Abstract
Sorry, not available.
Click the PDF button.
References
Information
Click the PDF button.
- 강영옥・조나혜・박소연・김지연, 2021, “합성곱신경망을 활용한 SNS 사진 분류 및 관광객과 거주자의 관광활동 특성 분석,” 대한지리학회지, 56(3), 247-264.
- 권헌교・신원섭・김재준, 2004, “도시림의 유형에 따른 이용편익 비교,” 한국산림휴양학회지, 8(2), 37-46.
- 길대영・전가현・이강, 2017, “딥러닝 알고리즘을 활용한 건설현장사진의 공종별 분류에 대한 기초 연구,” 대한건축학회 학술발표대회 논문집, 32(2), 785-786.
- 김동하・백규승・김용대, 2017, “딥러닝 모형의 복잡도에 관한 연구,” 한국데이터정보과학회지, 28(6), 1217-1227.
- 김지원・표현아・하정우・이찬규・김정희, 2015, “다양한 딥러닝 알고리즘과 활용,” 정보과학회지, 33(8), 25-31.
- 김충열・문현식・김태운・조민기・강미영・안기완・임효인, 2016, “이용객 모니터링을 통한 울산 대왕암 도시숲의 관리방안,” 한국도서연구, 28(4), 139-154.
- 박선아・이명우, 2016, “숲 공간유형별 특성에 따른 치유효과 분석: 심리적 회복감과 만족도를 중심으로,” 한국조경학회지, 44(4), 75-85.
- 박제강・박용규・온한익・강동중, 2015, “딥러닝을 이용한 영상내 물체 인식 기법,” 제어・로봇・시스템학회 논문지, 21(4), 21-26.
- 유윤희・연평식・신원섭, 2013, “도시림의 유형에 따른 회복환경지각척도의 비교,” 한국산림휴양학회지, 17(1), 33-45.
- 이승훈, 2011, “심리적 지표 평가에 의한 도시와 옥상정원, 숲의 경관 비교,” 서울도시연구, 12(3), 53-65.
- 이승훈, 2012, “녹시율과 회복환경 간의 정적 관계에 대한 배경스트레스원의 가법적 영향 검증,” 서울도시연구, 13(2), 187-205.
- 이승훈・현명호, 2003, “한국판 회복환경지각척도의 요인구조,” 한국심리학회지, 8(2), 229-241.
- 임승빈, 2009, 「경관분석론」, 서울: 서울대학교 출판부.
- 정성철・이민하・구교상・조은경・한상열・허태철・주성현, 2010, “도시림 조성・관리 방안에 관한 시민-공무원 인식조사,” 한국산림휴양학회지, 14(3), 39-45.
- 홍은빈・전준호・이승용, 2016, “사진 구도 개선을 위한 딥러닝 기반 반복적 크롭핑,” 정보과학회논문지, 43(12), 1356-1364.
- 황주연・임동섭・백두원, 2009, “직선 성분을 이용하는 구도가 유사한 사진 검색 방법,” 한국멀티미디어학회논문지, 12(11), 1539-1546.
- Barona, C.O., 2015, Adopting public values and climate change adaptation strategies in urban forest management: A review and analysis of the relevant literature, Journal of Environmental Management, 164, 215-221.
- Bell, S.L., Foley, R., Houghton, F., Maddrell, A., and Williams, A.M., 2018, From therapeutic landscapes to healthy spaces, places and practices: A scoping review, Social Science & Medicine, 196, 123-130.
- Buscombe, D. and Ritchie, A.C., 2018, Landscape classification with deep neural networks, Geosciences, 8(7), 244.
- Carvalho-Ribeiro, S.M. and Lovett, A., 2011, Is an attractive forest also considered well managed? Public preferences for forest cover and stand structure across a rural/urban gradient in northern Portugal, Forest Policy and Economics, 13(1), 46-54.
- Chen, W.Y. and Jim, C.Y., 2010, Resident motivations and willingness-to-pay for urban biodiversity conservation in Guangzhou (China), Environmental Management, 45, 1052-1165.
- Chen, B. and Nakama, Y., 2015, Residents’ preference and willingness to conserve homestead woodlands Coastal villages in Okinawa Prefecture, Urban Forestry & Urban Greening, 14, 919-931.
- Collado, S., Staats, H., and Sorrel, M.A., 2016, A relational model of perceived restorativeness: Intertwined effects of obligations, familiarity, security and parental supervision, Journal of Environmental Psychology, 48, 24-32.
- Daniel, T.C. and Vining, J., 1983, Methodological issues in the assessment of landscape quality, Human Behavior and Environment, 6, 39-84.
- Deng, J., Andrada, R., and Pierskalla, C., 2017, Visitors’ and residents’ perceptions of urban forests for leisure in Washington D.C., Urban Forestry & Urban Greening, 28, 1-11.
