Remote Sensing for Mangrove Landscape Pattern Identification on the Coast of Ranong, Thailand

Abstract

The mangrove landscape in the Ranong coastal ecosystem provides habitat and niches for many aquatic animals. It also plays an important role in shoreline protection and serves as a livelihood source for millions of people. This study was conducted to identify and determine the pattern of mangrove patches and their species by using remotely sensed data and field methods, respectively. The pointcentered quarter method was used for mangrove vegetation inventory. The results revealed that Mueng district had the highest number of mangrove patches. The smallest number of patches was identified in Kra Buri district. Most of the patches were clumped and elongated with a medium or large size. In total, 19 mangrove species were identified with 7 dominant species—namely, Avicennia marina, A. officinalis, Bruguiera parviflora, Ceriops decandra, C. tagal, Rhizophora apiculata and R. mucronata. The results provide useful information for mangrove habitat restoration and coastal landscape planning in Ranong province. The dominant species of mangrove found in the area could be promoted for mangrove rehabilitation.