Suitability-sensitivity analysis of nature-based tourism using geographic information systems and analytic hierarchy process

Abstract

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. ARTICLE HISTORY

Evaluation of the Comprehensive Ecotourism Suitability and Recognition of Its Key Landscape Pattern Factors (Case Study of Henan Province, China)

“…Based on previous studies of ecotourism by experts and scholars, we select 7 spatial indexes as evaluation factors for ecotourism suitability: naturalness (NL) [19], water proximity (WP), traffic proximity (TP), landscape diversity (LD) [32], vegetation coverage (VC), relief suitability (RS) [33] and climate comfort (CC) [34], which are used in the following formula to calculate the composite index of ecotourism suitability [35]:…”

Using multivariate statistics to assess ecotourism potential of water-bodies: A case-study in Mauritania

“…The multi-spatial layers and the continuous analyses allowed by GIS tools increase the spatial accuracy of predictions and the information handled, thus assisting in the decision-making process (Dhami, Deng, Burns, & Pierskalla, 2014;Dhami, Deng, Strager, & Conley, 2017). For instance, GIS and participatory methods (Delphi and Analytic Hierarchy Process, AHP) were used to map ecotourism as a cultural service (Nahuelhual et al, 2013), high resolution IKONOS images and GIS were used for planning useful resources to ecotourism (Fung & Wong, 2007), and visitor's preferences were assessed for mapping weighted and unweighted potential sites for forest-based ecotourism development (Dhami et al, 2014).…”

“…Environmental features, such as high slopes may influence ecotourism potential of a site (Dhami et al, 2014(Dhami et al, , 2017, and we measured it by calculating the standard deviation of the slope (derived from altitude at 90m resolution) in 1x1km window around each water-body, using the "Buffers" tool of ArcGIS 10.1 (ESRI, 2012). Water-bodies with large areas and permanent water availability play a crucial role in desert environments, allowing the observation of large species diversity and traditional human activities, such as water pumping from mudbrick-wells for watering cattle (Brito et al, 2014(Brito et al, , 2016Hosni, 2000;.…”

“…Thus, the area of each water-body was estimated in the field with a GPS and the water availability was assessed using the Normalized Difference Water Index (NDWI) at 1 arc second resolution in a 1x1km window around water-bodies. Vegetation heterogeneity is well appreciated by tourists (Chhetri & Arrowsmith, 2008;Dhami et al, 2014Dhami et al, , 2017 and thus, we used the Normalized Difference Vegetation Index (NDVI) time-series from the period between 2000 and 2016, at 250m resolution to extract it in a 1x1km window around water-bodies. Short geographic distances between visiting sites are best acknowledged because tourists and ecotourism enterprises tend to maximize, in general, the return on time/money invested to visit a region (Kienast, Degenhardt, Weilenmann, Wäger, & Buchecker, 2012).…”

Optimizing the DRASTIC Method for Nitrate Pollution in Groundwater Vulnerability Assessments: a Case Study in China

“…Sensitivity analysis provides information on the infl uence of the ratings and the weights assigned to each of the factors considered in the model to judge the signifi cance of the subjective elements. Two sensitivity analysis tests can be performed: the map removal sensitivity analysis introduced by Lodwick et al [42], and the single-parameter sensitivity analysis introduced by Napolitano and Fabbri [43]. In this study, the single-parameter sensitivity analysis was chosen to evaluate the impact of each DRASTIC parameter on the vulnerability index by comparing their effective weights with their theoretical weights [44].…”