2006International Journal of Remote SensingRequires access

Algorithm to monitor snow cover using AWiFS data of RESOURCESAT‐1 for the Himalayan region

Anil V. Kulkarni, Devendra Singh, Pratistha Mathur, V. D. Mishra

Open publisher page 133 citations

Abstract

Seasonal snow cover is one of the important natural resources of the Himalayas. This is an important parameter in assessing the availability of water in the Himalayan Rivers, forecasting and assessing avalanches and numerous other applications. In the present paper, the normalized difference snow index (NDSI) technique is discussed to monitor snow cover using an AWiFS sensor on RESOURCESAT–1, a remote sensing satellite recently launched by India. AWiFS is a unique sensor, providing data of 56 m spatial resolution at 5‐day intervals. Satellite data and field investigations were carried out to assess the correct NDSI value representing snow. This technique is particularly useful for the Himalayan region as it can also be applied under mountain shadow conditions. This is possibly due to reflectance from diffuse radiation in shadow areas. An algorithm is developed to provide changes in the areal extent of snow at intervals of 5 and 10 days. In the 5‐daily product, snow extent will be generated scene‐wise. In this product, snow and cloud extent will be given. In the 10‐daily product, three scenes will be analysed and a basin‐wise estimate of the maximum snow extent will be available.

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What this paper is about

Seasonal snow cover is one of the important natural resources of the Himalayas. This is an important parameter in assessing the availability of water in the Himalayan Rivers, forecasting and assessing avalanches and numerous other applications. In the present paper, the normalized difference snow index (NDSI) technique is discussed to monitor snow cover using an AWiFS sensor on RESOURCESAT–1, a remote sensing satellite recently launched by India. AWiFS is a unique sensor, providing data of 56 m spatial resolution at 5‐day intervals. Satellite data and field investigations were carried out to assess the correct NDSI value representing snow. This technique is particularly useful for the Himalayan region as it can also be applied under mountain shadow conditions. This is possibly due to reflectance from diffuse radiation in shadow areas. An algorithm is developed to provide changes in the areal extent of snow at intervals of 5 and 10 days. In the 5‐daily product, snow extent will be generated scene‐wise. In this product, snow and cloud extent will be given. In the 10‐daily product, three scenes will be analysed and a basin‐wise estimate of the maximum snow extent will be available.

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Available abstract

Seasonal snow cover is one of the important natural resources of the Himalayas. This is an important parameter in assessing the availability of water in the Himalayan Rivers, forecasting and assessing avalanches and numerous other applications. In the present paper, the normalized difference snow index (NDSI) technique is discussed to monitor snow cover using an AWiFS sensor on RESOURCESAT–1, a remote sensing satellite recently launched by India. AWiFS is a unique sensor, providing data of 56 m spatial resolution at 5‐day intervals. Satellite data and field investigations were carried out to assess the correct NDSI value representing snow. This technique is particularly useful for the Himalayan region as it can also be applied under mountain shadow conditions. This is possibly due to reflectance from diffuse radiation in shadow areas. An algorithm is developed to provide changes in the areal extent of snow at intervals of 5 and 10 days. In the 5‐daily product, snow extent will be generated scene‐wise. In this product, snow and cloud extent will be given. In the 10‐daily product, three scenes will be analysed and a basin‐wise estimate of the maximum snow extent will be available.

Key concepts: Snow, Remote sensing, Snow cover, Satellite, Shadow (psychology), Environmental science, Precipitation, Physical geography

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