6. Zheng, Yu, et al. “Visual Sensitivity versus Ecological Sensitivity: An Application of GIS in Urban Forest Park Planning.” Urban Forestry & Urban Greening, vol. 41, 2019, pp. 139–149., https://doi.org/10.1016/j.ufug.2019.03.010. Accessed Nov. 2021.
Zheng et al. investigate the use of GIS in balancing visitor usability and satisfaction in Tianzhu Mountain National Forest Park with the ecological sensitivity of park ecology in this study. First, using slope, distance, and visibility as proxy for a visual sensitivity metric, Zheng et al. used photographs and a topographic map obtained from GaoFen-1 to produce a digital elevation model (DEMs), used to identify areas of high visual sensitivity on high use trails in the park. These areas were then subjected to the ‘Visibility’ spatial analyst tool and assigned a class of visual sensitivity. Second, ecological sensitivity of the park was assessed using weighted criteria including slope, aspect, distance to river, elevation, and vegetation. One map was then generated for each criteria, giving a total of five ecological sensitivity maps, each representing a different criteria. These maps were then combined to produce a final map with the ecological sensitivities for the entire park. Finally the visual and ecological sensitivity maps were overlaid, giving the final map of any potentially intersecting points. This study demonstrates a valuable method for planning wilderness recreation areas which will be exciting and visually striking (thus enticing) to visitors while also balancing the sometimes delicate nature of the ecosystems present in wilderness recreation areas.
7. Geneletti, Davide, and Iris Van Duren. “Protected Area Zoning for Conservation and Use: A Combination of Spatial Multicriteria and Multiobjective Evaluation.” Landscape and Urban Planning, vol. 85, no. 2, 2008, pp. 97–110., https://doi.org/10.1016/j.landurbplan.2007.10.004. Accessed Nov. 2021.
Multi-criteria decision analysis (MCDA) is a powerful tool in a park planner’s toolkit since it allows for many different factors to be considered and weighed at the same time to produce an optimal outcome. This paper looks at the application of MCDA to effectively zone Paneveggio-Pale di S. Martino (PPSM) Natural Park using GIS technology. The park contains three levels of management, each with differing or conflicting criteria. Geneletti and Van Duren aimed to rezone the park based on suitability of land cover to each of the levels of management. To accomplish this, the authors first divided the park into units of ecology and then applied their MCDA process to each of the land units. This yielded a suitability map showing which level of management each land unit was suitable for. The approach Geneletti and Van Duren take here could be extremely useful in integrating a wilderness recreation area into an ecologically sensitive zone. The MCDA approach gives parks managers the ability to weigh the aspects of the park and the surrounding ecology they want to emphasize and reduce the noise of other aspects which are of less importance. The second benefit of this approach is that this breaks up the study area into units of ecology, rather than geographic blocks. This is helpful because it allows for more tailored approach to integration and identification of areas more or less suitable for recreation or conservation aims.
8. Phua, Mui-How, and Mitsuhiro Minowa. “A GIS-Based Multi-Criteria Decision Making Approach to Forest Conservation Planning at a Landscape Scale: A Case Study in the Kinabalu Area, Sabah, Malaysia.” Landscape and Urban Planning, vol. 71, no. 2-4, 2005, pp. 207–222., https://doi.org/10.1016/j.landurbplan.2004.03.004. Accessed Nov. 2021.
