Tropical forests store over 40% of the terrestrial carbon and play a major role in the global carbon cycle. A large part of this carbon is sequestered in aboveground biomass (hereafter referred to as AGB or biomass), contributing towards climate regulation. Accurate and reliable forest biomass stockestimation is critical in understanding forest role to regional carbon cycles. So far, the total biomass in Almora District ecosystems is often under-estimated. This study develops to model the relationship between the biomass and the NDVI using both ground based and geospatial technology methods. To achieve this objective, NDVI, were computed from the newly launched Landsat 8 OLI satellite data and used in this study. Results showed a significant relationship (α = 0.05) between biomassNDVI. On the contrary, no significant (p >0.05) relationship was established between remotely sensed vegetation indices and the biomass. These findings imply that aboveground woody biomass stocks can be used as a proxy to estimate biomass in tropical forest. Overall, these findings underscore the potential and significance of remote sensing data in understanding Almora District ecosystems contribution to the global carbon cycle.

Keywords: vegetation indices, woody biomass, satellite data

In the present scenario of climate change, climatologists are concerned with the soaring rates of deglaciation in high mountain areas. Being the most sensitive climate change indicators, there has been a phenomenal increase in the interpretation of changing glaciers using remote sensing images. However, the data generated needs to be validated and the inferences drawn must be supported by logical explanations to facilitate the understanding of the relevant processes. The present study investigates the frontal (snout)changes of Pindari glacier through a comprehensive analysis of remote sensing data and field validations. Regional case studies of glacier front changes demonstrate that the Himalayan glaciers are retreating;however, the rate of retreat is variable over time. The Pindari glacier has witnessed highest rate of retreat(73.27m)during 2009-2010. The in-situ measurements have recorded a high recession during 1845 to 1958, that significantly decreased during 1958-1966. Subsequently, a gradual increase in the rate of recession till 2010 has been reported and is evident in remote sensing data also. However, since 2010, the rate of retreat has again slowed down. The present observations may be interpreted as direct consequence of the rapidly changing climate wherein the glaciers are witnessing a negative mass balance and hence the retreat. Our data is in accordance with other local and regional studies and imply mass wasting of glaciers as a response to global climate warming.

We have studied bank erosion and accretion along the Putharjhora-Kranti reaches of the Chel River, piedmont Sikkim Himalaya using SOI topographical maps of 1955 and 1970, and Landsat images of 1976, 1987, 1994, 2005, 2010 and 2017. Extensive field survey was also conducted to supplement the study and thereby verify the findings derived from GIS analysis. We have deployed overlay method for determination of areas of bank erosion and accretion by superimposing and comparing sequential changes in the position of banks in these years. We identified 342 erosion plots (all plots >1m² has been considered, plots <1m² were neglected). The total area of bank erosion from 1955-1970 equaled 34.77 km², of which 12.4 km² occurred along the left bank and 22.4 km² along the right bank. The total area of bank retreat amounted to 13.65 km² during 1955 to 1970, 9.61 km² from 1970 to 1976, 1.45 km² from 1976 to 1987, 3.43 km² from 1987 to 1994, 3.55 km² from 1994 to 2005, 1.93 km² from 2005 to 2010, and 1.15 km² from 2010 to 2017. The annual rate of bank erosion from 1955 to 1970 averaged 0.92 km²/y, and increased to the highest value of 1.61 km²/y during 1970 to 1976, then decreased to the lowest derived value of 0.13 km²/y during 1976 to 1987, 0.5 km²/y from 1987 to 1994, 0.33 km²/y during 1994-2005, 0.38 km²/y from 2005 to 2010, and 0.17 km²/y from 2010 to 2017. Spatially, the Oodlabari Bazaar-Nipuchapur Tea Garden section has suffered the most extensive bank erosion whereas Rajadanga-Kranti section of the study reach sustained minimal bank erosion. Further, right bank has recorded larger erosion compared to the left. A brief analysis of possible sources of error in estimation for bank erosion area has also been provided.

Keywords: Bank erosion and accretion, River Chel, Putharjhora-Kranti, Overlay method