Using remote sensing technique for analyzing temporal changes of seagrass beds by human impacts in waters of Cam Ranh Bay, Vietnam

Abstract

Seagrass beds/meadows are very productive ecosystems with high biodiversities. However, they have been degraded under high pressures of human activities. Combining depth-invariance index and ground-truthing, distribution of seagrass beds in Cam Ranh Bay was identified by analyses of multi-remote sensing images such as LANDSAT, SPOT and ALOS AVNIR-2. Although coverage of seagrass meadows was1178 ha, the seagrass meadows were being degraded by illegal fishing methods, aquaculture and discharges from industries and living domestics. The reducing ratio of seagrass coverage has been increased in recent years. While the depth-invariance index method would help to detect the areas of seagrass beds, this method requires combination of field trip and absorption library methods to increase classification accuracy. Final maps of the status and changes of seagrass beds could help to integrate the sustainable development of economy with protection of natural resources. © (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.