Cloud Cover

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. 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.Read More

Attachment	Size
Automated mapping of snow cover using IRS - IC data (1996-97)	1.01 MB

Tags:

Content Type: Research
Category: Clouds, Digital Elevation Model (DEM), Dozier's Method, Flood Control, Hydrological Cycle, Hydropower Planning, Integrated Land and Water Information Systems (ILWIS), Proximity Analysis, Remote Sensing, Reservoir, Reservoir Operation, River Basin, Runoff, Slope, Snow Covered Areas (SCA), Snow Cover Estimation, Snow Melt Mapping, Snow Melt Runoff, Sub-basin, Topography, Water Use, Cloud Cover, Drainage, Hydrology, Rivers, Water Bodies, Water Resources
Author: National Institute of Hydrology
Source: National Institute of Hydrology
Location / Time: 1996, 1997, India, Satluj, Spiti
Difficulty Level: Expert

Background on the Meteorological Datasets

We foresee that this data can be useful in making rainwater harvesting and water balance estimates, in various research areas, climate change adaptation studies and more. We also believe in the democratising effect of having this kind of data freely available to the general public.Read More

Tags:

Content Type: Data
Category: Climate, Cloud Cover, Diurnal Temperature Range, Ecosystems, Evapotranspiration, Geographical Information Systems (GIS), Ground Frost Frequency, Humidity, Meteorological Data, Potential Evapotranspiration, Precipitation, Rainfall, Rainwater Harvesting, Rainwater Harvesting Potential, Reference Crop Evapotranspiration, Temperature, Vapour Pressure, Water Balance, Water Balance Demo, Water Balance Modelling, Weather, Wet Day Frequency
Associated People / Organizations: Philip D. Jones, School of Environmental Sciences, Timothy D. Mitchell, Tyndall Centre for Climate Change Research, University of East Anglia
Location / Time: 1901, 2002, India
Difficulty Level: Expert
Special Tags: General

Meteorological Datasets

Meteorological data is essential for water resource planning and research. In India, this data is difficult to obtain for the average citizen. In this application, entire datasets for various meteorological indicators from 1901 to 2002, for any part of India, is made available for users, in a simple format.Read More

Tags:

Content Type: Data
Category: Climate, Cloud Cover, Diurnal Temperature Range, Ecosystems, Evapotranspiration, Geographical Information Systems (GIS), Ground Frost Frequency, Humidity, Meteorological Data, Potential Evapotranspiration, Precipitation, Rainfall, Rainwater Harvesting, Rainwater Harvesting Potential, Reference Crop Evapotranspiration, Temperature, Vapour Pressure, Water Balance, Water Balance Demo, Water Balance Modelling, Water Resources, Weather, Wet Day Frequency
Associated People / Organizations: University of East Anglia, Tyndall Centre for Climate Change Research, Timothy D. Mitchell, School of Environmental Sciences, Philip D. Jones, Indian Meteorological Department, Government of Rajasthan
Location / Time: India
Difficulty Level: Expert
Special Tags: General

Search India Water Portal

Cloud Cover

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

Background on the Meteorological Datasets

Meteorological Datasets

About the Portal

Subscribe to this Channel

Channels

Community

Community

About IWP

Other Portals