Automated mapping of snow cover using IRS-IC data - A research report by National Institute of Hydrology

The study presents automated mapping of snow cover using a new spectral channel of Indian Remote Sensing (IRS-IC) data for the Spiti sub-basin of the Satluj river basin.

The study presents automated mapping of snow cover using a new spectral channel of Indian Remote Sensing (IRS-IC) data for the Spiti sub-basin of the Satluj river basin. Snow is an important phase of the hydrological cycle and the estimation of snowmelt runoff in the Himalayan rivers, either seasonal or daily, is of immense use in proper management and use of water resources in the basins.

A number of models have been developed for simulation and forecasting of snowmelt runoff. Data requirement of these models is quite high and conventional ground measurement in snow covered areas cannot meet these requirements because of various shortcomings like frequency of observation, point measurement not representative of large areas, hostile climate conditions and inaccessibility of areas.

Remote sensing techniques offer excellent synoptic and repetitive overviews in various spectral channels of electromagnetic spectrum and serve as a spatial data base for snow related studies these days.

The new spectral channel in the wavelength range 1.55 to 1.7 µm of the LISS-III sensor of IRS-IC (of spatial resolution 23.5 m) has been used for discriminating the snow cover areas from clouds.  A procedure, developed by Dozier, has been utilized for automated mapping of snow cover area in the basin. Dozier’s algorithm has been utilized for snow cover estimation using the remote sensing data of LISS II sensor.

However, because of the deficiency of satellite information below 0.52 µm with this sensor, it is not possible to directly identify snow in shadowed areas and areas under the clouds, and hence, an indirect method has been suggested. This method is based on the combined use of digital image processing techniques (Proximity Analysis) and topographic details.

Digital Elevation Model (DEM) for the area was developed using GIS software, ILWIS for getting the topographical details. Topographic information such as slope and aspect for each pixel was derived from DEM and used as data for the Proximity Analysis.

The study is significant as real-time and long-term forecasting of runoff in these basins can result in optimum operation of reservoirs for conservation and flood control, for planning hydropower regulation and hence optimum use of water.

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