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Journal Publications

New Publications: (Email Greg Brown for PDF file if there is no link for download).

1. Karimi, A., Tulloch, A., Brown, G., and Hockings, M. 2017. AUnderstanding the effects of different social data on selecting priority conservation areas. Conservation Biology. Link to pre-print of article.

2. Levin, N., Lechner, A., and Brown, G. 2017. An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. Applied Geography 79: 115-126. Link to pre-print of article.

3. Loerzel, J., Goedeke,T., Dillard, M., Brown, G. 2017. SCUBA divers above the waterline: Using participatory mapping of coral reef conditions to inform reef management. Marine Policy 76: 79–89. Link to article.

4. Brown, G., Strickland-Munro, J., Kobryn, H., and S. Moore. 2017. Mixed methods participatory GIS: An evaluation of the validity of qualitative and quantitative mapping methods. Applied Geography 79:153-166. Link to article.

5. Brown, G., Kangas, K., Juutinen, A., and A. Tolvanen. 2017. Identifying environmental and natural resource management conflict potential using participatory mapping. Society & Natural Resources. Link pre-print of article.

6. Moore, S., Brown, G., Kobryn, H. and Strickland-Munro, J. 2017. Identifying conflict potential in a coastal and marine environment using participatory mapping. Journal of Environmental Management 197:706-718. Link to article.

7. Brown, G., Hausner, V. 2017. An empirical analysis of cultural ecosystem values in coastal landscapes. Ocean & Coastal Management 142:49-60. Link to article.

8. Brown, G., Pullar, D., and Hausner, V. 2016. An evaluation of spatial value transfer methods for identifying cultural ecosystem services. Ecological Indicators Link to pre-print article.

9. Strickland-Munro, J., Kobryn, H., Brown, G., and Moore, S. 2016. Marine spatial planning for the future: Using Public Participation GIS (PPGIS) to inform the human dimension for large marine parks. Marine Policy Link to article.

10. Strickland-Munro, J., Kobryn, H., Moore, S., and Brown, G. 2016. Valuing the wild, remote and beautiful: Using public participation GIS to inform tourism planning in the Kimberley, Western Australia. International Journal of Sustainable Development and Planning Link to article.

11. Zolkafli, A., Liu, Y., and Brown, G. 2017. Bridging the knowledge divide between public and experts using PGIS for land use planning in Malaysia. Applied Geography 83:107-117. Link to article.

12. Zolkafli, A., Brown, G., and Liu, Y. 2017. An evaluation of the capacity-building effects of participatory GIS (PGIS) for public participation in land use planning. Planning Practice & Research (in press). Link to pre-print of article.

13. Brown, G., Strickland-Munro, J., Kobryn, H., and S. Moore. 2016. Stakeholder analysis for marine conservation planning using Public Participation GIS. Applied Geography. Link to pre-print article.

14. Brown, G., 2016. A review of sampling effects and response bias in internet participatory mapping (PPGIS/PGIS/VGI). Transactions in GIS. Link to article.

15. Brown, G., Hausner, V., Grodzińska-Jurczak, M., Pietrzyk-Kaszyńska, A., Olszańska, A., Peek, B., Rechciński, M., and Lægreid, E. 2015. Cross-cultural values and management preferences in protected areas of Norway and Poland. Journal for Nature Conservation. Link to article.

16. Brown, G., de Bie, K. and Weber, D. 2015. Identifying public land stakeholder perspectives for implementing place-based land management. Landscape and Urban Planning. Link to article.

17. Wolf, I.D., Wohlfart, T., Brown, G., and A. Bartolome Lasa. 2015. The use of public participation GIS (PPGIS) for park visitor management: A case study of mountain biking. Tourism Management. Link to article.

18. Karimi, A., Brown, G., and Hockings, M. 2015. Methods and participatory approaches for identifying social-ecological hotspots. Applied Geography. Link to article.

19. Hausner, V., Brown, G., and Lægreid, E. 2015. Effects of land tenure and protected areas on ecosystem services and land use preferences in Norway. Land Use Policy. Link to article.

20. Brown, G., Hausner, V., and Lægreid, E. 2015. Physical landscape associations with mapped ecosystem values with implications for spatial value transfer: An empirical study from Norway. Ecosystem Services. Link to article.

