Sensitivity analysis between Radar Vegetation Index (RVI) and NDVI for estimating net primary production and carbon stock of mangrove forest | |
| Author | Maharjan, Bijaya |
| Call Number | AIT Thesis no.RS-16-03 |
| Subject(s) | Radar Radar--Vegetation Index (RVI) Primary productivity (Biology) Carbon Mangrove forests |
| 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-16-03 |
| Abstract | The Carnegie Ames Stanford Approach ( CASA ) model is applicable to estimate Net Primary Production (NPP) of mangrove forest . The study was focused on mangrove forest NPP and carbon stock estimation, located at coastal zone of Chanthaburi province of eastern Thailand. The annual NPP estimation from CASA mode l seemed low in mature age comparison with annual NPP estimated from observed carbon stock from field data. This may be the effect of early NDVI saturation before NPP stable/decrease. NDVI derived from optical imagery is major parameter to define NPP of forest . The Radar vegetation index (RVI) measures volume scattering caused by structural elements of canopies derived from dual/full polarized PALSAR data along with growth of trees. The strong positive correlation was observed between RVI with field based carbon stock estimation over age of plantation. The sensitivity analysis between RVI and NDVI over forest growth had shown that R VI was more sensitivity to medium and high level of plantation growth than NDVI. So NDVI adjustment using RVI was introduced t o estimate further retrieve parameters such as NPP and hence of carbon stock in better way with breaking early NDVI saturation point in mature mangrove forest . The annual NPP estimation from conventional CASA model for 15, 17 and 19 years were as 28.953, 29.171 and 28.387 g m C/m 2 whereas the values were refined as 34.701, 35.741 and 36.476 g m C/m 2 respectively after implementation of adjustment approach. Similarly, the RVI generated from PALSAR data had positive correlation (R 2 = 0.8716) with increment of f ield carbon stock of mangrove trees over age of plantation. The amount of carbon stock of mangrove forest at end of 21 years , estimated from CASA model (Landsat) and CASA model after adjustment of NDVI by RVI were as 0.602 KgC/m 2 and 0.668 KgC/m 2 respectively whereas 0.757 KgC/m 2 as field based estimation . Hence the NDVI adjustment approach by RVI decreased the error in carbon stock estimation of mature forest significantly. |
| Year | 2016 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. RS-16-03 |
| 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) | Kiyoshi Honda;Shinichi Nakamura |
| Scholarship Donor(s) | Asian Development Bank – Japan Scholarship Program (ADB - JSP) |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2016 |