scholarly journals Spatial patterns in glacier area and elevation changes from 1962 to 2006 in the monsoon-influenced eastern Himalaya

2014 ◽  
Vol 8 (4) ◽  
pp. 3949-3998 ◽  
Author(s):  
A. Racoviteanu ◽  
Y. Arnaud ◽  
M. Williams ◽  
W. F. Manley
Keyword(s):  
Spatial Patterns ◽  
Thermal Emission ◽  
Spatial Scales ◽  
Remote Sensing Data ◽  
Eastern Himalaya ◽  
Slope Aspect ◽  
Glacier Area ◽  
Covered Area ◽  
Landsat 7 ◽  
Elevation Changes

Abstract. This study presents spatial patterns in glacier area and elevation changes in the monsoon-influenced part of the Himalaya (eastern Nepal and Sikkim) at multiple spatial scales. We combined Corona KH4 and topographic data with more recent remote-sensing data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), the Advanced Spaceborne Thermal Emission Radiometer (ASTER), QuickBird (QB) and WorldView-2 (WV2) sensors. We present: (1) spatial patterns of glacier parameters based on a new "reference" geospatial Landsat/ASTER glacier inventory from ~ 2000; (2) changes in glacier area (1962–2006) and their dependence on topographic variables (elevation, slope, aspect, percent debris cover) as well as climate variables (solar radiation and precipitation), extracted on a glacier-by-glacier basis and (3) changes in glacier elevations for debris-covered tongues and their relationship to surface temperature extracted from ASTER data. Glacier mapping from 2000 Landsat/ASTER yielded 1463 km2 ± 88 km2 total glacierized area in Nepal (Tamor basin) and Sikkim (Zemu basin), parts of Bhutan and China, of which we estimated 569 km2 ± 34 km2 to be located in Sikkim. Supraglacial debris covered 11% of the total glacierized area, and supraglacial lakes covered about 5.8% of the debris-covered area. Based on analysis of high-resolution imagery, we estimated an area loss of −0.24% ± 0.08% yr−1 from the 1960's to the 2010's, with a higher rate of retreat in the last decade (−0.43% yr−1 ± 0.9 % from 2000 to 2006) compared to the previous decades (−0.20% yr−1 ± 0.16% from 1962 to 2000). Retreat rates of clean glaciers were −0.7% yr−1, almost double than those of debris-covered glaciers (−0.3% yr−1). Debris-covered tongues experienced an average lowering of −30.8 m ± 39 m from 1960's to 2000's (−0.8 m ± 0.9 m yr−1), with enhanced thinning rates in the upper part of the debris covered area, and overall thickening at the glacier termini.

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

2015 ◽  
Vol 9 (2) ◽  
pp. 505-523 ◽  
Author(s):  
A. E. Racoviteanu ◽  
Y. Arnaud ◽  
M. W. Williams ◽  
W. F. Manley
Keyword(s):  
Spatial Patterns ◽  
Thermal Emission ◽  
Eastern Himalaya ◽  
Slope Aspect ◽  
Glacier Area ◽  
Glacier Surface ◽  
Area Loss ◽  
Debris Cover ◽  
Landsat 7 ◽  
The Himalaya

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 km2 total glacierized area, of which 569 ± 34 km2 was located in Sikkim and 488 ± 29 km2 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.

scholarly journals Glacier Changes in the Chhombo Chhu Watershed of Tista basin between 1975 and 2018, Sikkim Himalaya, India

2021 ◽  
Author(s):  
Arindam Chowdhury ◽  
Milap Chand Sharma ◽  
Sunil Kumar De ◽  
Manasi Debnath
Keyword(s):  
Large Population ◽  
Eastern Himalaya ◽  
Glacier Area ◽  
Change Analysis ◽  
Sikkim Himalaya ◽  
Mountain Communities ◽  
Area Loss ◽  
Landsat 7 ◽  
Landsat 5 Tm ◽  
Sentinel 2A

