Biomass assesssment from combined optical and SAR remote sensing data in Surat Thani Province, Thailand | |
| Author | Kumar, Kilaparthi Kiran |
| Call Number | AIT Thesis no.RS-16-12 |
| Subject(s) | Biomass--Assessment---Thailand--Surat Thani Remote sensing--Thailand--Surat Thani |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis;no. RS-16-12 |
| Abstract | Today the carbon content in the atmosphere is predominantly increasing due to greenhouse gas emission and deforestation. Forest plays a key role in global carbon cycle monitoring which contains70%-80% of global carbon .Forest absorbs the carbon dioxide from atmosphere by process of sequestration through photosynthesis; it stores more carbon than any other terrestrial ecosystem in form of wood biomass. The availability of biomass in the environment as agricultural products, wood, renewable energy and food waste. Therefore, it is essential to estimate the biomass content in the environment. In olden days, biomass estimated by the inventory techniques, which take lot of time and cost. The spatial distribution of biomass cannot obtain by inventory techniques so the application of remote sensing in biomass assessment introduced to solve the problem. Overall accuracy of classified map indicates land features on map shows 91.13% accurate with different land features on ground. From1990-2015 supervised land cover classification forest area undergoes massive decrease of 0.825 sq km every year. Similarly oil palm 1.4 sq km ,mixed plantation 0.234 sq km, urban area 0.82 sq km increases every year from 1990-2015.lemon0.032 sq km and rose apple0.037 sq km occupies less area in 2015.Both optical (LANDSAT-8) and synthetic aperture radar (ALOS-2) remote sensing data used for above ground biomass (AGB) assessment. Biomass that stores in branch and stem of tree called as above ground biomass. Twenty ground sample plots of 30m*30m utilized for biomass calculation from allometric equations. Optical remote sensing calculates the biomass based on the spectral indices of SAVI and RVI by regression analysis (R²=0.813). Synthetic aperture radar is an emerging technique uses high frequency wavelengths for biomass estimation. HV backscattering shows good relation (R²=0.74) with field calculated biomass compared to HH (R²=0.43) utilizes for biomass model generation by linear regression analysis. Combination of both optical spectral indices (SAVI, RVI) and HV SAR backscattering increases the plantation biomass accuracy to (R²=0.859) compared to optical (R²=0.788) and SAR (R²=0.742). |
| Year | 2016 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis;no. RS-16-12 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Nagai, Masahiko |
| Examination Committee(s) | Nakamura, Shinichi;Apichon Witayangkurn |
| Scholarship Donor(s) | AIT Fellowship |
| Degree | Thesis (M.Eng.) - Asian Institute of Technology, 2016 |