Abstract
How do local community perceive pollution risk and social problems in abandoned areas? Which factors affect these risk perceptions? Among several factors affecting environmental perceptions, familiarity to places has long been known to positively affect landscape perception, but is this also true for abandoned area with scruffy vegetation and industrial remnants? Will long-term residents eventually adapt to and accept these neglected landscapes? In the past, efforts have largely been devoted to the cleanup of large, highly polluted areas. This left many smaller, less polluted sites, often in urban or suburban areas, relatively neglected. These areas, which typically consist of small abandoned industrial and commercial sites and vacant lots in neighborhoods, are problematic since people living nearby continue to suffer from urban blight. Recently, there has been a shift in the focus of brownfield programs from highly polluted post-industrial cleanup to local brownfield reuse. In this new environment, a participatory planning process that engages the community seems to have become more important. In order to better understand factors affecting community people’s risk perception and effectively engage community support for the better management of derelict sites, this study investigated the factors on local community perceptions of abandoned landscapes including the effect of familiarity (the length of residency) and other sociodemographic (gender and age). For the study, the 200 study participants in eight neighborhoods along the Rail Corridor Revitalization Project in the city of Roanoke, VA, were asked to participate in survey and evaluate scenes of three types of abandoned landscapes focusing on two aspects, preference and pollution concerns. The results of scene ratings showed that lower scene preferences were associated with scene concerns related to higher pollution. However, although age and gender were associated with participants’ preference ratings and attitudes toward social problems and pollution, there was no significant effect for the length of residency.

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References
Andrews M, Gatersleben B (2010) Variations in perceptions of danger, fear and preference in a simulated natural environment. J Environ Psychol 30(4):473–481
Appleton J (1975) The experience of landscape. Wiley, London
Daniel TC (2001) Whither scenic beauty? Visual landscape quality assessment in the 21st century. Landsc Urban Plan 54(1):267–281
Daniel TC, Vining J (1983) Methodological issues in the assessment of landscape quality. In: Altman I, Wohlwill J (eds) Behavior and the natural environment. Plenum PressSpringer, US, New York, pp 39–84
Dearden P (1984) Factors influencing landscape preferences: an empirical investigation. Landsc P 11(4):293–306
Erdem M, Nassauer JI (2013) Design of brownfield landscapes under different contaminant remediation policies in Europe and the United States. Landsc J 32(2):277–292
Frantz CM, Mayer FS (2014) The importance of connection to nature in assessing environmental education programs. Stud Educ Eval. 41:85–89
Giovanis E, Ozdamar O (2018) Health status, mental health and air quality: evidence from pensioners in Europe. Environ Sci Pollut Res 25(14):14206–14225
Gliner JA, Leech NL, Morgan GA (2002) Problems with null hypothesis significance testing (NHST): what do the textbooks say? J Exp Educ 71(1):83–92
Gobster PH (1999) An ecological aesthetic for forest landscape management. Landsc J 18(1):54–64
Herzog TR (1995) A cognitive analysis of preference for urban nature. In: Sinha A (ed) Landscape perception, 65_82. Academic Press, New York
Herzog TR, Herbert EJ, Kaplan R, Crooks CL (2000) Cultural and developmental comparisons of landscape perceptions and preferences. Environ Behav 32(3):323–346
Hofmann M, Westermann JR, Kowarik I, van der Meer E (2012) Perceptions of parks and urban derelict land by landscape planners and residents. Urban For Urban Green 11(3):303–312
Jakle JA, Wilson D (1992) Derelict landscape: the wasting of America’s built environment. Rowman & Littlefield, Savage
Jarosz AF, Wiley J (2014) What Are the Odds? A Practical Guide to Computing and Reporting Bayes Factors. The Journal of Problem Solving 7 (1)
Kaplan R (1990) The perception of landscape style: a cross-cultural comparison. Landsc Urban Plan 19(3):251_262
Kaplan R, Kaplan S (1989) The experience of nature: a psychological perspective. Cambridge University Press, New York
Kim EJ, Miller P (2015) Periodic characteristics and implications of programs and policies for brownfield management in the U.S.A. Kor. Inst of Landsc A J 43(1):96–107
Kim KH, Choi JW, Lee E, Cho YM, Ahn HR (2015) A study on the risk perception of light pollution and the process of social amplification of risk in Korea. Environ Sci Pollut Res 22(10):7612–7621
Krinke R (2001) Overview: design practice and manufactured sites. In: Kirkwood N (ed) Manufactured sites: rethinking the post-industrial landscape. Spon Press, New York, pp 125–149
Krlozu N (2016) Youths’ perception and knowledge towards environmental problems in a developing country: in the case of Ataturk University, Turkey. Environ Sci Pollut Res 23(12):12482–12490
Krypotos AM, Blanken TF, Arnaudova I, Matzke D, Beckers T (2017) A primer on Bayesian analysis for experimental psychopathologists. J Exp Psychopathol 8(2):140–157
Lafortezza R, Corry RC, Sanesi G, Brown RD (2008) Visual preference and ecological assessments for designed alternative brownfield rehabilitations. J Environ Manag 89(3):257–269
Lippard LR (1998) The lure of the local: sense of place in a multicentered society. New Press, New York
Lothian A (1999) Landscape and the philosophy of aesthetics: is landscape quality inherent in the landscape or in the eye of the beholder? Landsc Urban Plan 44(4):177–198
Matsunaga M (2010) How to factor-analyze your data right: do’s, don’ts, and how-to’s. International Journal of Psychological Research 3(1):97–110
Maulan S (2006) A perceptual study of wetlands: implications for wetland restoration in the urban areas in Malaysia (Doctoral dissertation, Virginia Polytechnic Institute and State University)
Mott JH, Bowen EE (2014) Teaching NHST vs Bayesian inference in postsecondary technology programs. In: Proceedings of the 9th International Conference on Teaching Statistics
Nassauer JI (1995) Messy ecosystems, orderly frames. Landsc J 14(2):161–170
Osborne JW (2015) What is rotating in exploratory factor analysis. Pract Assess Res Eval 20(2):1–7
Ruelle C, Halleux JM, Teller J (2013) Landscape quality and brownfield regeneration: a community investigation approach inspired by landscape preference studies. Landsc Res 38(1):75–99
Ryan RL (1998) Local perceptions and values for a mid-western river corridor. Landsc Urban Plan 42(2):225–237
Sklenicka P, Molnarova K (2010) Visual perception of habitats adopted for post-mining landscape rehabilitation. Environ Manag 46(3):424–435
Southworth M (2001) Wastelands in the evolving metropolis. Institute of Urban & Regional Development Working Paper Series. University of California, Berkeley
Tang IC, Sullivan WC, Chang CY (2015) Perceptual evaluation of natural landscapes the role of the individual connection to nature. Environ Behav 47(6):595–617
van de Schoot R, Depaoli S (2014) Bayesian analyses: where to start and what to report. Eur. Health Psychol 16(2):75–84
Woods J (1995) Environmental factors that influence preference and price perceptions of commercial landscapes and storefronts (Doctoral dissertation, Virginia Polytechnic Institute and State University)
Zube EH, Sell JL, Taylor JG (1982) Landscape perception: research, application and theory. Landsc P 9(1):1–33
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Kim, E.J., Kang, Y. Relationship among pollution concerns, attitudes toward social problems, and environmental perceptions in abandoned sites using Bayesian inferential analysis. Environ Sci Pollut Res 26, 8007–8018 (2019). https://doi.org/10.1007/s11356-019-04272-5
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DOI: https://doi.org/10.1007/s11356-019-04272-5