Abstract. Glaciers of the Tista basin represent an important water resource for mountain communities and large population downstream. The present article attempts to assess the observable changes in the glacier area in the Chhombo Chhu Watershed (CCW) of Tista basin, Sikkim Himalaya. The CCW consists of 74 glaciers (>0.02 km2) with a mean glacier size of 0.61 km2. The change of such glacier outlines obtained from the declassified hexagon KH-9 (1975), Landsat 5 TM (1989), Landsat 7 ETM+ (2000), Landsat 5 TM (2010), and Sentinel 2A (2018). The total glacier area in 1975 was 62.6 ±0.7 km2; by 2018, the area had decreased to 44.8 ±1.5 km2, an area loss of 17.9 ± 1.7 km2 (0.42 ± 0.04 km2 a−1). Debris free glaciers exhibit more area loss by 11.8 ± 1.2 km2 (0.27 ± 0.03  km2 a−1) followed by partially debris-covered (5.0 ± 0.4 km2 or 0.12 ± 0.01 km2 a−1) and maximum debris-covered (1.0 ± 0.1 km2 or −0.02 ± 0.002 km2 a−1) glaciers. The quantum of glacier area loss in the CCW of Sikkim Himalaya took its pace during 2000–2010 (0.62 ± 0.5 km2 a−1) and 2010–2018 (0.77 ± 0.6 km2 a−1) timeframes. Field investigations of selected glaciers and climatic records also support the trend in glacier recession in the CCW due to a significant increase in temperature trend and more or less static precipitation since 1995. Glacier retreat rates in the CCW were almost similar to the Changme Khangpu basin and other selected glaciers in Sikkim Himalaya. This glacier inventory and area change analysis will provide valuable information to the glaciological and hydrological community to model and plan the water resources in the Sikkim state of Eastern Himalaya. The dataset is now available from the Zenodo web portal: http://doi.org/10.5281/zenodo.4457183 (Chowdhury et al., 2021).

scholarly journals Recent changes in glacier area and volume within the southern Canadian Cordillera

2007 ◽  
Vol 46 ◽  
pp. 215-221 ◽  
Author(s):  
Christopher M. DeBeer ◽  
Martin J. Sharp
Keyword(s):  
Aerial Photography ◽  
Rocky Mountains ◽  
Glacier Area ◽  
Considerable Variability ◽  
Coast Mountains ◽  
Ice Volume ◽  
Covered Area ◽  
Scaling Relationship ◽  
Landsat 7 ◽  
Area And Volume

AbstractNet changes in glacier area in the region 50–51˚ N, 116–125˚W, which includes the Columbia and Rocky Mountains (1951/52–2001) and the Coast Mountains (1964/65–2002), were determined through a comparison of historic aerial photography and contemporary Landsat 7 ETM+ imagery. The volumes of individual glaciers were estimated using an empirical volume–area scaling relationship. The area of glaciers in the Coast Mountains decreased by 120±10km2, or 5%of the initial ice-covered area here. The areas of glaciers in the Columbia and Rocky Mountains decreased by 20 and 6km2 respectively, corresponding to relative changes in total area of –5% and –15%. The estimated total ice volume loss from the whole region was 13 ±3 km3. In all parts of the study area, the relative changes in area of individual glaciers showed considerable variability, while the smallest glaciers remained essentially unchanged. This suggests that local factors unique to individual glaciers largely determine their sensitivity to climatic change, and that the very small glaciers are collectively less sensitive to such change.

scholarly journals Multi-temporal airborne LIDAR-DEMs for glacier and permafrost mapping and monitoring

2009 ◽  
Vol 3 (2) ◽  
pp. 383-414 ◽  
Author(s):  
J. Abermann ◽  
A. Fischer ◽  
A. Lambrecht ◽  
T. Geist
Keyword(s):  
Airborne Lidar ◽  
Aerial Photographs ◽  
Good Representation ◽  
Glacier Area ◽  
Covered Area ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Elevation Changes ◽  
Remote Sensing Techniques ◽  
Permafrost Mapping

Abstract. The proposed method presents a simple and robust way to derive glacier extent by using multi-temporal high-resolution DEMs (digital elevation models) as a main data source. For glaciers that are not debris covered, we perform the glacier boundary delineation by analysing roughness differences between ice and its surroundings. A promising way to distinguish dead ice, debris-covered ice or permafrost from its rocky surroundings is shown by taking elevation changes from DEMs of different dates into consideration. In case data has a high spatial and temporal resolution a good representation of the extent of debris cover and thus the overall ice covered area can be given. We use examples to show how potentially ambiguous areas can be treated decisively by the additional qualitative analysis of aerial photographs. Problems and limitations are discussed in comparison with selected other remote sensing techniques and accuracies are quantified. For glaciers larger than 1 km2 an accuracy of ±1% of the glacier area could be assessed. The errors of smaller glaciers do not exceed ±5% of the glacier area.

scholarly journals Supraglacial debris thickness variability: impact on ablation and relation to terrain properties

2018 ◽  
Vol 12 (12) ◽  
pp. 3719-3734 ◽  
Author(s):  
Lindsey I. Nicholson ◽  
Michael McCarthy ◽  
Hamish D. Pritchard ◽  
Ian Willis
Keyword(s):  
Slope Failure ◽  
Spatial Scales ◽  
Slope Aspect ◽  
Small Scale ◽  
Main Process ◽  
Simple Relationship ◽  
Glacier Surface ◽  
Covered Area ◽  
Thickness Variability ◽  
Ground Penetrating

