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The river Brahmputra flowing through the state of Assam (India) floods every year. The analysis of spatial extent and temporal pattern of flood-inundated areas is of prime importance for mitigation of floods. With the development of remote sensing techniques, flood mapping for large areas can be done easily. In case of flood affected area mapping of large area it will not be feasible to use high-resolution data, because the whole area will be covered in number of scenes. Therefore use of NOAA (National Oceaongraphic Atmospheric Administrative) data is quite useful in such type of studies. NOAA-AVHRR (Advanced Very High Resolution Radiometer) data have the potential for flood monitoring due to high frequency of global coverage, wide swath, high repetivity and low cost. In this study, NOAA-AVHRR data have been used for mapping of flood-affected area during the year 2003. On the basis of spectral characteristics of land and water, a methodology for water identification is presented. The maximum spatial extent of floods, generated by compiling the available cloud free maps, is informative about flood damages. Analysis of results reveals that in the months of July and August almost 25-30% of the area was flood affected. Also the result indicates that in some districts, the flood-affected area is very high.

Stress accumulated in rocks in tectonically active areas may manifest itself as electromagnetic radiation emission and temperature variation through a process of energy transformation. Land surface temperature (LST) changes before an impending earthquake can be detected with thermal infrared (TIR) sensors such as NOAA-AVHRR, Terra/Aqua-MODIS, etc. TIR anomalies produced by 10 recent earthquakes in Iran during the period of Jun 2002-Jun 2006 in the tectonically active belt have been studied using pre-and post-earthquake NOAA-AVHRR datasets. Data analysis revealed a transient TIR rise in LST ranging 2-13°C in and around epicentral areas. The thermal anomalies started developing about 1-10 days prior to the main event depending upon the magnitude and focal depth, and disappeared after the main shock. In the case of moderate earthquakes (\6 magnitude) a dual thermal peak instead of the single rise has been observed. This may lead us to understand that perhaps pre-event sporadic release of energy from stressed rocks leads to a reduction in magnitude of the main shock. This TIR temperature increment prior to an impending earthquake can be attributed to degassing from rocks under stress or to p-hole activation in the

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Snow is a dynamic natural element, the distribution of which is largely controlled by latitude and altitude. In the tropical country like India, snow distribution is mostly controlled by altitude. The present study aims to identify the relationship between snow accumulation with elevation and aspect in rugged terrain in the Himalayan region. The river basins of four tributaries of the River Indus i.e. Satluj, Chenab, Ravi and Beas located in the western Himalaya were considered for study. Snow covered area was estimated for a period of 2 years (01 Jan 2003 to 17 Dec 2004) using MODIS 8 days' maximum snow cover products. Aspect and classified relief maps were prepared using the USGS DEM. The interrelationship between aspect, elevation and snow cover area was determined for all the four river basins and comparative analysis has been made. A 2 years average shows that Satluj has the minimum snow covered area 23%, while Chenab has the highest snow covered area i.e. 42%, Ravi and Beas has 33% and 38% respectively. The minimum elevation from where snow covered area appears has been calculated and it has been observed that in case of Satluj, snow appears at a higher elevation (1,369 m) while in Chenab snow appears at an elevation of 834 m, followed by Ravi (1,058 m) and Beas (1,264 m). It was found that aspect has a major impact on snow accumulation in the lower elevations in all the basins as compared to higher elevations. Snow accumulates most in the northwest and northeast aspect. The rate of change in snow cover with elevation is determined for all the river basins and it has been concluded that Satluj has the lowest rate of change of snow cover with elevation (1.3% per 100 m), Chenab 1.8% per 100 m, followed by Ravi 2% per 100 m and Beas (2% per 100 m).

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