Remote Sensing and GIS

Technology is starting to fill in the blanks in the scientific record for the Hindu Kush Himalayas, whose size and remoteness has served in the past as a major obstacle to data collection. 

Remote sensing technologies are providing new data sets and spatially referenced information to help scientists, development planners and policymakers make informed decisions. From forecasts about crop yields, impending droughts and natural disasters to observations of forest growth patterns and the dynamics of snow and water, the range of topics that benefit from being analysed and modelled visually is vast.  

ICIMOD is internationally regarded as a regional resource centre for geo-information and earth observation applications with a mountain focus. Over the past two decades, we have developed and shared remote sensing and geographic information systems to assist decision-making at many levels. Within our own areas of focus, such as trans-boundary landscape conservation and river basin management, geospatial science is used to expand knowledge of scientific and socio-ecological challenges and ensure that programmes are informed by the latest and most extensive data.

Staff articles

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Stories

Potentially Dangerous Glacial Lakes of Nepal

This map story lists glacial lakes of Nepal that have been categorized as potentially dangerous based publication - "Glacial Lakes and Glacial Lake Outbrust Flood in Nepal", published by ICIMOD in 2011.

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Imja lake - Fastest growing glacial lake of the HKH

This story map allows users to visualize the changes of Imja Glacial lake using a time-slider tool from 1992 to 2009 as well as it provides the basic information,charts and statistics about Imja Lake.

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Datasets

Soil loss in Koshi Basin 2010

High levels of water-induced erosion in the transboundary Himalayan river basins are contributing to substantial changes in basin hydrology and inundation. Basin-wide information on erosion dynamics is needed for conservation planning, but field-based studies are limited. This study used remote sensing (RS) data and a geographic information system (GIS) to estimate the spatial distribution of soil erosion across the entire Koshi basin. The revised universal soil loss equation (RUSLE) was used in an ArcGIS environment with rainfall erosivity, soil erodibility, slope length and steepness, cover-management, and support practice factors as primary parameters. The estimated annual erosion from the basin was around 42 million tonnes.


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Soil loss in Koshi Basin 1990

High levels of water-induced erosion in the transboundary Himalayan river basins are contributing to substantial changes in basin hydrology and inundation. Basin-wide information on erosion dynamics is needed for conservation planning, but field-based studies are limited. This study used remote sensing (RS) data and a geographic information system (GIS) to estimate the spatial distribution of soil erosion across the entire Koshi basin. The revised universal soil loss equation (RUSLE) was used in an ArcGIS environment with rainfall erosivity, soil erodibility, slope length and steepness, cover-management, and support practice factors as primary parameters. The estimated annual erosion from the basin was around 42 million tonnes.


View Metadata
Glaciers of Bhutan 1990

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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Glaciers of Nepal 2000

Digital polygon data of Glaciers of Nepal in 2000. This dataset is created using Landsat MSS, TM 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.


View Metadata
Glaciers of Bhutan 2010

Digital polygon data of Glaciers of Bhutan in 2010. This dataset is created using Landsat TM and ETM+, imageries of 2010. 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.


View Metadata
Glaciers of Nepal 2010

Digital polygon data of Glaciers of Nepal in 2010. This dataset is created using Landsat TM, ETM+ imageries of 2010. 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.


View Metadata
Glaciers of Nepal 1980

Digital polygon data of Glaciers of Nepal 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.


View Metadata
Glaciers of Bhutan 2000

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.


View Metadata
Glaciers of Bhutan 1980

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.


View Metadata
Glaciers of Nepal 1990

Digital polygon data of Glaciers of Nepal in 1990. This dataset is created using Landsat MSS, TM 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.


View Metadata

Science applications

Resource Accounting Tool

The application carries out all the analyses or geo-processings in Google Earth Engine, the Google’s cloud based platform, except for species occurrence data which are obtained directly from Global Biodiversity Information Facility (GBIF).

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Glacier Dynamics in Afghanistan

The application showcases changes in the glaciers in Afghanistan from 1990 to 2015. The interactive glacier maps were prepared for 1990, 2000, 2010, and 2015 using a uniform data set and methodology, which provide a scientific basis for understanding the changes taking place in the glacial environment in the Himalayas of Afghanistan.

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Relevant Publications

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Knowledge Hubs, Portals, and Initiatives

Meet our Experts

Mir Abdul Matin

Theme Leader, Geospatial Solutions

Birendra Bajracharya

Acting Regional Programme Manager - MENRIS

Sudip Pradhan

Programme Coordinator, Regional Database System

Finu Shrestha

Research Associate, GIS

Faisal Mueen Qamar

Remote Sensing Specialist