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Ghose, M. K.
- Estimation of Pyrogenic Carbon Emissions from Forests of Sikkim Himalaya, India:A Geoinformatics Approach
Abstract Views :241 |
PDF Views:91
Authors
Pradeep Kumar
1,
M. K. Ghose
2
Affiliations
1 Forests, Environment and Wildlife Management Department, Government of Sikkim, Deorali, Gangtok 737 102, IN
2 Sikkim Manipal University, Gangtok 737 102, IN
1 Forests, Environment and Wildlife Management Department, Government of Sikkim, Deorali, Gangtok 737 102, IN
2 Sikkim Manipal University, Gangtok 737 102, IN
Source
Current Science, Vol 112, No 09 (2017), Pagination: 1864-1872Abstract
With a view to understanding the micro-level mechanisms and lay the future path for improved carbon emission estimations from forest fires, we estimate fire emissions in Sikkim Himalaya, India. Remote sensing and geographical information system were used for fire scar identification, by mapping the multiple strata-based carbon density and partitioning the forest carbon into multiple pools. Fraction of carbon consumed in fire was further partitioned into the processes of flaming and smouldering. The estimation of trace gases of carbon dioxide, carbon monoxide and methane was made accordingly.Keywords
Carbon Emissions, Forest Fire, Geoinformatics Approach, Remote Sensing.Full Text
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Abstract Views :251 |
PDF Views:73
Authors
Pradeep Kumar
1,
M. K. Ghose
2
Affiliations
1 Forests, Environment and Wildlife Management Department, Government of Sikkim, Gangtok 737 102, IN
2 Sikkim Manipal University, Gangtok 737 102, IN
1 Forests, Environment and Wildlife Management Department, Government of Sikkim, Gangtok 737 102, IN
2 Sikkim Manipal University, Gangtok 737 102, IN
Source
Current Science, Vol 112, No 10 (2017), Pagination: 2043-2050Abstract
Sequestration of carbon through forests is an important aspect in global climate change mitigation. Assessment of carbon in forests using remote sensing and GIS tools is one of the most important aspects of rapid and verifiable methodologies. A number of studies have shown the utility of spectral (vegetation) indices like NDVI in the assessment of forest carbon. However, there are limitations to this approach. The mountainous topography and high biodiversity affect the spectral values in pixels in multiple ways. The present article aims to test the validity of use of vegetation indices in high-biodiversity forests in mountains by modelling the ground based forest carbon measurement with vegetation indices of NDVI, EVI, SAVI and MSAVI in a multi-sensor, multi-season data environment with multiple regression methods like linear, power, logarithmic, polynomial and exponential. It is found that all the regressions have a poor coefficient of determination not even exceeding 0.2. It is concluded that the remote sensing-based spectral vegetation indices alone cannot be a proxy for forest carbon calculators in high biodiversity mountain forests.Keywords
Biodiversity, Forest Carbon, Mountain, Remote Sensing, Vegetation Indices.Full Text
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