Estimation of net primary productivity (NPP) from CASA model for mangrove plantation using remote sensing : a case study of Kung Krabaen Bay Royal Development Study Center in Chanthaburi Province | |
| Author | Ticha Lolupiman |
| Call Number | AIT Thesis no.RS-15-06 |
| Subject(s) | Mangrove forests--Remote sensing--Thailand--Chanthaburi Mangrove forests--Remote sensing--Case studies |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. RS-15-06 |
| Abstract | Net Primary Productivity (NPP) is the product of photosynthesis and the vital element to measure the carbon storage on forest . Thus, carbon storage can be estimated by NPP. The CASA model was selected to estimate NPP in this study. CASA model is biosphere model to estimate NPP from satellite data. This study focuses on mangrove plantation where relates to mangrove age. However, study on mangrove was a challenge because a lot of water in study area and water is affected to the result of the model. This study tried to determine the age of tree which less water effect and modify CASA model with general growth rate to improve the result of carbon stock. The results reveal the year that has less effect from water in the study site and present carbon stock from modified CASA model and field data collection at Kung Krabean bay. The year with less effect from water discovered at 6 - 15 years old (RMSE = 2 and 1.7). Moreover, carbon stock results at 2014 from modified CASA model and field data collection were 250,901.988 and 389,715.043 kgC which CASA model provided closely value du ring 6 - 15 years old (RMSE = 0.3 ). Thus, CASA model can estimate carbon stock during 6 - 15 years old with high accuracy and less accuracy after 16 years old. However , there is something more that have to do to improve the result after 16 years old . The improved model leads to carbon stock measurement by remote sensing in the future. |
| Year | 2015 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-15-06 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing (RS) |
| Chairperson(s) | Sarawut Ninsawat |
| Examination Committee(s) | Nitin, Kumar Tripathi;Honda, Kiyoshi;Nakamura, Shinichi |
| Scholarship Donor(s) | Greater Mekong Subregion (GMS) Scholarship |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2015 |