- Donovan, G.H. and Butry, D.T., 2010, Trees in the city: Valuing street trees in Portland, Oregon, Landscape and Urban Planning, 94(2), 77-83.
- Dupont, L., Antrop, M., and Van Eetvelde, V., 2015, Does landscape related expertise influence the visual perception of landscape photographs? Implications for participatory landscape planning and management, Landscape and Urban Planning, 141, 68-77.
- Eggers, J., Lindhagen, A., Lind, T., Lamas, T., and Ohman, K., 2018, Balancing landscape-level forest management between recreation and wood production, Urban Forestry & Urban Greening, 33, 1-11.
- Endreny, T., Santagata, R., Perna, A., Stefano, C.D., Rallo, R.F., and Ulgiati, S., 2017, Implementing and managing urban forests: A much needed conservation strategy to increase ecosystem services and urban wellbeing, Ecological Modelling, 360, 328-335.
- Feimer, N.R., 1979, Personality and environment perception: Alternative predictive systems and implications for evaluative judgements, Ph.D. Dissertation, University of California, Berkeley.
- Fyhri, A., Jacobsen, J.K.S., and Tømmervik, H., 2009, Tourists’ landscape perceptions and preferences in a Scandinavian coastal region, Landscape and Urban Planning, 91(4), 202-211.
- Gerrish, E. and Watkins, S.L., 2018, The relationship between urban forests and income: A meta-analysis, Landscape and Urban Planning, 170, 293-308.
- Guo, Z., Shao, X., Xu, Y., Miyazaki, H., Ohira, W., and Shibasaki, R., 2016, Identification of village building via Google Earth images and supervised machine learning methods, Remote Sensing, 8(4), 271.
- Hagerhall, C.M., 2001, Consensus in landscape preference judgements, Journal of Environmental Psychology, 21(1), 83-92.
- Hartig, T., Kaiser, F.G., and Bowler, P.A., 1997, Further development of a measure of perceived envrionmental restorativeness (Working paper no 5), Gävle, Sweden: Uppsala University, Institute for Housing Research.
- Hauru, K., Lehvavirta, S., Korpela, K., and Kotze, D.J., 2012, Closure of view to the urban matrix has positive effects on perceived restorativeness in urban forests in Helsinki, Finland, Landscape and Urban Planning, 107, 361-369.
- Herzog, T.R. and Stark, J.L., 2004, Typicality and preference for positively and negatively valued environmental settings, Journal of Environmental Psychology, 24(1), 85-92.
- Hoyle, H., Hitchmough, J., and Jorgensen, A., 2017, All about the ‘wow factor’? The relationship between aesthetics, restorative effect and perceived biodiversity in designed urban planting, Landscape and Urban Planning, 164, 109-123.
- Hu, S., Yue, H., and Zhou, Z., 2019, Preferences for urban stream landscapes: Opportunities to promote unmanaged riparian vegetation, Urban Forestry & Urban Greening, 38, 114-123.
- Kang, Y., Cho, N., Yoon, J., Park, S., and Kim, J., 2021, Transfer learning of a deep learning for exploring tourists’ urban image using geotagged photos, ISPRS International Journal of Geo-Information, 10(3), 137.
- Kaplan, R., 2004, The social values of forests and trees in urbanized societies, IUFRO World Series, 14, 167-178.
- Kaplan, R. and Kaplan, S., 1989, The experience of nature: A psychological perspective, New York: Cambridge University Press.
- Kaplan, S., 1995, The restorative benefits of nature: Toward an integrative framework, Journal of Environmental Psychology, 15(3), 169-182.
- Korpela, K. and Hartig, T., 1996, Restorative qualities of favorite places, Journal of Environmental Psychology, 16, 221-233.
- Krizhevsky, A., Sutskever, I., and Hinton, G.E., 2017, ImageNet classification with deep convolutional neural networks, Communications of the ACM, 60(6), 84-90.
- López-Martínez, F., 2017, Visual landscape preferences in Mediterranean areas and their socio-demographic influences, Ecological Engineering, 104, 205-215.
- MA: Millennium Ecosystem Assessment, 2005, Ecosystems and Human Well-being: Current States and Trends, Washington D.C.: Island Press.
- Mattila, O., Korhonen, A., Poyry, E., Hauru, K., Holopainen, J., and Parvinen, P., 2020, Restoration in a virtual reality forest environment, Computers in Human Behavior, 107, 106295.
- Merry, K., Bettinger, P., Siry, J., and Bowker, J.M., 2020, Preferences of motorcyclists to views of managed, rural southern United States landscapes, Journal of Outdoor Recreation and Tourism, 29, 100259.
- Middel, A., Lukasczyk, J., Zakrzewski, S., Arnold, M., and Maciejewski, R., 2019, Urban form and composition of street canyons: A human-centric big data and deep learning approach, Landscape and Urban Planning, 183, 122-132.
