Abstract
This paper presents a method for identifying and monitoring regional tourism development preferences using an Internet public participation geographic information system (PPGIS). In 2004, a large baseline study of landscape values and development preferences was completed on Kangaroo Island (KI), South Australia, using low technology, paper-map PPGIS. In 2010, we implemented an Internet-based PPGIS monitoring study with the same participants to (1) determine the efficacy of smaller scale monitoring efforts using an Internet-based PPGIS, (2) examine whether residents' tourism development preferences had changed over the last six years and (3) assess the strengths and weaknesses of the PPGIS methodology for identifying changes in tourism development preferences. Since KI is the first international tourism destination to adopt the Tourism Optimization Management Model (TOMM) for monitoring tourism outcomes, we contrast the PPGIS monitoring method with information from the TOMM process. Our results indicate that tourism development preferences remained relatively stable over the past six years with some small changes on the western reach of the island. We argue that an Internet-based PPGIS method can be an effective tool for tourism development planning and monitoring because the method is place-based, cost-effective and provides tighter coupling with land use planning controls such as zoning.
在地理信息网站上使用公众参与GIS(PPGIS)来监测旅游发展的偏好
该文章介绍了一种使用英特网公众参与GIS(PPGIS)来确认和监测区域旅游发展偏好的方法。在2004年,在南澳大利亚的袋鼠岛(KI),使用低科技,纸制PPGIS完成了一个大型的对景观价值和发展偏好的基地研究。在2010年,我们对相同的参与者进行了一种英特网为基础的PPGIS监测研究:1)使用一种英特网为基础的PPGIS来决定更小型监测结果的功效,2)来检验居民旅游发展偏好在过去的六年中有否改变,3)来评估PPGIS方法的好处和缺点来决定旅游发展偏好的改变。因为KI是第一个实施旅游最优管理模式(TOMM)来监测旅游结果的国际旅游目的地,所以我们用TOMM过程中的信息来对比PPGIS监测方法。我们的结果显示旅游发展偏好在过去的六年中处于相对的稳定,只在岛的西海岸有些小变化。我们认为一种英特网为基础的PPGIS方法对旅游发展规划和监测来说是一种有效的工具,因为该方法是以地区为基础,节省花费的和能提供与土地使用规划控制例如分区,更紧密的联合。
Acknowledgements
The authors wish to acknowledge the work of Susan Hale in collecting data for the 2004 KI study and the Center for Spatial Information at Central Washington University for contributing to the 2010 data collection effort.