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Land Suitability analysis using GIS based multicriteria modelling approach
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... Behaviour and attitude [17]. the least suitable condition (highest oil spill risk) and the highest -the most suitable condition (lowest oil spill risk) [14]. Analytic hierarchy process (AHP) was handled via quantifying criteria and alternative choices for relating those elements to the overall goal. ...
The environmental sensitivity maps would be envisaged as an elaborated scheme exchanging knowledge among numerous stakeholders at decision-making and execution levels. Local knowledge, scientific knowledge and public knowledge are required to associate toward the development of environmental sensitivity maps, particularly the identification of shoreline types and its sensitivity; compiling biology, human-use resource information; ranking, prioritising sensitive sites and resources at risk. Especially, the value of local knowledge has been recognised over time and the need for its effective integration into research and development has grown significantly. One of the options to enhance the role of this knowledge should be participatory tools emphasising researchers-facilitation to obtain indigenous perceptions as well as increase environmental sensitivity maps adoption in the planning, regulatory community in islands and coastal areas.
... First, the simplest statistic estimating the dispersion of a dataset refers to quartiles (e.g. the 25th, the 50th percentile, and the 75th percentile) with the top 25% or the 75th percentile as the upper quartile. Second, the suitability analysis is highly subjective (Hanna & Culpepper, 1998;Welhan & Moore, 2012), and the suitability-unsuitability classification threshold has been subjectively determined in previous studies (e.g. Guinotte & Davies, 2014;Welhan & Moore, 2012;Zorn et al., 2008) with the 75th percentile as one possible choice. ...
... Second, the suitability analysis is highly subjective (Hanna & Culpepper, 1998;Welhan & Moore, 2012), and the suitability-unsuitability classification threshold has been subjectively determined in previous studies (e.g. Guinotte & Davies, 2014;Welhan & Moore, 2012;Zorn et al., 2008) with the 75th percentile as one possible choice. Third, the 75th percentile is also used by several federal agencies in the United States. ...
Evaluation and identification of nature-based tourism (NBT) destinations is not a new practice; however, evaluating the variability of various inputs in the identification of NBT destinations have only recently gained special attention. This study highlights the importance of conducting sensitivity analysis of criteria weights in mapping NBT areas in the state of West Virginia. As an extension to the study by Dhami, Deng, Burns, and Pierskalla (2014, Identifying and mapping forest-based ecotourism areas in West Virginia incorporating visitors’ preferences. Tourism Management, 42, 165–176) who examined and mapped NBT areas in West Virginia by incorporating visitors’ perceptions as criteria weights into a spatial suitability model, this study focuses on how sensitive NBT areas are to the variations of visitors’ and ecotourism experts’ perceptions of selected criteria (i.e. remoteness, slope, vegetation, wildlife, mining, and logging) using a simple one-at-a-time method. Results indicate that visitors and ecotourism experts perceived the criteria in a similar manner with the presence of vegetation and remoteness being ranked as the most important criteria for NBT areas. The results also show that about one-third of West Virginia is highly suitable and least sensitive to variations in criteria weights, and therefore suitable for a wide range of NBT tourists, irrespective of their preferences for the selected NBT criteria. Research implications and limitations are discussed.
The Kingdom of Thailand has been facing with natural disasters every year: landslide, drought, wind storm, landslide etc. especially, the last decade the natural disaster was most frequency and devastated vast areas. Furthermore, landslide occurrences have become more and more recurrence and human impacts have been increasing on seriously natural disasters problem during the past couple of decades. The study has been designed to analyze the risk landslide areas for landslide management in Phetchabun province, Thailand. This study aim to apply the geo-informatics technology, create landslide risk map, and develop landslide monitoring and warning systems used for formulating preparedness and recovery plans. This analyzed the concerned physical and environmental factors though statistical techniques and spatial analysis. The analyzed factors included with river, elevation, street, land use, sub-basin area, slope, drainage and rainfall. Potential Surface Analysis (PSA) technique has been used for analysis included with overlaying and Weighting-Rating Model for landslide risk area. The validation model compared with historical data. The result could show risk areas of landslide in Phetchabun province that high risk areas are covering north-eastern and central of province. In addition, we divided risk area as three levels; high risky, moderate and less. Furthermore, the consequences can be protect or relieved by using appropriate measures; including both publicizing risk information and be prepared for the happening of such disasters. However, some of spatial data have to up to date and improve to high accuracy.
