process of capture and long-term storage of atmospheric carbon dioxide (Sedjo and
Sohngen 2012) in soil. Soil can be considered as the largest pool of terrestrial
organic carbon in the biosphere storing more CO 2 (2200 Pg) than plants (Batjes
1996). Forest and forest soil play an important role in the global carbon balance
(Pareta and Pareta 2011 and Jha et al. 2003). Soil stores 2.5–3.0 times higher as that
stored in the plants and two to three times more than the atmospheric CO 2
(Davidson et al. 2000). The forest soils are one of the major carbon sink in earth
having higher content of organic carbon (Dey 2005).
Through the process of photosynthesis, plants assimilate carbon and return to the
soil as litter and gets stored as soil organic matter (Negi and Gupwta 2010).
Accurate estimation of soil organic carbon pool helps for climate change study and
prediction of variation in climate change and its effect on local and global climate as
well as biodiversity. The remote sensing technologies are being used for preparation
of land use land cover (LULC) map and area estimation under different land use
practices. Geographical information system (GIS) technology is useful for spatial
analysis and preparation of SOC pool map. The present study is an attempt to
estimate the carbon sequestration stock in forest soils of various land use system in
Honnaver taluk of Uttar Kannada district (Karnataka).
2 Material and Method
The study was conducted in Honnaver taluka of Uttar Kannada district, Karnataka,
India. The study region lies between 14° 8′ 0″ N to 14° 25′ N Latitude and 74° 25′ E
to 74° 45′ E Longitude covering a surface area about 68520 ha. The study area is
shown in Fig. 1.
The toposheets covering the study area with scale 1:50,000 were procured from
SOI Bangalore. IRS LISS-3 satellite image path 097 row 063 dated 22 January 2010
spatial resolutions with 23.5 × 23.5 m procured from NRSC Hyderabad. The image
was atmospheric and corrected to obtain actual reflectance value of the earth surface
and also topographic normalization procedure was performed to reduce hill shade
effects on the images using ERDAS IMAGINE 2011 software. The toposheet was
georeferenced with projected coordinate system (WGS84). All georeferenced
toposheet were clipped and mosaic to cover geographical area of the study region.
Digitization of the study region boundary was done on mosaic toposheet and the same
boundary was used to subset study area from the satellite image. The images were
classified based on GPS data point using supervised calcifications method. Totally six
classes were classified, i.e. dense forest, sparse forest, open land, agriculture land,
water body and settlement. Out of these six LULC classes dense forest, sparse forest,
open land and agriculture land were selected for the estimation of soil organic pool.
Soil samples were collected from different land use land class area, viz., dense
forest, sparse forest, open land and agriculture land. While taking the samples the
land terrain was considered. In sloppy land, the number samples were taken along
the slope from top to bottom and in case of flat land grid at equidistance were
440
A.G. Koppad and P. Tikhile
Sohngen 2012) in soil. Soil can be considered as the largest pool of terrestrial
organic carbon in the biosphere storing more CO 2 (2200 Pg) than plants (Batjes
1996). Forest and forest soil play an important role in the global carbon balance
(Pareta and Pareta 2011 and Jha et al. 2003). Soil stores 2.5–3.0 times higher as that
stored in the plants and two to three times more than the atmospheric CO 2
(Davidson et al. 2000). The forest soils are one of the major carbon sink in earth
having higher content of organic carbon (Dey 2005).
Through the process of photosynthesis, plants assimilate carbon and return to the
soil as litter and gets stored as soil organic matter (Negi and Gupwta 2010).
Accurate estimation of soil organic carbon pool helps for climate change study and
prediction of variation in climate change and its effect on local and global climate as
well as biodiversity. The remote sensing technologies are being used for preparation
of land use land cover (LULC) map and area estimation under different land use
practices. Geographical information system (GIS) technology is useful for spatial
analysis and preparation of SOC pool map. The present study is an attempt to
estimate the carbon sequestration stock in forest soils of various land use system in
Honnaver taluk of Uttar Kannada district (Karnataka).
2 Material and Method
The study was conducted in Honnaver taluka of Uttar Kannada district, Karnataka,
India. The study region lies between 14° 8′ 0″ N to 14° 25′ N Latitude and 74° 25′ E
to 74° 45′ E Longitude covering a surface area about 68520 ha. The study area is
shown in Fig. 1.
The toposheets covering the study area with scale 1:50,000 were procured from
SOI Bangalore. IRS LISS-3 satellite image path 097 row 063 dated 22 January 2010
spatial resolutions with 23.5 × 23.5 m procured from NRSC Hyderabad. The image
was atmospheric and corrected to obtain actual reflectance value of the earth surface
and also topographic normalization procedure was performed to reduce hill shade
effects on the images using ERDAS IMAGINE 2011 software. The toposheet was
georeferenced with projected coordinate system (WGS84). All georeferenced
toposheet were clipped and mosaic to cover geographical area of the study region.
Digitization of the study region boundary was done on mosaic toposheet and the same
boundary was used to subset study area from the satellite image. The images were
classified based on GPS data point using supervised calcifications method. Totally six
classes were classified, i.e. dense forest, sparse forest, open land, agriculture land,
water body and settlement. Out of these six LULC classes dense forest, sparse forest,
open land and agriculture land were selected for the estimation of soil organic pool.
Soil samples were collected from different land use land class area, viz., dense
forest, sparse forest, open land and agriculture land. While taking the samples the
land terrain was considered. In sloppy land, the number samples were taken along
the slope from top to bottom and in case of flat land grid at equidistance were
440
A.G. Koppad and P. Tikhile