21. Ramirez-Gomez, S.O.I., Brown, G., Verweij, P.A, and Boot, R. 2016. Participatory mapping of ecosystem service values to identify community use zones. Journal for Nature Conservation. Link to pre-print of article.

22. Brown, G., Raymond, C., and J. Corcoran. 2015. Mapping and measuring place attachment. Appliced Geography. Link to article.

23. Brown, G., Weber, D., and K. de Bie. 2014. Is PPGIS good enough? An empirical evaluation of the quality of PPGIS crowd-sourced spatial data for conservation planning. Land Use Policy. Link to article.

24. Brown, G., Fagerholm, N. 2014. Empirical PPGIS/PGIS mapping of ecosystem services: A review and evaluation. Ecosystem Services. Link to article.

25. Brown, G., Weber, D., and K. de Bie. 2014. Assessing the value of public lands using public participation GIS (PPGIS) and social landscape metrics. Link to publication. Applied Geography.

26. Brown, G. 2015. Engaging the wisdom of crowds and public judgment for land use planning using public participation GIS (PPGIS). Australian Planner. Link to article.

27. Lechner, A., Brown, G., and C. Raymond. 2015. Modeling the impact of future development and public conservation orientation on landscape connectivity for conservation planning. Landscape Ecology. Link to pre-print article.

28. Brown, G., and M. Kytta. 2014. Key issues and research priorities for public participation GIS (PPGIS): A synthesis based on empirical research. Link to publication. Applied Geography.

29. Brown, G., Donovan, S., Pullar, D., Pocewicz, A., Toohey, R., and Ballesteros-Lopez, R. 2014. An empirical evaluation of workshop versus survey PPGIS methods. Applied Geography. Link to article.

30. Brown, G., Schebella, M., and D. Weber. 2014. Using Participatory GIS to measure physical activity and urban park benefits. Landscape and Urban Planning. Link to article.

31. Ramirez-Gomez, S., Brown, G. and Tjon Sie Fat, A. 2013. Participatory Mapping with Indigenous Communities for Conservation: Challenges and Lessons from Suriname. The Electronic Journal of Information Systems in Developing Countries. Link to article.

32. Brown, G. and C. Raymond. 2014. Methods for Identifying Land Use Conflict Potential using Participatory Mapping. Landscape and Urban Planning. Link to article.

33. Brown, G. 2013. The relationship between social values for ecosystem services and global land cover: An empirical analysis. Ecosystem Services. Link to article

34. Brown, G. and S. Donovan. 2013. Escaping the national forest planning quagmire: Using public participation GIS (PPGIS) to assess acceptable national forest use. Journal of Forestry. Link to article.

35. Brown, G. 2013. Analysis of the empirical relationships between spatial and non-spatial preferences for national forest management and place-based values for national forests. Applied Geography. Link to article.

36. Brown, G., M. Kelly, and D. Whitall. 2013. Which “public”? Sampling effects in public participation GIS (PPGIS) and Volunteered Geographic Information (VGI) systems for public lands management. Journal of Environmental Planning and Management. Link to article.

37. Brown, G. and S. Donovan. 2013. Measuring change in place values for environmental and natural resource planning using Public Participation GIS (PPGIS): Results and challenges for longitudinal research. Society & Natural Resources. Link to article.

38. Brown, G. and L.Brabyn. 2012. The extrapolation of social landscape values to a national level in New Zealand using landscape character classification. Applied Geography. Link to article.

39. Brown, G. and L. Brabyn. 2012. An analysis of the relationships between multiple values and physical landscapes at a regional scale using public participation GIS and landscape character classification. Landscape and Urban Planning. Link to article.

40. Brown, G. and D. Weber. 2012. A Place-based Approach to Conservation Management using Public Participation GIS (PPGIS). Journal of Environmental Planning and Management. Link to article.

41. Brown, G., and D. Weber. 2012. Measuring Change in Place Values Using Public Participation GIS (PPGIS). Applied Geography. Link to article.

42. Brown, G., Weber, D., Zanon, D., and K. de Bie.  2012. Evaluation of an online (opt-in) panel for Public Participation Geographic Information Systems (PPGIS) surveys.  International Journal of Public Opinion Research.Link to article.

