Geoinformatics in mangrove monitoring: damage and recovery after the 2004 Indian Ocean tsunami in Phang Nga, Thailand

Abstract

Abstract. In the aftermath of the 2004 Indian Ocean Tsunami, it has been proven that mangrove ecosystems provide protection against coastal disasters by acting as bioshields. Satellite data have been effectively used to detect, assess, and monitor the changes in mangroves during the pre-and post-tsunami periods. However, not much information regarding mangrove restoration or reforestation is available. Rather than undertaking time-consuming fieldwork, this study proposed using geoinformatic technologies such as Remote Sensing (RS), Geographic Information System (GIS), and Global Positioning System (GPS) to monitor the mangrove recovery. The analysis focused only on the tsunami-impacted mangrove areas along the western coast of the Tai Muang, Takuapa and Khuraburi Districts of Phang Nga Province, southern region of Thailand. The results consisted of 2 parts, first: the supervised classification of main land uses, namely forest, mangrove, agricultural land, builtup area, bare soil, water body, and miscellaneous covers in ASTER images, was conducted using the maximum likelihood method with higher than 75 % for overall accuracy. Once the confusion between classes was improved in postprocessing, the accuracy of mangrove class was greater than 85 % for all dates. The results showed that the mangrove area Difference Vegetation Index (NDVI) fluctuation curve and the supporting field survey data. The recovery patterns were summarized into 2 categories: (i) gradually recovery, and (ii) fluctuating recovery. The gradually recovery category that implied the homogeneous pattern or uniform reforestation was observed in the seriously damaged area where most of the mangrove trees were swept away during the tsunami. This pattern covered approximately 50.35 % of the total reforested area. The NDVI time series of the uniform or homogeneous reforested mangrove at the sampled plots has gradually increased after 2005. The fluctuating recovery category that implied the heterogeneous pattern or non-uniform reforestation was observed in partially damaged areas where some of the mangrove trees were swept away and broken but still some trees were remained in the area. The heterogeneous patterns covered approximately 49.65 % of the total reforested area.

Potential of remote sensing techniques for tsunami hazard and vulnerability analysis – a case study from Phang-Nga province, Thailand

“…Choowong et al, 2009;Vosberg, 2010). Ecosystem recovery was assessed by Kamthonkiat et al (2011) andVu (2008), focusing on mangroves based on ASTER imagery. Chang et al (2006) and Olwig et al (2007) evaluated the role of mangrove forests in mitigating tsunami impacts and thus focused on the socio-ecological dimension of vulnerability.…”

Application of Remote Sensing for Tsunami Disaster

“…Monitoring proposals were applied for a damaged mangrove area. Kamthonkiat et al (2011) www.intechopen.com…”

Rapid Assessment of Crop Status: An Application of MODIS and SAR Data to Rice Areas in Leyte, Philippines Affected by Typhoon Haiyan

“…Geospatial and remote sensing based damage assessments have been used in post-tsunami impact assessments (e.g., [10,11]). On 26 December 2004, earthquakes in the Indian Ocean triggered massive waves that caused vast destruction of many coastal areas in the region [12].…”

“…Specific examples include the use of high-resolution imagery (IKONOS satellite datasets) to map changes in vegetation near Aceh, Indonesia, immediately after the event [13], mapping of coastal vegetation changes in Phang Nga province, Thailand [14,15] and assessments of the protection potential of mangrove vegetation cover along the west coast of Thailand [16]. ASTER/Landsat imagery has been used to estimate tsunami-damaged areas [12] and to map and assess vegetation changes-using vegetation indices such as the Normalized Difference Vegetation Index (NDVI)-due to short-term [11] and long-term tsunami effects [17]. These studies are extremely useful for estimating the damages to natural resources.…”