Estimation of above ground biomass by using multispectral data for Evergreen Forest in Phu Hin Rong Kla National Park, Thailand
Description
Tropical forest is the most important and largest source for stocking CO2 from the atmosphere which might be one of the main sources of carbon emission, global warming and climate change in recent decades. There are two main objectives of this study. The first one is to establish a relationship between above ground biomass and vegetation indices and the other is to evaluate above ground biomass and carbon sequestration for evergreen forest areas in Phu Hin Rong Kla National park, Thailand. Random sampling design based was applied for calculating the above ground biomass at stand level in the selected area by using Brown and Tsutsumi allometric equations. Landsat 7 ETM+ data in February 2009 was used. Support Vector Machine (SVM) was applied for identifying evergreen forest area. Forty-three of vegetation indices and image transformations were used for finding the best correlation with forest stand biomass. Regression analysis was used to investigate the relationship between the biomass volume at stand level and digital data from the satellite image. TM51 which derived from Tsutsumi allometric equation was the highest correlation with stand biomass. Normalized Difference Vegetation Index (NDVI) was not the best correlation in this study. The best biomass estimation model was from TM51 and ND71 (R2 =0.658). The totals of above ground biomass and carbon sequestration were 112,062,010 ton and 56,031,005 ton respectively. The application of this study would be quite useful for understanding the terrestrial carbon dynamics and global climate change. (author)
Availability note (English)
Available from Salzburg University Library, Hofstallgasse 2-4, 5020 Salzburg (AT)Additional details
Publishing Information
- Imprint Pagination
- 146 p.
INIS
- Country of Publication
- Austria
- Country of Input or Organization
- Austria
- INIS RN
- 44007647
- Subject category
- S54: ENVIRONMENTAL SCIENCES; S58: GEOSCIENCES;
- Resource subtype / Literary indicator
- Thesis, Non-conventional Literature
- Descriptors DEI
- BIOMASS; CARBON; CARBON DIOXIDE; CARBON SEQUESTRATION; CLIMATIC CHANGE; FORESTS; GREENHOUSE EFFECT; REGRESSION ANALYSIS; THAILAND
- Descriptors DEC
- AIR POLLUTION CONTROL; ASIA; CARBON COMPOUNDS; CARBON OXIDES; CHALCOGENIDES; CLIMATIC CHANGE; CONTROL; DEVELOPING COUNTRIES; ELEMENTS; ENERGY SOURCES; MATHEMATICS; NONMETALS; OXIDES; OXYGEN COMPOUNDS; POLLUTION CONTROL; RENEWABLE ENERGY SOURCES; SEPARATION PROCESSES; STATISTICS