It is often a reality that wilderness parks or conservation areas have multiple stakeholders with different or even opposing viewpoints on management action and/or options. In their 2005 paper, Phua and Minowa used Multi-Criteria Decision Analysis supported by GIS to address conservation objectives in Kinabalu, Malaysia. Different indicators were chosen and weighted for this study to represent three different conservation-oriented stakeholder objectives and preferences. These included forest and ecosystem biodiversity, soil and water functions, and potential threats. The authors then combined field work, literature, and remote sensing techniques to generate maps in a GIS representing the indicators mentioned above. Finally, these maps were run through a compromise program to show areas of highest suitability for meeting all stakeholder criteria. This program generated 3566 new polygons. 11 of theses polygons were identified as the most suitable for a new wilderness area based on their connectivity, distance from settlements, and forested nature. These 11 polygons were finally overlaid on a map of the adjacent Kinabalu Park and the existing road network to show a new area which connects to the park and does not encounter any roads. This study demonstrates how planners can integrate not only existing wilderness parks, but completely new parks into existing park/reserve structures using multi-criteria analysis, remote sensing, and GIS mapping. For application in wilderness park planning specifically, new aims from relevant stakeholders could be collected and reweighted to include visitor and recreation objectives alongside conservation aims.
9. Tomczyk, Aleksandra M., and Marek Ewertowski. “Planning of Recreational Trails in Protected Areas: Application of Regression Tree Analysis and Geographic Information Systems.” Applied Geography, vol. 40, June 2013, pp. 129–139., https://doi.org/10.1016/j.apgeog.2013.02.004. Accessed 26 Nov. 2021.
Tomczyk and Ewertowski present a methodology for using GIS software and recreation area user input processed with regression tree analysis to create trail systems in protected areas which balance the objectives of recreation with the needs of conservation. This method was tested using data collected in the Gorce National Park, Poland, and included indicators of trail degradation which were analysed to understand the relationships between human use and environmental stress. This information was then applied to finding new trails with minimized impact.
The indicators used to assess and predict trail degradation included the type of trail (non-motorized/motorized), slope, soil type, ect. This information was then added to a GIS database containing Gorce National Park which included layers such as a DEM, soil classes, and other park characteristics and features. Next, the uses and demands on each trial were assessed based on user input. Combining the trail degradation information and user inputs, a regression tree analysis was performed to assess the current trail degradation and help predict the future potential degradation. These areas were designated on the map, and were then used in a least-cost path function to find the routes with the least impact through the park area.
This study presents a very comprehensive, yet simple method for integrating multiple recreation types and needs into a broader conservation-oriented area. This method relies on fairly simple and easy to collect inputs as well as short, practical analysis to understand use and overuse in parks, as well as to model solutions for problems of degradation.
10. Rocchi, L., et al. “Recreation vs Conservation in Natura 2000 Sites: A Spatial Multicriteria Approach Analysis.” Land Use Policy, vol. 99, 2020, p. 105094., https://doi.org/10.1016/j.landusepol.2020.105094. Accessed 26 Nov. 2021.
Rocchi et al. discuss using a multi-criteria decision analysis for integrating nature-based tourism (NBT) into the Natura 2000 Network (N2K) network in central Italy. The authors aim was to use suitability and capacity criteria from three expert sources to assess which parks in the Umbria region may be able to expand NBT opportunities, which should stabilize at current usage, and which should reduce usage to create the optimal balance of tourism and conservation. To accomplish this, the authors combined the criteria provided by experts with spatial data using mapping software to produce the optimized output maps. In this study, the authors used a QGIS plugin, VectorMCDA, which is unique among the mapping software discussed elsewhere in this bibliography and allows for “…complete integration between GIS and MCDA, [meaning] that they use the same interface and database.” This plugin used with a method designed to identify geographic points with the most ideal placement toward desirable alternatives and away from undesirable ones (TOPSIS, or Technique for Order Preference by Similarity to Ideal Design). Factors chosen to be in the MCDA included habitat conservation status, habitat priority, human activities, recreation impacts, biodiversity and wildlife breeding indices, etc. These factors were then weighted and applied to the TOPSIS algorithm to generate the ideal point output map. This final map showed that only several of the many sites in the Umbria region were suitable for expansion of recreational opportunities.
The benefits of this study to recreation and conservation integration in wilderness recreation areas are immense. The methodology described in this paper provides an alternative method of applying MCDA to other methods described in this bibliography. The customizability of MCDA and its ability to be combined with spatial data in a GIS empower planners and managers to set any goals they wish and model the feasibility and impact of these decisions before investing fully.