Abstract. Shallow ground-penetrating radar (GPR) surveys are used to characterize the small-scale spatial variability of supraglacial debris thickness on a Himalayan glacier. Debris thickness varies widely over short spatial scales. Comparison across sites and glaciers suggests that the skewness and kurtosis of the debris thickness frequency distribution decrease with increasing mean debris thickness, and we hypothesize that this is related to the degree of gravitational reworking the debris cover has undergone and is therefore a proxy for the maturity of surface debris covers. In the cases tested here, using a single mean debris thickness value instead of accounting for the observed small-scale debris thickness variability underestimates modelled midsummer sub-debris ablation rates by 11 %–30 %. While no simple relationship is found between measured debris thickness and morphometric terrain parameters, analysis of the GPR data in conjunction with high-resolution terrain models provides some insight into the processes of debris gravitational reworking. Periodic sliding failure of the debris, rather than progressive mass diffusion, appears to be the main process redistributing supraglacial debris. The incidence of sliding is controlled by slope, aspect, upstream catchment area and debris thickness via their impacts on predisposition to slope failure and meltwater availability at the debris–ice interface. Slope stability modelling suggests that the percentage of the debris-covered glacier surface area subject to debris instability can be considerable at glacier scale, indicating that up to 32 % of the debris-covered area is susceptible to developing ablation hotspots associated with patches of thinner debris.

scholarly journals Glacier mass balance over the central Nyainqentanglha Range during recent decades derived from remote-sensing data

2019 ◽  
Vol 65 (251) ◽  
pp. 422-439 ◽  
Author(s):  
KUNPENG WU ◽  
SHIYIN LIU ◽  
ZONGLI JIANG ◽  
JUNLI XU ◽  
JUNFENG WEI
Keyword(s):  
Mass Balance ◽  
Remote Sensing Data ◽  
Shuttle Radar Topography Mission ◽  
Topographic Maps ◽  
Glacier Mass Balance ◽  
Glacier Area ◽  
Ice Surface ◽  
Digital Elevation ◽  
Elevation Changes ◽  
Elevation Model

ABSTRACTTo obtain information on changes in glacier mass balance in the central Nyainqentanglha Range, a comprehensive study was carried out based on digital-elevation models derived from the 1968 topographic maps, the Shuttle Radar Topography Mission DEM (2000) and TerraSAR-X/TanDEM-X (2013). Glacier area changes between 1968 and 2016 were derived from topographic maps and Landsat OLI images. This showed the area contained 715 glaciers, with an area of 1713.42 ± 51.82 km2, in 2016. Ice cover has been shrinking by 0.68 ± 0.05% a−1 since 1968. The glacier area covered by debris accounted for 11.9% of the total and decreased in the SE–NW directions. Using digital elevation model differencing and differential synthetic aperture radar interferometry, a significant mass loss of 0.46 ± 0.10 m w.e. a−1 has been recorded since 1968; mass losses accelerated from 0.42 ± 0.20 m w.e. a−1 to 0.60 ± 0.20 m w.e. a−1 between 1968–2000 and 2000–2013, with thinning noticeably greater on the debris-covered ice than the clean ice. Surface-elevation changes can be influenced by ice cliffs, as well as debris cover and land- or lake-terminating glaciers. Changes showed spatial and temporal heterogeneity and a substantial correlation with climate warming and decreased precipitation.

scholarly journals Supraglacial debris thickness variability: Impact on ablation and relation to terrain properties

2018 ◽  
Author(s):  
Lindsey I. Nicholson ◽  
Michael McCarthy ◽  
Hamish Pritchard ◽  
Ian Willis
Keyword(s):  
Slope Failure ◽  
Spatial Scales ◽  
Slope Aspect ◽  
Small Scale ◽  
Main Process ◽  
Simple Relationship ◽  
Glacier Surface ◽  
Covered Area ◽  
Thickness Variability ◽  
Ground Penetrating