43. Brown, G., and D. Weber.  2012. Using Public Participation GIS (PPGIS) on the Geoweb to monitor tourism development preferences. Journal of Sustainable Tourism. Link to article.

44. Brown, G., and P. Reed.  2012. Values Compatibility Analysis:  Integrating public values in a forest planning decision support system. Applied Spatial Analysis and Policy. Link to article.

45. Brown, G. 2012. Public Participation GIS (PPGIS) for regional and environmental planning:  Reflections on a decade of empirical research.  URISA Journal. Link to article.

46. Pocewicz, A., Nielsen-Pincus,M., Brown, G., and R. Schnitzer.  2012.  An evaluation of internet versus paper-based methods for Public Participation Geographic Information Systems (PPGIS). Transactions in GIS. Link to article.

47. Brown, G. 2012. An empirical evaluation of the spatial accuracy of public participation GIS (PPGIS) data. Applied Geography.Link to article.

48. Brown, G. 2014. Identifying Landscape Values in Prince William Sound with Public Participation Geographic Information Systems (PPGIS). Unpublished book chapter. Link to publication.

Value Mapping & PPGIS Methods

1. Brown, G. and D. Weber. 2011.  Public Participation GIS: A new method for national park planning. Landscape and Urban Research. 102(1):1-15 Link to article. 

This article describes research to evaluate the use of a public participation geographic information system (PPGIS) for national park planning. Visitor perceptions of park experiences, environmental impacts, and facility needs were collected via an internet-based mapping method for input into a national park planning decision support system. The results demonstrate that an internet, participatory mapping method can be effective in measuring visitor experiences, environmental impacts, and facility needs for a variety of park planning processes.

2. Brown, G. and P. Reed. 2011.  Social Landscape Metrics:  Measures for Understanding Place Values from Public Participation Geographic Information Systems (PPGIS). DOI:10.1080/01426397.2011.591487 Landscape ResearchLink to article. 

This article introduces the concept of social landscape metrics that quantify human perceptions of place resulting from the use of public participation geographic information systems (PPGIS).  The articles presents and explains a set of social landscape metrics that measure the composition and configuration of human perceptions of landscapes.  Two classes of social landscape metrics, boundary and inductive, are described along with their applications for land use planning and management.

3. Brown, G., J. Montag, and K. Lyon. 2011. Public Participation GIS:  A method for identifying ecosystem services. Society & Natural Resources. http://dx.doi.org/10.1080/08941920.2011.621511 Link to article. 

This article describes the use of an internet-based public participation geographic information system (PPGIS) to identify ecosystem services in Grand County, Colorado.  The PPGIS method demonstrates potential for identifying ecosystem services to augment expert judgment and to inform public or environmental policy decisions regarding land use tradeoffs.

4. Brown, G. and D. Pullar. 2011. An evaluation of the use of points versus polygons in Public Participation Geographic Information Systems (PPGIS) using quasi-experimental design and Monte Carlo simulation. International Journal of Geographic Information Science. http://www.tandfonline.com/loi/tgis20 Link to article. 

This article describes a quasi-experimental design where spatial data was collected as both point and polygon spatial features in the same PPGIS study.  Monte Carlo simulation methods are used to describe the relationship between the quantity of data collected and the degree of spatial convergence in the two methods for each of four PPGIS attributes.  The results demonstrate that the same PPGIS attributes identified by points and polygons will converge on a collective spatial “truth” within the study area provided there are enough observations, however, the degree of spatial convergence varies by PPGIS attribute type and the quantity of data collected.

5. Zhu, X., S. Pfueller, P. Whitelaw, and C. Winter. 2010. Spatial Differentiation of Landscape Values in the Murray River Region of Victoria, Australia. Environmental Managment 45(5):896-911. 

This article advances understanding of the location of perceived landscape values through a statistically based approach to spatial analysis of value densities. Survey data were obtained from a sample of people living in and using the Murray River region, Australia, where declining environmental quality prompted a reevaluation of its conservation status. When densities of 12 perceived landscape values were mapped using geographic information systems (GIS), valued places clustered along the entire river bank and in associated National/State Parks and reserves. While simple density mapping revealed high value densities in various locations, it did not indicate what density of a landscape value could be regarded as a statistically significant hotspot or distinguish whether overlapping areas of high density for different values indicate identical or adjacent locations. A spatial statistic Getis–Ord Gi* was used to indicate statistically significant spatial clusters of high value densities or ‘‘hotspots’’.

