Carbon Sequestration Analysis of dominant tree species using Geo-informatics Technology in Gujarat State (INDIA)

Year 2017, , 79 - 93, 15.05.2017

Ankit Arya Shalini Shalini Negi Jaydipsinh C. Kathota Ajay N. Patel Manik H. Kalubarme , J. K. Garg

https://doi.org/10.30897/ijegeo.312517

Cited By: 3

Abstract

Comparative analysis of carbon store of three dominant tree
species in planned green capital city of Gandhinagar and unplanned industrial
town of Mahesana in Gujarat State, India was carried out using geo-informatics
technology. The selected three major dominant tree species grown in these towns
are Azadirachta indica, Acacia sp. and Cassia
sp. The high spatial
resolution Remote Sensing Satellite data from Indian Remote Sensing Satellite
(IRS-Resourcesat-1) LISS-IV, Cartosat-1, and Google earth images were used in
this study. The tree cover was categorized into dense and sparse on the basis
of canopy cover observed on Satellite data. A grid of 1km X 1km was created in
GIS environment and superimposed on Cartosat-1 images. Random sample of 20 %
was selected for detailed tree count in the field and total tree count was
estimated from these selected sample grids. 

 

Total biomass and carbon sequestered in the major tree species
have been estimated using a non-destructive method. The carbon stock estimated for three major
tree species in Gandhinagar and Mahesana towns indicate that Azadirachta indica has maximum carbon
sequestration potential as compared to Acacia
sp. and Cassia
sp. The
maximum of carbon stock was present in Girth at Breast Height (GBH) size
>180 cm which is followed by GBH size 90 to 180 cm. The total number of
trees in Gandhinagar town is much higher as compared to Mahesana town;
therefore estimated carbon store of dominant tree species in Gandhinagar town
is very high as compared to Mahesana town which is more arid as compared to
Gandhinagar.

Keywords

Carbon Sequestration, urban forestry, Total biomass, Girth at Breast Height (GBH), Carbon store, Remote Sensing (RS), Geographic Information System (GIS), Indian Remote Sensing Satellite

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