Geographic Information System for Risk Area Assessment on Natural Gas Pipeline Construction in Nakhon Nayok Province

Abstract

The objective of this study is to identify potential risk areas caused by the pipeline construction project in Nakhon Nayok province. The potential surface analysis was employed for the manipulation process using critical factors including soil drainage, clay minerals, soil texture, slope, relative humidity, air quality index, distances from bodies of water, roads, and the pipeline. The evaluation of weighting and rating scores has been proposed by experts using 2 main methods, including scaling and hierarchical methods. The risk areas have been divided into high, moderate and low levels. The outputs of these two methods are compared.
It was found that the risk areas identified by the scaling method consist of high risk areas of 316.69 square kilometers (14.77%), moderate risk area of 1,523.05 square kilometers (71.04%), and low risk areas of 304.12 square kilometers (14.19%). Meanwhile, the risk areas evaluated by the hierarchical method consist of high risk areas of 219.47 square kilometers (10.24%), moderate risk areas of 1,839.05 square kilometers (85.78%), and low risk areas of 85.34 square kilometers (3.9%). The comparison of those two methods using the Kappa index has shown the value of 0.66. Thus, those two methods were only in the relation of 66 %. The assessment on land utilization within the high risk areas was analyzed based on the output of the scaling method with larger high risk areas. The land use patterns found in the high risk area include the following areas agriculture of 200.50 square kilometers (63.31%), urban of 74.71square kilometers (23.59%), forest of 5.35 square kilometers (1.69%), water bodies 20.71 square kilometers (6.54%), and others 15.42 square kilometers (4.87%). The purpose of this study was to apply the Geographic Information System for to identify potential risk areas. Geographic Information System (GIS) are a set of computer tools for collecting, storing, transforming and displaying spatial data from the real world.