6. Brown, G. and P. Reed. 2009.  Public Participation GIS:  A new method for national forest planning. Forest Science 55(2):166-182. Link to article. 

This article: 1) reviews previous applications of landscape value mapping methods across a variety of planning applications; 2) describes the participatory, internet mapping method used in 3 studies of national forests in Arizona and Oregon in 2006 and 2007; 3) presents and evaluates the results to show likely future implementation constraints; and 4) based on lessons learned, describes a recommended PPGIS protocol for national forest planning.

7. Beverly, Jennifer L., Uto, Kinga, Wilkes, J. and P. Bothwell. 2008. Assessing spatial attributes of forest landscape values: an internet-based participatory mapping approach.  Canadian Journal of Forest Research. 38:289-303.

The paper GIS method of mapping landscape values (Brown and Reed) is adapted to the internet for a region in Alberta, Canada, primarily to assist forest fire management planning. This manuscript provides a summary of various spatial methods that describe the frequency and distribution of landscape values in the study area.

8. Brown, G. 2005.  Mapping Spatial Attributes in Survey Research for Natural Resource Management:  Methods and Applications. Society & Natural Resources 18(1):1-23. Link to article.   

This is the primary article on landscape value mapping methods.  The author describes spatial measures of landscape values and place attributes developed and used in five surveys of the general public in Alaska (1998-2003). The author reviews the spatial data collection rationale behind these studies, as well as design concepts, methods, and implementation issues for a general public survey that includes a spatial mapping component.  Other topics covered include operationalization of theory, map and materials selection, digitizing and data entry concerns, and spatial data analysis tools.

9. Brown, G. 2006.   Mapping Landscape Values and Development Preferences:  A Method for Tourism and Residential Development Planning.  International Journal of Tourism Research 8:101-113. Link to article.

The author presents a method for measuring and analyzing landscape values and tourism and residential development preferences.  Survey data from Kangaroo Island, South Australia are analyzed to determine the relative strength of landscape values as predictors of place-specific development preferences.  Results indicate tourism development preferences are most closely associated with recreation, economic, and scenic landscape values while residential development preferences are most closely associated (inversely) with recreation, economic, and learning values.  Preferences for “no development” are most closely associated with wilderness, therapeutic, and intrinsic landscape values.  A simple development index is generated from the spatial data that ranges from positive (acceptable development) to negative (no development) values.

10. Raymond, C. and G. Brown. 2006.  A method for assessing protected area allocations using a typology of landscape values.  Journal of Environmental Planning and Management 49(6):797-812. Link to article.

The authors use spatial survey data from the Otways region of Victoria, Australia to present a method that differentiates between public and private lands based on locally perceived landscape values.  Discriminant analysis is used to predict prospective national park expansion areas.  Results indicate survey respondents hold more indirect and less tangible values for national parks and reserves, and more direct use values for private lands.  There was moderate agreement between public and expert-derived national park boundaries.  The authors argue that mapping local landscape values, when combined with expert assessment, can strengthen protected areas planning and management.

11. Raymond, C., and G. Brown. 2007. A spatial method for assessing resident and visitor attitudes toward tourism growth and development. Journal of Sustainable Tourism. 15(5):1-22. Link to article.

The authors compare attitudes toward tourism development in the Otways region of Victoria, Australia, using traditional survey research questions with spatial preferences for development collected in the same survey.  Results from the survey show conditional support for tourism growth and development in the Otway Hinterland and along the Otway Coast while results from spatial attribute data show there are place-specific differences in “acceptable development” and “inappropriate development” preferences. The authors argue the spatial attribute method is an inclusive process that can potentially bridge pro-development and anti-development responses that emerge during community consultation by providing development preference data that is scaleable to both local and regional scales.

12. Brown, G. 2003.  A Method for Assessing Highway Qualities to Integrate Values in Highway Planning.  Journal of Transport Geography 11(4):271-283. Link to article.

