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

Authors : Ankit ARYA, Shalini SHALİNİ NEGİ, Jaydipsinh C. KATHOTA, Ajay N. PATEL, Manik H. KALUBARME, J. K. GARG

Pages : 79-93

Doi:10.30897/ijegeo.312517

View : 9 | Download : 6

Publication Date : 2017-05-15

Article Type : Research Paper

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 insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(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 insert ignore into