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Original Articles

Accuracy assessment of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions

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Pages 5863-5878 | Received 13 Sep 2006, Accepted 23 Oct 2007, Published online: 20 Sep 2008
 

Abstract

Snow cover information is an essential parameter for a wide variety of scientific studies and management applications, especially in snowmelt runoff modelling. Until now NOAA and IRS data were widely and effectively used for snow‐covered area (SCA) estimation in several Himalayan basins. The suit of snow cover products produced from MODIS data had not previously been used in SCA estimation and snowmelt runoff modelling in any Himalayan basin. The present study was conducted with the aim of assessing the accuracy of MODIS, NOAA and IRS data in snow cover mapping under Himalayan conditions. The total SCA was estimated using these three datasets for 15 dates spread over 4 years. The results were compared with ground‐based estimation of snow cover. A good agreement was observed between satellite‐based estimation and ground‐based estimation. The influence of aspect in SCA estimation was analysed for the three satellite datasets and it was observed that MODIS produced better results. Snow mapping accuracy with respect to elevation was tested and it was observed that at higher elevation MODIS sensed more snow and proved better at mapping snow under mountain shadow conditions. At lower elevation, IRS proved better in mapping patchy snow cover due to higher spatial resolution. The temporal resolution of MODIS and NOAA data is better than IRS data, which means that the chances of getting cloud‐free scenes is higher. In addition, MODIS has an automated snow‐mapping algorithm, which reduces the time and errors incorporated during processing satellite data manually. Considering all these factors, it was concluded that MODIS data could be effectively used for SCA estimation under Himalayan conditions, which is a vital parameter for snowmelt runoff estimation.

Acknowledgements

Ajanta Goswami was supported by the Council of Scientific and Industrial Research, India under the CSIR‐JRF Fellowship Grant No 9/143 (495)/04‐EMR‐I. The authors are thankful to Bhakra Beas Management Board (BBMB), Nangal, India for providing the air temperature data used in this study. Thanks are due to Santosh Panda, research scholar, IIT Roorkee for providing timely help and information related to this work.

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