The author presents a survey methodology for mapping six intrinsic highway qualities as well as special places to help select and prioritize highways for scenic byways nomination.  Analysis of data from the 2001 statewide survey of Alaska residents is used to develop the concept of a highway experience opportunity spectrum and potential experience opportunity classes.  With knowledge about the spatial locations of intrinsic highway qualities, transportation planners can make informed choices to maintain or alter the set of highway experience opportunities associated with a highway system.

13. Tyrvainen, L., Makinen, K., and J. Schippperjin.  2007.  Tools for mapping social values of urban woodlands and other green areas.  Landscape and Urban Planning  79(1):5–19.

The authors present a simple method to describe the social values of green areas in urban areas for strategic planning purposes.  Using a mail survey in Helsinki, Finland, general attitudes toward the benefits of green areas were measured.  Local residents were asked to identify on a map provided positive qualities such as beautiful scenery, peace and quiet, and the feeling of being in a forest, as well as negative qualities.  The results were mapped in GIS with the most important features associated with favourite places being tranquillity, the feeling of being in a forest, and naturalness.

14. McIntyre, N., Yuan, M.,  Payne, R.J., and J. Moore.  2004.  Development of a values-based approach to managing recreation on Canadian Crown lands.  Proceedings of the second International Conference on Monitoring and Management of Visitor Flows in Recreational and Protected Areas, June 16–20, 2004, Rovaniemi, Finland.

The paper describes an approach that combined both interpretive approaches to data collection (narratives and value mapping) and survey methods in the elicitation of values attached to a working forest. In terms of methods, focus group participants were asked to mark ‘special places’ and associated values directly onto 1:50,000 maps of the study area in the Dog River/Matawin area of North Western Ontario.  Visitors to the area were asked to take photographs during their trips, and to record the subject, location, importance, and positive or negative effect on her/his experience.  Photographs and photo-logs were analysed for expression of values. Finally, a survey was administered (n=487) that asked respondents (residents and visitors) to rate six general forest values and more specific values extracted from analysis of the focus groups.

15. Gunderson, K., Watson, A., Nelson, and J. Titre.  2004.  Mapping place meanings on the Bitterroot National Forest – a landscape-level assessment of personal and community values as input to fuel hazard reduction treatments.  BEMRP Research Project Summary.  Aldo Leopold Wilderness Research Institute. http://leopold.wilderness.net/unpublished/UNP105.pdf

The study used qualitative research methods focusing on local community knowledge to capture as much context as possible about the relationship people have to the Bitterroot Front, Bitterroot National Forest, Montana..  Twelve semi-structured interviews, nine key informant interviews, and two focus groups were used to collect data (33 individuals total).  The interviews included information pertaining to important places visited and places seldom or never visited, but important on the Bitterroot Front, types of recreation and work activities at each specific place, and responses to “why they value” specific places.  Respondents were also asked to circle and rate, in order of importance, the top three specific places they identified on a map provided by the researchers.  Values “hotspots” were identified as areas where there was high incidence of respondent site selection. Site selections fell into 3 classifications for specificity: specific, medium, and broad.  Outside of a few respondents who selected the entire Bitterroot Front as being important, places “not selected” were typically lacking road and trail access.

Landscape Values Theory and Frameworks

1. Rolston, H. and J. Coufal. 1991.  A forest ethic and multivalue forest Management.  Journal of Forestry 89(4):35-40.

The authors challenge the traditional value orientation of the forestry profession and argue for expanding the five statutory public forest values to include both human and biotic elements.  The typology of ten forest values advocated by the authors include life support, economic, scientific, recreation, esthetic, wildlife, biotic diversity, natural history, spiritual, and intrinsic value.  This value typology become the reference standard for the Brown and Reed (2000) typology.

2. Brown, G. and P. Reed. 2000. Validation of a forest values typology for use in national forest planning. Forest Science 46(2):240-247. Link to article.

The authors present data from a survey of Alaska residents in the Chugach National Forest plan revision process to validate a forest values typology inspired by Rolston and Coufal (1991) and to examine the relationship between attitudes toward forest management actions and forest values.  Key findings indicate that: (1) survey respondents were able to identify with 13 distinct forest values based on a modified Rolston and Coufal (1991) forest value typology, (2) no obvious latent structure of variables or constructs emerged from factor analysis of the 13 forest values indicating that the forest value typology may not be easily simplified without compromising the exclusiveness of measured forest values, (3) small, but statistically significant correlations were found between attitudes toward specific forest management practices such as logging and mining and held forest values, and (4) forest values are modestly predictive of respondent preferences for specific forest planning decisions.

