Year 2020, Volume 66 Issue 3 (30.09.2020)

Year : 2020
Volume : 66
Issue : 3 (30.09.2020)
   
Authors : Yannawut UTTARUK, Teerawong LAOSUWAN
Title : METHODS OF ESTIMATION FOR ABOVE GROUND CARBON STOCK IN NONGBUA-NONMEE COMMUNITY FOREST, MAHA SARAKHAM PROVINCE, THAILAND
Abstract : The climate of the world today has changed greatly. This is mainly due to human activity causing large emissions of carbon dioxide (CO2) from the reserve into the atmosphere, which is the main cause of global warming. This research methodology comprised of training for people in the community and local government sector, so they acquired knowledge and understanding of the causes and consequences of global warming. The people will also learn the adjustment toward weather atmosphere, the method in relieving global warming issues with the potential of the community forest as well as tree measurement techniques. The research method was based from the analysis of the carbon stock from the community forest from 3 different methods; which are 1) method of tree measurement by farmers in the community 2) Measurement, Reporting and Verification (MRV) online method, and 3) the application of Geoinformatics Technology (GIT). The research results found that 50 participants in the training session possessed over 80 percent of understanding toward causes and consequences from global warming, adjustment toward the change of weather atmosphere, and way to relieve the severity of global warming issue with a potential of community forest. Participants were also able to learn tree measurement techniques as well as able to record results. The results from the data analysis from the field survey, MRV online tool, and Geoinformatics Technology found that the community forest can complete the process of carbon stock that is equivalent to 5,256.66 tCO2e, 5,061.32 tCO2e, 5,058.01 tCO2e respectively.
For citation : Uttaruk, Y., Laosuwan, T. (2020): Methods of estımatıon for above ground carbon stock ın Nongbua-nonmee communıty forest, Maha Sarakham Provınce, Thaıland. Agriculture and Forestry, 66 (3): 183-195
Keywords : Community forest, Carbon stock, Ecological structure, Remote Sensing, Geoinformatics technology, MRV
   
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