A Brief Description of Recovery Process of Coastal Vegetation after Tsunami: A Google Earth time-series remote sensing data

  • Mochamad Candra Wirawan Arief Graduate School of Bioresources, Mie University, 1577 Kurima-machiya, Tsu, Mie Japan, 514-8507
  • Akemi Itaya Graduate School of Bioresources, Mie University, 1577 Kurima-machiya, Tsu, Mie, Japan 514-8507
Keywords: coastal management, fish and shrimp cultivation, GIS, tree planting

Abstract

The recovery of land cover/use after the disaster is sometimes disorderly, especially in developing countries. It is necessary to continuously monitor the progress of land cover/use recovery after disaster in order to sustain vegetation around estuarine and coastal areas. The purpose of this study was to assess the recovery progress of vegetation around estuarine and coastal areas after the Indian Ocean tsunami using a simplified method which consisting Google Earth and visual photo interpretation. Vegetation areas were able to be detected with high accuracy (80%−100%) using simplified method which consisting Google Earth and visual photo interpretation. We were able to show that all most of area including mangrove forests recovered relatively smoothly. However, the area which has a large vegetation areas have not enough recovered, which reached to half or less than half compare with before tsunami. This may be significant in affecting the role of the coastal ecosystem and bioshield. A large number of small mangrove patches (less than 0.1 ha) were able to found around ponds, a number that rapidly increased after the tsunami. Some site in 2013 was double that in 2004. Fish farmers might have planted them for supplying nutrients to ponds and maintain the water quality. Dozen years have passed since the 2004 tsunami, and it might be time to more focus on the recovery of large vegetation area.
Published
2017-08-31
How to Cite
Arief, M. C. W., & Itaya, A. (2017). A Brief Description of Recovery Process of Coastal Vegetation after Tsunami: A Google Earth time-series remote sensing data. Jurnal Manajemen Hutan Tropika, 23(2), 81-89. https://doi.org/10.7226/jtfm.23.2.81
Section
Articles