3. Tarrant, M.A., Cordell, H.K., and  G.T. Green. 2003. PVF: A Scale to Measure Public Values of Forests. Journal of Forestry 101(6):24-30. Sept. 2003

The authors present a 12 item scale for measuring the relative importance of national forest resources—both economic and noneconomic—based on data collected from the National Survey on Recreation and the Environment.  The scale supports the existence of three latent factors: protection, amenity, and outputs.  The scale had moderate levels of internal reliability and demonstrated predictive validity. Protection values were significantly higher for women, urban residents, and younger respondents. The scale differed from the Brown and Reed value typology in that it did not include scale items that measured spiritual, cultural, historic, or intrinsic values for forests.

4. Manning, R., Valliere, W., and B. Minteer. 1999. Values, ethics, and attitudes toward national forest management: An empirical study. Society and Natural Resources12:421–36.

The authors measured environmental values and ethics and their relationships to attitudes toward national forest management based on a survey of Vermont residents concerning management of the Green Mountain National Forest. Survey findings indicated respondents (1) favor nonmaterial values of national forests, (2) subscribe to a diversity of environmental ethics, including anthropocentric and bio-/ecocentric, and (3) support emerging concepts of ecosystem management. Environmental values and ethics explained approximately 60% of the variation in attitudes toward national forest management.  The values scale differed from the Brown and Reed value typology in that it did not include therapeutic, subsistence, future, and intrinsic values and contained new values labeled intellectual, education, and moral/ethical.  Historic and cultural values were combined in the Manning et al. scale.

5. Studley, J.F.  2005.  Sustainable knowledge systems and resource stewardship: in search of ethno-forestry paradigms for the indigenous peoples of eastern Kham.  Doctoral thesis.  Loughborough University. 481 p.  http://hdl.handle.net/2134/2101

The author uses the forest values typology developed by Brown and Reed (2000) with indigenous peoples of the Kham region in Tibet.  In field trials of the values typology, individuals were asked to distribute 100 pins representing the total value of the forest across a set of 13 paper circles on the basis of the relative importance of each value to them.  The method appeared to work reasonably well with all values used, although the list of forest values was later expanded to include more culturally-bound forest values.  The use of the forest values typology was a small part of a larger investigation to cognitively map forest values among Tibetan minority nationalities, to map their spatial distribution, and to correlate changes in forest values with cultural and biophysical phenomena. 

6. Brown, G. and Raymond, C. 2007. The relationship between place attachment and landscape values: Toward Mapping Place Attachment. Applied Geography.  27:89-111. Link to article.

The authors examine the external validity of a two-dimensional place attachment scale (Williams and Vaske, 2003) in Australia and its relationship with place-based landscape values.  The place attachment scale and landscape value measures were included in a mail survey of residents and visitors to the Otways region (Victoria, Australia).  Regression analysis is used to show that landscape importance values, especially spiritual and wilderness values, are significant predictors of the scale-based measure of place attachment. The relationship between a map-based measure of place attachment and mapped landscape values is explored. Spatial cross-correlation and regression analyses show that aesthetic, recreation, economic, spiritual, and therapeutic values spatially co-locate with special places and thus likely contribute to place attachment. The authors argue that survey mapping of landscape values and special places provides a reasonable proxy for scale-based measures of place attachment while providing richer, place-based information for land use planning.

7. Alessa, N., Kliskey, A., and G. Brown. 2008. Social-ecological hotspots mapping: a spatial approach for identifying coupled social-ecological space. Landscape and Urban Planning. 85(1):27-39. Link to article.

The authors present a method for identifying coupled social-ecological hotspots, spatial areas of convergence between high human and ecological values. Using data from mapped landscape values in Alaska and a measure of net primary productivity, the authors overlay social space with ecological space in the same region. Values hotspots (and warm spots) are determined using kernel density estimation methods. The potential value of social-ecological systems mapping is highlighted using an example of land use planning under the Coastal Zone Management Act.

