Heberling Matthew T, Templeton Joshua J
Sustainable Technology Division, Sustainable Environments Branch, U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, Cincinnati, OH 45268, USA.
Environ Manage. 2009 Apr;43(4):619-27. doi: 10.1007/s00267-008-9149-8. Epub 2008 May 28.
We estimate an individual travel cost model for Great Sand Dunes National Park and Preserve (GSD) in Colorado using on-site, secondary data. The purpose of the on-site survey was to help the National Park Service better understand the visitors of GSD; it was not intended for a travel cost model. Variables such as travel cost and income were estimated based on respondents' Zip Codes. Following approaches found in the literature, a negative binomial model corrected for truncation and endogenous stratification fit the data the best. We estimate a recreational benefit of U.S. $89/visitor/year or U.S. $54/visitor/24-h recreational day (in 2002 U.S. $). Based on the approach presented here, there are other data sets for national parks, preserves, and battlefields where travel cost models could be estimated and used to support National Park Service management decisions.
我们使用实地二次数据，为科罗拉多州的大沙丘国家公园及保护区（GSD）估算了个体旅行成本模型。实地调查的目的是帮助国家公园管理局更好地了解GSD的游客情况；该调查并非用于旅行成本模型。旅行成本和收入等变量是根据受访者的邮政编码估算得出的。按照文献中所采用的方法，一个针对截断和内生分层进行校正的负二项式模型对数据拟合效果最佳。我们估算出每位游客每年的游憩效益为89美元，或每位游客每24小时游憩日的效益为54美元（按2002年美元计算）。基于此处介绍的方法，还有其他一些关于国家公园、保护区和战场的数据集，在这些数据集中可以估算旅行成本模型，并用于支持国家公园管理局的管理决策。
