What Affects Support for Wetland Tourism? A Case Study from Sri Lanka

Abstract

Development of sustainable tourism is not possible without the support and involvement of the local community. Thus, it would be beneficial to understand how residents perceive tourism development. This study investigates the main factors that influence residents’ support for tourism development in the context of wetland tourism. The study was conducted in one of the most extensive wetland areas in Sri Lanka, situated not far from the capital, Colombo. The main instrument for data collection was a survey applied both to residents living inside the Muthurajawela Wetland and to residents living outside but in the proximity of the wetland. The data collected were subsequently processed, evaluated, and explained using SPSS 26. Besides descriptive statistics, a binomial logistic regression was employed to understand which factors influence residents’ attitudes toward future tourism development. The study found that six factors could predict support for tourism development: gender, age, employment (connected or not to tourism), residence (inside or outside the wetland), interaction with tourists, and satisfaction with the current level of tourism development. The results were then discussed in the context of the extant literature and limitations were acknowledged.

Do natural landscapes contribute to reducing Land Surface Temperature (LST)? A case study from Muthurajawela wetland, Sri Lanka

“…This study attempts to quantify the impacts of different LULC categories on Land Surface Temperature (LST) in Muthurajawela wetland and its surroundings in Sri Lanka. Muthurajawela is one of the largest coastal wetland in the country and has experienced increased developmental pressure in the last few decades with significant changes in LULC in the area (Zimar et al, 2020;Athukorala et al, 2021;Egresi et al, 2021). To present an account on how different LULC could affect LST, this study involved a detailed analysis of temperature variations starting from the wetland and the marshes (natural areas) and moving to the surrounding areas up to the city, including the barren land, agricultural areas and the city (anthropogenic areas) using Geographic Information System (GIS) and Remote Sensing (RS) as a tool.…”