8. Brown, G. 2008.  A theory of urban park geography.  Journal of Leisure Research 40(4): 589-607. Link to article.

A theory of urban park values is presented using the theory of island biogeography as an analogue.  Viewing urban parks as islands within a virtual sea of development, the theory predicts that two factors—the size of park and distance from concentrated human habitation—influence the diversity of park values.  All other factors being equal, the diversity of human values for parks will increase with park size while the diversity of park values will decrease the further one moves from concentrated areas of human habitation.  Spatial data from a study of Anchorage, Alaska residents indicate a relatively strong relationship between park size and the diversity of park values and a weak, inverse relationship between distance from domicile and diversity of park values.  The results also indicate that: 1) park value diversity differs by NRPA classification with the smallest classification—neighborhood parks—having the lowest value diversity and natural resource area parks having the highest value diversity, 2) neighborhood parks contain significantly higher social/cultural values than community or natural resource area parks, and 3) community and natural resource area parks contain significantly higher natural and wildlife values than neighborhood parks.  The implications of the theory for urban area park planning are discussed.

9. Nielsen-Pincus, Max. 2011. Mapping landscape values: An analysis of methods and geographical associations among values at the landscape scale. Society & Natural Resources. 24(6): 535-552.

The author uses a landscape values typology to investigate how values are mapped on the landscape in three counties of Idaho and Oregon and compares empirically collected values data to environmental values theory.  The author examines the spatial scale at which participants collectively map regions of value and the geographic associations between different values in the typology.  The results demonstrate that a given area can offer multiple values to communities.  Furthermore, when geographically operationalized the landscape values typology can be divided primarily into two categories: material (socioeconomic quality) and postmaterial (personal/environmental quality) values.  The findings reflect on the need for land use planners, natural resource managers, and local decision makers to facilitate both material and postmaterial values in their decisions. 

10. Black, Anne E. and Adam Liljeblad. Working paper. Mapping place values on public lands. Available from Anne Black, Aldo Leopold Wilderness Research Institute, USDA Forest Service, Rocky Mountain Research Station, Missoula, MT. aeblack@fs.fed.us

This paper presents a theoretically-based method for integrating social and ecological data in a GIS format usable by ecological models. The authors collected social data on place attachment by asking attendees at public meetings to draw on hard-copy maps. Information was digitized with attributes and explanations populating the text fields to create GIS datasets designating important social places to allow simulation modeling between management actions and place values. By creating spatial data representing local residents’ place attachment and integrating this with a vegetation simulator, the method provide managers and the public the ability to consider the longer-term consequences of alternative fuels, fire and land management activities on both social and ecological values.

Landscape Value Applications

1. Clement, J. and A. Cheng. 2010.  Using analyses of public value orientations, attitudes and preferences to inform national forest planning in Colorado and Wyoming. Applied Geography 31:393-400. 

This article presents results and discusses implications from social surveys conducted on three national forests in Colorado and Wyoming. The results indicate that although respondents identified aesthetic, biodiversity, future and recreation value orientations as most important, there are also surprising linkages between value orientations, attitudes and preferences towards forest uses and policy options associated with specific geographic and socio-economic contexts and conditions. The results also
suggest some “hotspots” where value orientations, attitudes and preferences display some apparent contradictions.

2. Max Nielsen-Pincus, Caren S. Goldberg, Amy Pocewicz, Jo Ellen Force,
Lisette P. Waits, Penelope Morgan, Lee Vierling.  2010.  Predicted effects of residential development on a northern Idaho landscape under alternative growth management and land protection policies.  Landscape and Urban Planning 94:255–263.

The authors assessed two policy tools, urban growth boundaries and agricultural use zoning, for their potential to help manage growth and sustain the rural
landscape. Using a survey-based model, they simulated the effects of the two policy tools on land use change and compared the results with predictions of land use change for two rural counties (4794km2) in northern Idaho developed in a previous project. They measured the effects of predicted exurban development using four measures: number of housing units predicted on productive agricultural lands, number of
housing units predicted on a groundwater resource area, changes to a wildfire hazard index for residential structures, and the social acceptability of residential development patterns given current development preferences. The latter measure was measured using data from PPGIS.

3. Brown, G. and L. Alessa.  2005.  A GIS-based Inductive Study of Wilderness Values.  International Journal of Wilderness 11(1):14-18. Link to article.

