资源环境科技发展态势分析平台

Retrieval of biophysical properties of mangrove vegetation (e.g. height and above ground biomass) has typically relied upon traditional forest inventory data collection methods. Recently, the availability of Unmanned Aerial Vehicles (UAV) with different types of sensors and capabilities has proliferated, opening the possibility to expand the methods to retrieve biophysical properties of vegetation. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Perak Province, Malaysia, this study aimed to investigate the use of UAV imagery for retrieving structural information on mangroves. We focused on a structurally complex 90-year-old protective forest zone and a simpler 15-year-old productive forest zone that had been silviculturally managed for charcoal production. The UAV data were acquired in June 2016. In the productive zone, the median tree stand heights retrieved from the UAV and field data were, respectively, 13.7 m and 14 m (no significant difference, p-value =.375). In the protective zone, the median tree stand heights retrieved from the UAV and field data were, respectively, 25.8 and 16.5 m (significant difference, p-value =.0001) taking into account only the upper canopy. The above ground biomass (AGB) in the productive zone was estimated at 217 Mg ha(-1) using UAV data and 238 Mg ha(-1) using ground inventory data. In the protective zone, the AGB was estimated at 210 Mg ha(-1) using UAV data and 143 Mg ha(-1) using ground inventory data, taking into account only upper canopy trees in both estimations. These observations suggested that UAV data were most useful for retrieving canopy height and biomass from forests that were relatively homogeneous and with a single dominant layer. A set of guidelines for enabling the use of UAV data for local management is presented, including suggestions as to how to use these data in combination with field observations to support management activities. This approach would be applicable in other regions where mangroves occur, particularly as these are environments that are often remote, inaccessible or difficult to work in.