At the watershed level, crown projection area (CPA) vs. basal area (BA) model was developed and validated. At the watershed level, for CPA delineation, region growing technique was adopted. GeoEye-1 images captured on 15 December, 2012 was used.

In the watershed level, existing lease hold forest boundary delineated to know the exact area under the lease hold forest. GeoEye-2009 image used for this pupose in the Kayerkhola watershed

Large landslide dams are one of the most disastrous natural phenomena in mountainous regions all over the world Such dams are formed most commonly in tectonically active settings where high mountains border narrow and steep valleys and earthquakes occur frequently. Landslide dams are very diverse in terms of their formation, geotechnical characteristics, longevity, stability, and flood hazard. The two major causes of landslide dam formation are precipitation and earthquake. About 50% of dam-forming landslides are brought about by rainstorms and snowmelts, 40% by earthquakes, and 10% by other factors Geometry of valley in relation to geometry and volume of debris and discharge of damming river are some of the factors which are responsible for the development of landslide dams. Schuster et al. (1998) mentioned four groups of governing factors responsible for the spatial distribution of landslide dams. They are i) seismic intensity, ii) slope gradient and topography, iii) lithology and weathering properties, and iv) soil moisture and groundwater content. Landslide dams are generated by various types of mass movements, which range from rock falls and rockslides in steep walled, narrow canyons to earth slumps in flat river lowlands. Managing landslide-dam hazards requires an understanding of the temporal and spatial scales on which such phenomena occur. Many previous works on landslide dams have been mainly descriptive in character, and have produced a multitude of documented case studies and inventories (e.g. Costa and Schuster, 1988; Costa and Schuster, 1991). More recent work is focused on quantitative methods of determining the post-formation development, in particular, the controls on dam longevity.

Large landslide dams are one of the most disastrous natural phenomena in mountainous regions all over the world Such dams are formed most commonly in tectonically active settings where high mountains border narrow and steep valleys and earthquakes occur frequently. Landslide dams are very diverse in terms of their formation, geotechnical characteristics, longevity, stability, and flood hazard. The two major causes of landslide dam formation are precipitation and earthquake. About 50% of dam-forming landslides are brought about by rainstorms and snowmelts, 40% by earthquakes, and 10% by other factors Geometry of valley in relation to geometry and volume of debris and discharge of damming river are some of the factors which are responsible for the development of landslide dams. Schuster et al. (1998) mentioned four groups of governing factors responsible for the spatial distribution of landslide dams. They are i) seismic intensity, ii) slope gradient and topography, iii) lithology and weathering properties, and iv) soil moisture and groundwater content. Landslide dams are generated by various types of mass movements, which range from rock falls and rockslides in steep walled, narrow canyons to earth slumps in flat river lowlands. Managing landslide-dam hazards requires an understanding of the temporal and spatial scales on which such phenomena occur. Many previous works on landslide dams have been mainly descriptive in character, and have produced a multitude of documented case studies and inventories (e.g. Costa and Schuster, 1988; Costa and Schuster, 1991). More recent work is focused on quantitative methods of determining the post-formation development, in particular, the controls on dam longevity.

At the watershed level, crown projection area (CPA) vs. basal area (BA) model was developed and validated. At the watershed level, for CPA delineation, region growing technique was adopted. GeoEye-1 images captured on 2nd November, 2009 was used.

The Above Ground Biomass(AGB) data obtained from the model was converted into carbon stock by applying a conversion factor of 0.47, as suggested by IPCC.

The Gorkha earthquake (M 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing 9,000 and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and geologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision makers. We mapped 4312 co-seismic and post-seismic landslides and surveyed 491 glacier lakes for earthquake damage, but found only 9 landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities are correlated with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.

Leaf Area Index (LAI) generated based on Landsat-8 the OLI cloud free images. To generate tree canopy height map, a density scatter graph between the Geoscience Laser Altimeter System (GLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat) estimated maximum height and Landsat LAI nearest to the center coordinates of the GLAS shots show a moderate but significant exponential correlation (31.211*LAI0.4593, R2= 0.33, RMSE=13.25 m).

From the field well distributed circular (750m2 and 500m2), 1124 field plots (0.001% representation of forest cover) measured which were used for estimation AGB (ton/ha) using Sharma et al. (1990) proposed equations for all tree species of Nepal. A satisfactory linear relationship (AGB = 8.7018*Hmax-101.24, R2=0.67, RMSE=7.2 ton/ha) achieved between maximum canopy height (Hmax) and AGB (ton/ha).

The Gorkha earthquake (M 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing 9,000 and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and geologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision makers. We mapped 4312 co-seismic and post-seismic landslides and surveyed 491 glacier lakes for earthquake damage, but found only 9 landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities are correlated with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.