The authors present the results of spatial analysis of wilderness values in Alaska.  Using data from two regional planning studies, perceived landscape values from inside and outside wilderness areas were compared to determine if proportionate value differences exist between wilderness and non-wilderness areas. Multiple regression analysis was used to confirm the results and determine the relative strength of general landscape values as predictors of wilderness value.  Results indicate that wilderness areas reflect values associated with indirect, intangible or deferred human uses of the landscape—life sustaining, intrinsic, and future values while landscape values outside wilderness areas reflect more direct, tangible, and immediate uses of the landscape—economic, recreation, and subsistence values.  These results are consistent with national survey results on wilderness values for the National Wilderness Preservation System.  The authors suggest that landscape value perceptions can be used to complement GIS-based wilderness inventory methods.

4. Brown, G., C. Smith, L. Alessa, and A. Kliskey. 2004.  A comparison of perceptions of biological value with scientific assessment of biological importance.  Applied Geography 24(2):161-180. Link to article.

The authors assess the spatial coincidence of local perceptions of biological value identified in a survey of Alaska residents with biologically significant areas identified by scientists from a marine conservation workshop.  The results indicate a moderate degree of spatial coincidence between local values and scientific assessment with obvious geographic areas of agreement and disagreement in the study area of Prince William Sound, Alaska.  The authors argue that incorporation of local perceptions of biological importance can complement and strengthen scientific biological assessments and they propose an iterative conservation planning process that includes both methodologies. 

5. Reed, P. and G. Brown. 2003. Values Suitability Analysis: A Methodology for Identifying and Integrating Public Perceptions of Forest Ecosystem Values in National Forest Planning.  Journal of Environmental Planning and Management 46(5):643-658. Link to article.

The authors present a planning methodology called "values suitability analysis" (VSA) that combines the features of expanded public participation with a rational, analytic framework for incorporating human values into forest plan decision making. The VSA methodology provides a means to evaluate and compare how “logically consistent” potential management prescriptions (set of activities) are with publicly held forest values.  Based on a spatial inventory of landscape values, the VSA methodology constructs a numerical rating, or set of ratings, for each management prescription and landscape value interaction.  These ratings are used to determine (1) which management prescription is most compatible with the dominant landscape value within a given management area, as well as (2) the marginal difference in overall compatibility between alternative management prescriptions.  The VSA methodology can be used to generate forest plan alternatives or serve as a benchmark to evaluate different forest plan alternatives.  The authors believe adoption of VSA may be hampered by lack of trust and other institutional issues.

6. Brown, G., P. Reed, and C.C. Harris. 2002. Testing a Place-Based Theory for Environmental Evaluation: an Alaska Case Study.  Applied Geography. 22(1):49-77. Link to article.

The authors test Norton and Hannon’s (1997) theory of environmental evaluation that is based on a commitment to place or “sense of place” using community-based survey data collected as part of the planning process for the Chugach National Forest (Alaska).  The theory suggests that humans engage in geographic discounting (humans like to be near positive place attributes and far from negative place attributes) which is influenced by sense of place.  The empirical evidence provides moderate support for the theory that community place attachment is related to distance and intensity of environmental valuation, i.e., how individuals within a community perceive landscape values around their community.  Given the results, the authors highlight the importance of community-based environmental analysis.

 

Technical Reports

1. Weber, D. and G. Brown. 2014. Identifying and Mapping the Values of Victorian Public Lands. University of Queensland and University of South Australia.

2. Brown, G., and D. Weber. 2012. Community Mapping of Park Experiences & Environmental Impacts in South West Victoria: A PPGIS Study. University of Queensland and University of South Australia.

3. Brown, G., D. Weber, and D. Zanon. 2009. Mapping Park Experiences and Environmental Impacts in the Greater Alpine Region of Victoria, Australia: A PPGIS Survey of Park Visitors. (Note: 42 MB file downlaod). University of South Australia, Central Washington Univeresity, and Parks Victoria.

4. Brown, G., C. Raymond. 2006. Mapping Spatial Attributes for Conservation and Tourism Planning: A Survey of Residents and Visitors. CRC for Sustainable Tourism. Griffith University, Gold Coast, Australia. http://www.crctourism.com.au. ISBN: 192070476 0