ACADSTAFF UGM
| Judul/Title | Mangrove Leaf Area Index (LAI) Mapping Using Worldview-2 Imagery in Perancak Estuary, Bali, Indonesia |
| Penulis/Author | Aldo Restu Agi Prananda (1) ; Prof. Muhammad Kamal, S.Si., M.GIS., Ph.D. (2); Denny Wijaya Kusuma (3) |
| Tanggal/Date | 2020 |
| Kata Kunci/Keyword | |
| Abstrak/Abstract | Mangrove forests are unique ecosystem that have many functions in the environment. Mangroves provide food and energy for tropical coastal ecosystem, habitat for coastal flora and fauna, and protection from coastal abrasion. The health status of mangrove could be represented using a biophysical tree parameter called Leaf Area Index (LAI). LAI can be defined as one half the total of green area per unit horizontal ground surface area. This study aims to (1) map the distribution of mangrove LAI in Perancak Estuary, Bali, Indonesia, using a high-spatial resolution WorldView-2 image data (2 m pixel size) and Normalized Difference Vegetation Index (NDVI), and (2) assess the accuracy of the LAI mapping. The selected mangrove site is under authority of Institute of Marine Research and Observation (IMRO) where continuous monitoring of mangrove health is conducted periodically, especially in the restored mangrove areas. Part of this study was designed to develop a baseline for mangrove LAI monitoring at some permanent sample sites. Mangrove objects were first visually discriminated from non-mangrove objects and the non-mangrove objects were masked out to focus on the mangrove objects. The LAI map was created based on the semi-empirical relationships between NDVI and field LAI values measured from hemispherical photograph. The corresponding values of both parameters were correlated to find the regression function for modelling the LAI map. The LAI map shows the distribution of high LAI values correspond to the mature planted mangroves, and the natural mangrove and young planted mangroves representing moderate and low LAI values, respectively. The accuracy of mangrove LAI map was high at 91 % and 1:1 plot shows the model was underestimated. |
| Level | Internasional |
| Status |