Limits...
Optical Remote Sensing of Glacier Characteristics: A Review with Focus on the Himalaya

View Article: PubMed Central

ABSTRACT

Asterr: The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the dvanced paceborne hermal mission and eflection adiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya.

No MeSH data available.


An example of the relationship between accumulation area ratio and mass balance, used to derive the steady-state AAR for Shaune Garang and Gor Garang glaciers [105].
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3675549&req=5

f1-sensors-08-03355: An example of the relationship between accumulation area ratio and mass balance, used to derive the steady-state AAR for Shaune Garang and Gor Garang glaciers [105].

Mentions: The AAR/ELA method described in detail in [28] focuses on finding a relationship between AAR and mass balance. Then the steady-state AAR (the value at which the glacier is in equilibrium with the climate) can be established for a particular glacier or glaciers within one climatic region [28]. For individual glaciers, the method involves the following steps: 1) compiling field-based mass balance measurements (bn) and AAR for individual glaciers in a region; 2) plotting bn vs. AAR for each glacier, and finding the regression lines of the form:(1)Bn=a*AAR+bwhere Bn is the specific mass balance in water equivalent (m) and AAR is the accumulation area ratio, as shown in Fig. 1; 3) obtaining the value of AAR for which mass balance is zero from eqn.1 - this yields the steady-state AAR (AAR0), the value at which a glacier is in equilibrium with the climate. When the AAR method is applied for several glaciers in the same climatic zone, a single regression line is plotted, from which the regional AAR0 is obtained. For example, [28] used Landsat imagery from several glaciers in the Western Himalaya for different years, and found a generalized value of AAR0 of 0.44 for the Western Himalaya. This is different than the AAR0 of 0.67 typical of alpine glaciers [26] or an AAR0 of 0.82 for tropical glaciers [104]. These differences in the steady-state AAR values show the need for applying this method for each region separately.


Optical Remote Sensing of Glacier Characteristics: A Review with Focus on the Himalaya
An example of the relationship between accumulation area ratio and mass balance, used to derive the steady-state AAR for Shaune Garang and Gor Garang glaciers [105].
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675549&req=5

f1-sensors-08-03355: An example of the relationship between accumulation area ratio and mass balance, used to derive the steady-state AAR for Shaune Garang and Gor Garang glaciers [105].
Mentions: The AAR/ELA method described in detail in [28] focuses on finding a relationship between AAR and mass balance. Then the steady-state AAR (the value at which the glacier is in equilibrium with the climate) can be established for a particular glacier or glaciers within one climatic region [28]. For individual glaciers, the method involves the following steps: 1) compiling field-based mass balance measurements (bn) and AAR for individual glaciers in a region; 2) plotting bn vs. AAR for each glacier, and finding the regression lines of the form:(1)Bn=a*AAR+bwhere Bn is the specific mass balance in water equivalent (m) and AAR is the accumulation area ratio, as shown in Fig. 1; 3) obtaining the value of AAR for which mass balance is zero from eqn.1 - this yields the steady-state AAR (AAR0), the value at which a glacier is in equilibrium with the climate. When the AAR method is applied for several glaciers in the same climatic zone, a single regression line is plotted, from which the regional AAR0 is obtained. For example, [28] used Landsat imagery from several glaciers in the Western Himalaya for different years, and found a generalized value of AAR0 of 0.44 for the Western Himalaya. This is different than the AAR0 of 0.67 typical of alpine glaciers [26] or an AAR0 of 0.82 for tropical glaciers [104]. These differences in the steady-state AAR values show the need for applying this method for each region separately.

View Article: PubMed Central

ABSTRACT

Asterr: The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the dvanced paceborne hermal mission and eflection adiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya.

No MeSH data available.