58
T. V. Ramachandra and S. Bharath
as evergreen, moist as well as dry deciduous, scrub, thorny, sholas, grasslands, and
mangroves in the estuarine areas. The state harbors 4500 species of flowering plants,
508 species of birds, 150 varieties of mammals, 156 reptile species, amphibians of
156 species, 405 fish species, and 330 butterflies. Soils of the state are fertile by two
major river systems (Krishna, Cauvery) and its tributaries. The state has a protected
area network of five national parks (2431.3 km
2 ) and 21 wildlife sanctuaries (3887.83
km
2 ), covering nearly 16% of forest area. Agriculture and horticulture sectors are
the backbone of the state’s economy. The state is the prime destination for IT and
BT technologies with knowledge, innovation, research, and development centers. It
has a gross domestic product (GDP) of |15.10 lakh crore (US$220 billion) as fourth
largest in India, growing at a healthy 7% per year with a per capita GDP of |207,000
(US$3,000).
3 Method
The protocol adopted to assess the carbon dynamics in Karnataka is presented in
Fig. 2. The research involved (i) assessment of land-use dynamics through spatial
data acquired using spaceborne sensors at regular intervals; (ii) field data collection to
classify remote sensing data, (iii) quantification of AGB through field measurements
of girth and height and sampling of the locations through transect based quadrat;
(iv) quantification of carbon across various forest types and soil; (v) data mining
pertaining to carbon emissions, sequestrations in forests and soils through published
literature; (vi) visualization of likely changes in carbon dynamics (a) with the current
rate of deforestation and degradation; (b) interventions with the afforestation; (c)
implementation of the proposed development projects. This was implemented in
three phases. Phase 1 focused on the land-use analyses, Phase 2 estimates the carbon
sinks as well as its variation over time; quantified the emissions across each sector
followed by carbon budgeting, and likely changes in carbon dynamics are predicted
in Phase 3.
Land-use dynamics—Spatial patterns of land-use dynamics assessment using
temporal remote sensing data: The remote sensing data of Landsat series for 1985,
2005, 2019 (downloaded from the public domain https://landsat.org) were analyzed
through efficient supervised classifier based on GMLC (Gaussian Maximum Likelihood Classifier) algorithm using free and opensource GRASS GIS (Geographical
Analysis Support System—https://wgbis.ces.iisc.ernet.in/grass/). The field investigation has been carried out for collecting training data, which was used to classify
the remote sensing data of 2019 coinciding with the field data collection period. The
earlier time remote sensing data were classified using collateral data compiled from
various sources such as Karnataka Forest Department reports (https://aranya.gov.in),
vegetation map of South India of 1:250,000, the French Institute of India (https://
www.ifpindia.org). The process of remote sensing data classification involved (i)
preparation of false-color composite (FCC) using five bands (R, G, and NIR) of
LANDSAT satellite data, which assisted in the selection of training sites through the
T. V. Ramachandra and S. Bharath
as evergreen, moist as well as dry deciduous, scrub, thorny, sholas, grasslands, and
mangroves in the estuarine areas. The state harbors 4500 species of flowering plants,
508 species of birds, 150 varieties of mammals, 156 reptile species, amphibians of
156 species, 405 fish species, and 330 butterflies. Soils of the state are fertile by two
major river systems (Krishna, Cauvery) and its tributaries. The state has a protected
area network of five national parks (2431.3 km
2 ) and 21 wildlife sanctuaries (3887.83
km
2 ), covering nearly 16% of forest area. Agriculture and horticulture sectors are
the backbone of the state’s economy. The state is the prime destination for IT and
BT technologies with knowledge, innovation, research, and development centers. It
has a gross domestic product (GDP) of |15.10 lakh crore (US$220 billion) as fourth
largest in India, growing at a healthy 7% per year with a per capita GDP of |207,000
(US$3,000).
3 Method
The protocol adopted to assess the carbon dynamics in Karnataka is presented in
Fig. 2. The research involved (i) assessment of land-use dynamics through spatial
data acquired using spaceborne sensors at regular intervals; (ii) field data collection to
classify remote sensing data, (iii) quantification of AGB through field measurements
of girth and height and sampling of the locations through transect based quadrat;
(iv) quantification of carbon across various forest types and soil; (v) data mining
pertaining to carbon emissions, sequestrations in forests and soils through published
literature; (vi) visualization of likely changes in carbon dynamics (a) with the current
rate of deforestation and degradation; (b) interventions with the afforestation; (c)
implementation of the proposed development projects. This was implemented in
three phases. Phase 1 focused on the land-use analyses, Phase 2 estimates the carbon
sinks as well as its variation over time; quantified the emissions across each sector
followed by carbon budgeting, and likely changes in carbon dynamics are predicted
in Phase 3.
Land-use dynamics—Spatial patterns of land-use dynamics assessment using
temporal remote sensing data: The remote sensing data of Landsat series for 1985,
2005, 2019 (downloaded from the public domain https://landsat.org) were analyzed
through efficient supervised classifier based on GMLC (Gaussian Maximum Likelihood Classifier) algorithm using free and opensource GRASS GIS (Geographical
Analysis Support System—https://wgbis.ces.iisc.ernet.in/grass/). The field investigation has been carried out for collecting training data, which was used to classify
the remote sensing data of 2019 coinciding with the field data collection period. The
earlier time remote sensing data were classified using collateral data compiled from
various sources such as Karnataka Forest Department reports (https://aranya.gov.in),
vegetation map of South India of 1:250,000, the French Institute of India (https://
www.ifpindia.org). The process of remote sensing data classification involved (i)
preparation of false-color composite (FCC) using five bands (R, G, and NIR) of
LANDSAT satellite data, which assisted in the selection of training sites through the