Data Set ID: 
HMA_Glacier_dH

High Mountain Asia Gridded Glacier Thickness Change from Multi-Sensor DEMs, Version 1

This data set contains gridded thickness changes for approximately 650 Himalayan glaciers between 1975 and 2000, and 1040 Himalayan glaciers between 2000 and 2016. The data were derived from KH-9 HEXAGON and ASTER digital elevation models (DEMs), by fitting robust linear trends to time series of elevation pixels over the glacier surfaces.

This is the most recent version of these data.

Version Summary: 

Initial release

STANDARD Level of Service

Data: Data integrity and usability verified

Documentation: Key metadata and user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools

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Parameter(s):
  • GLACIERS/ICE SHEETS > GLACIER THICKNESS/ICE SHEET THICKNESS
Data Format(s):
  • TIFF
  • NetCDF
Spatial Coverage:
N: 34.4, 
S: 27.4, 
E: 92.9, 
W: 75.4
Platform(s):HEXAGON KH-9, Terra
Spatial Resolution:
  • 30 m x 30 m
Sensor(s):ASTER, CAMERA
Temporal Coverage:
  • 1 January 1974 to 31 December 2017
Version(s):V1
Temporal ResolutionVariesMetadata XML:View Metadata Record
Data Contributor(s):Joshua Maurer, Summer Rupper, Joerg Schaefer

Geographic Coverage

Other Access Options

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As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Maurer, J., S. Rupper, and J. Schaefer. 2018. High Mountain Asia Gridded Glacier Thickness Change from Multi-Sensor DEMs, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/GGGSQ06ZR0R8. [Date Accessed].

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No technical references available for this data set.

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Filter and order from a data set web page
Many NSIDC data set web pages provide the ability to search and filter data with spatial and temporal contstraints using a map-based interface. This article outlines how to order NSIDC DAAC data using advanced searching and filtering.  Step 1: Go to a data set web page This article will use the... read more