Cryosphere Initiative

The Cryosphere Initiative hosted within the Regional Programme on Cryosphere and Atmosphere of the International Centre for Integrated Mountain Development (ICIMOD) focuses on the monitoring of glaciers, snow, permafrost, glacial lakes, and glacio-hydrology with an emphasis on in situ measurements, remote sensing, and modelling.

The Cryosphere Initiative, with support from the Norwegian Ministry of Foreign Affairs and partners, works to establish ICIMOD as a Regional Cryosphere Knowledge Hub to collate and share the knowledge of partners working in the region. Working with regional and international institutions that focus on cryosphere and cryosphere hydrology, the Initiative is enhancing the capacity of institutions in ICIMOD’s regional member countries to generate and access relevant data and knowledge about the cryosphere and sustained cryosphere monitoring. This work will contribute to the development of effective measures and policies for water resources and risk management in the HKH region.

Objectives

  • To improve knowledge and understanding of the HKH cryosphere and the impacts of climate change on water resources and hazards, and 
  • To build regional capacity for cryospheric monitoring in the region.


Publications

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Updates

Datasets

The 1000 m MODIS imagery showing a daily cloud cover of the HKH region. The image is generated using MODIS (NASA) algorithms to MODIS data received on ICIMOD's receiving station.


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The 1000 m MODIS imagery showing a daily cloud cover of the HKH region. The image is generated using MODIS (NASA) algorithms to MODIS data received on ICIMOD's receiving station.


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The 500 m MODIS imagery showing a daily snow cover of the HKH region. The image is generated using MODIS (NASA) algorithms to MODIS data received on ICIMOD's receiving station.


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In order to monitor changes in the glaciers in the Bhutan Himalaya, a repeat decadal glacier inventory was carried out from Landsat images of 1977/78(1980), 1990, 2000 and 2010. The base map of glaciers was obtained by object-based image classification method using the multispectral Landsat images of 2010. This method is used separately to delineate clean-ice and debris covered glaciers with some manual editing. Glacier polygons of 2000, 1990 and 1980 were obtained by manual editing on 2010 by separately overlaying respective years.


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The 1000 m MODIS imagery showing a daily cloud cover of the HKH region. The image is generated using MODIS (NASA) algorithms to MODIS data received on ICIMOD's receiving station.


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The 1000 m MODIS imagery showing a daily cloud cover of the HKH region. The image is generated using MODIS (NASA) algorithms to MODIS data received on ICIMOD's receiving station.


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Digital polygon data of Glaciers of Bhutan in 2000. This dataset is created using Landsat TM and ETM+, imageries of 2000. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.


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Digital polygon data of Glaciers of Bhutan in 1990. This dataset is created using Landsat MSS, imageries of 1990. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.


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Digital polygon data of Glaciers of Bhutan in 1980. This dataset is created using Landsat MSS imageries of 1980. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.


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Digital polygon data of Glaciers of Bhutan in 1980, 1990, 2000 and 2010. This dataset is created using Landsat MSS, TM and ETM+ imageries of respective years. The glacier outlines was derived semi-automatically using object-based image classification (OBIC ) method separately for clean ice and debris cover and further editing and validation was done carefully by draping over the high resolution images from Google Earth.


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Science applications

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