Abstract. Shallow ground penetrating radar (GPR) surveys are used to characterize the small-scale spatial variability of supraglacial debris thickness on a Himalayan glacier. Debris thickness varies widely over short spatial scales. Comparison across sites and glaciers suggests that the skewness and kurtosis of the debris thickness frequency distribution decrease with increasing mean debris thickness, and we hypothesise that this is related to the degree of gravitational reworking the debris cover has undergone, and is therefore a proxy for the maturity of surface debris covers. In the cases tested here, using a single mean debris thickness value instead of accounting for the observed small-scale debris thickness variability underestimates modelled midsummer sub-debris ablation rates by 11–30 %. While no simple relationship is found between measured debris thickness and morphometric terrain parameters, analysis of the GPR data in conjunction with high-resolution terrain models provides some insight to the processes of debris gravitational reworking. Periodic sliding failure of the debris, rather than progressive mass diffusion, appears to be the main process redistributing supraglacial debris. The incidence of sliding is controlled by slope, aspect, upstream catchment area and debris thickness via their impacts on predisposition to slope failure and meltwater availability at the debris-ice interface. Slope stability modelling suggests that the percentage of the debris-covered glacier surface area subject to debris instability can be considerable at glacier scale, indicating that up to 22 % of the debris covered area is susceptible to developing ablation hotspots associated with patches of thinner debris.

Estimation of PM10 Distribution using Landsat 7 ETM+ Remote Sensing Data

2017 ◽  
Vol 6 (1) ◽  
pp. 2246-2252 ◽  
Author(s):  
Ajay Roy ◽  
◽  
Anjali Jivani ◽  
Bhuvan Parekh ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Landsat 7

scholarly journals Imaging Spectroscopy for Conservation Applications

2021 ◽  
Vol 13 (2) ◽  
pp. 292
Author(s):  
Megan Seeley ◽  
Gregory P. Asner
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Case Studies ◽  
Spatial Scales ◽  
Imaging Spectroscopy ◽  
Remote Sensing Data ◽  
Decision Makers ◽  
High Spectral Resolution ◽  
Conservation Areas ◽  
Broad Array

As humans continue to alter Earth systems, conservationists look to remote sensing to monitor, inventory, and understand ecosystems and ecosystem processes at large spatial scales. Multispectral remote sensing data are commonly integrated into conservation decision-making frameworks, yet imaging spectroscopy, or hyperspectral remote sensing, is underutilized in conservation. The high spectral resolution of imaging spectrometers captures the chemistry of Earth surfaces, whereas multispectral satellites indirectly represent such surfaces through band ratios. Here, we present case studies wherein imaging spectroscopy was used to inform and improve conservation decision-making and discuss potential future applications. These case studies include a broad array of conservation areas, including forest, dryland, and marine ecosystems, as well as urban applications and methane monitoring. Imaging spectroscopy technology is rapidly developing, especially with regard to satellite-based spectrometers. Improving on and expanding existing applications of imaging spectroscopy to conservation, developing imaging spectroscopy data products for use by other researchers and decision-makers, and pioneering novel uses of imaging spectroscopy will greatly expand the toolset for conservation decision-makers.

scholarly journals Machine-Learning Classification of Soil Bulk Density in Salt Marsh Environments

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4408
Author(s):  
Iman Salehi Hikouei ◽  
S. Sonny Kim ◽  
Deepak R. Mishra
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Salt Marsh ◽  
Bulk Density ◽  
Remote Sensing Data ◽  
Soil Bulk Density ◽  
Soil Samples ◽  
Marsh Soil ◽  
Landsat 7 ◽  
Salt Marsh Soil

Remotely sensed data from both in situ and satellite platforms in visible, near-infrared, and shortwave infrared (VNIR–SWIR, 400–2500 nm) regions have been widely used to characterize and model soil properties in a direct, cost-effective, and rapid manner at different scales. In this study, we assess the performance of machine-learning algorithms including random forest (RF), extreme gradient boosting machines (XGBoost), and support vector machines (SVM) to model salt marsh soil bulk density using multispectral remote-sensing data from the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) platform. To our knowledge, use of remote-sensing data for estimating salt marsh soil bulk density at the vegetation rooting zone has not been investigated before. Our study reveals that blue (band 1; 450–520 nm) and NIR (band 4; 770–900 nm) bands of Landsat-7 ETM+ ranked as the most important spectral features for bulk density prediction by XGBoost and RF, respectively. According to XGBoost, band 1 and band 4 had relative importance of around 41% and 39%, respectively. We tested two soil bulk density classes in order to differentiate salt marshes in terms of their capability to support vegetation that grows in either low (0.032 to 0.752 g/cm3) or high (0.752 g/cm3 to 1.893 g/cm3) bulk density areas. XGBoost produced a higher classification accuracy (88%) compared to RF (87%) and SVM (86%), although discrepancies in accuracy between these models were small (<2%). XGBoost correctly classified 178 out of 186 soil samples labeled as low bulk density and 37 out of 62 soil samples labeled as high bulk density. We conclude that remote-sensing-based machine-learning models can be a valuable tool for ecologists and engineers to map the soil bulk density in wetlands to select suitable sites for effective restoration and successful re-establishment practices.

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