1962 to 2006 based on high-resolution imagery. On a glacier-by-glacier basis, clean glaciers exhibit more area loss on average from 1962 to 2006 (34 %) compared to debris-covered glaciers (22 %). Glaciers in this region of the Himalaya are shrinking at similar rates to those reported for the last decades in other parts of the Himalaya, but individual glacier rates of change vary across the study area with respect to local topography, percent debris cover or glacier elevations.

show abstract

Planimetric and volumetric glacier changes in the Khumbu Himal, Nepal, since 1962 using Corona, Landsat TM and ASTER data

Cited by 353 publications

References 27 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

Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change

Spatial patterns in glacier characteristics and area changes from 1962 to 2006 in the Kanchenjunga–Sikkim area, eastern Himalaya

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