Estimation of Carbon and Biomass Trees Outside Forest (Tof) Using Remote Sensing and GIS Case Study in Vikarabad District, Telangana State India

Abstract: Geospatial technology, remote sensing (RS), geographic information system (GIS), and global positioning system (GPS), commonly called the three 'S' systems, and field inventory methods with hyper spectral sensors play a major role in developing effective forest information. Management to realize scientific management of system forest resources ,Non-forest trees play an important role in global carbon cycling, as they are large pools of carbon as well as potential carbon sinks and atmospheric sources. Given the importance of biomass estimates in the global carbon (C) cycle, the present study demonstrates the potential of stand wise trees outside of forest inventory data, and we specifically used Cartosat-1 panchromatic (2.5 m) and multispectral. LISS-IV (5.8 m) dataset to quantify vegetation and create a much-needed database for TOF. The total geographical study area of Vikarabad district is 104903 sq.km. Results will help address key ecosystem services in the TOF, including quantifying greenhouse gas emissions from agriculture, forests and other land use categories. What is different from the above TOF biomass is that the TOF biomass averaged 2150.12 t/ha in all three classes linear, polygonal and scattered. Total TOF biomass and carbon content above ground were calculated as 24.43 t/ha, 414.46 t/ha and 556.36 t/ha respectively in the study area. The results of the study conclude that classification of TOF and prediction of biomass and carbon content in TOF can be successful. Achieved through a combined approach of remote sensing and GIS based spatial techniques with supplement of field data. The current approach would help to find potential carbon sequestration area in Vikarabad District Telangana State India