- Nielsen, A.B., Gundersen, V.S., and Jensen, F.S., 2018, The impact of field layer characteristics on forest preference in Southern Scandinavia, Landscape and Urban Planning, 170, 221-230.
- Pasini, M., Berto, R., Brondino, M., Hall, R., and Ortner, C., 2014, How to measure the restorative quality of environments: The PRS-11, Procedia Social and Behavioral Sciences, 159, 293-297.
- Pazhouhanfar, M. and Kamal, M., 2014, Effect of predictors of visual preference as characteristics of urban natural landscapes in increasing perceived restorative potential, Urban Forestry & Urban Greening, 13, 145-151.
- Peckham, S.C., Duinker, P.N., and Ordonez, C., 2013, Urban forest values in Canada: Views of citizens in Calgary and Halifax, Urban Forestry & Urban Greening, 12, 154-162.
- Peschardt, K.K. and Stigsdotter, U.K., 2013, Associations between park characteristics and perceived restorativeness of small public urban green spaces, Landscape and Urban Planning, 112, 26-39.
- Sang, Å.O. and Tveit, M.S., 2013, Perceptions of stewardship in Norwegian agricultural landscapes, Land Use Policy, 31, 557-564.
- Sevenant, M. and Antrop, M., 2010, The use of latent classes to identify individual differences in the importance of landscape dimensions for aesthetic preference, Land Use Policy, 27(3), 827-842.
- Simkin, J., Ojala, A., and Tyrvainer, L., 2020, Restorative effects of mature and young commercial forest, pristine old-growth forest and urban recreation forest: A field experiment, Urban Forestry & Urban Greening, 48, 126567.
- Sowińska-Świerkosz, B. and Soszyński, D., 2019, The index of the Prognosis Rural Landscape Preferences (IPRLP) as a tool of generalizing peoples’ preferences on rural landscape, Journal of Environmental Management, 248, 109272.
- Stigsdotter, U.K., Corazon, S.S., Sidenius, U., Refshauge, A.D., and Grahn, P., 2017, Forest design for mental health promotion: Using perceived sensory dimensions to elicit restorative responses, Landscape and Urban Planning, 160, 1-15.
- Strumse, E., 1996, Demographic differences in the visual preferences for agrarian landscapes in western Norway, Journal of Environmental Psychology, 16(1), 17-31.
- Tomao, A., Secondi, L., Carrus, G., Corona, P., Portoghesi, L., and Agrimi, M., 2018, Restorative urban forests: Exploring the relationship between forest stand structure, perceived restorativeness and benefits gained by visitors to coastal Pinus pinea forests, Ecological Indicators, 90, 594-605.
- Townsend, J.B. and Barton, S., 2018, The impact of ancient tree form on modern landscape preferences, Urban Forestry & Urban Greening, 34, 205-216.
- Ulrich, R.S., 1983, Aesthetic and affective response to natural environment, Behavior and the Natural Environment, 85-125.
- Ulrich, R.S., 1984, View through a window may influence recovery from surgery, Science, 224(4647), 420-421.
- Van den Berg, A.E. and Koole, S.L., 2006, New wilderness in the Netherlands: An investigation of visual preferences for nature development landscapes, Landscape and Urban Planning, 78(4), 362-372.
- Wang, R. and Zhao, J., 2017, Demographic groups’ differences in visual preference for vegetated landscapes in urban green space, Sustainable Cities and Society, 28, 350-357.
- Wang, R., Zhao, J., and Liu, Z., 2016, Consensus in visual preferences: The effects of aesthetic quality and landscape types, Urban Forestry & Urban Greening, 20, 210-217.
- Wang, W., Zhao, M., Wang, L., Huang, J., Cai, C., and Xu, X., 2016, A multi-scene deep learning model for image aesthetic evaluation, Signal Processing: Image Communication, 47, 511-518.
- Wilde, E.N. and Maxwell, J.T., 2018, Comparing climate-growth responses of urban and non-urban forests using L. tulipifera tree-rings in southern Indiana, USA, Urban Forestry & Urban Greening, 31, 103-108.
- Ye, Y., Zeng, W., Shen, Q., Zhang, X., and Lu, Y., 2019, The visual quality of streets: A human-centered continuous measurement based on machine learning algorithms and street view images, Environment and Planning B: Urban Analytics and City Science, 46(8), 1439-1457.
- Yu, C.P., Lee, H.Y., Lu, W.H., Huang, Y.C., and Browning, M.H.E.M., 2020, Restorative effects of virtual natural settings on middle-aged and elderly adults, Urban Forestry & Urban Greening, 56, 126863.
- Yu, C.P. and Hsieh, H., 2020, Beyond restorative benefits: Evaluating the effect of forest therapy on creativity, Urban Forestry & Urban Greening, 51, 126670.
- Yuan, J., Deng, J., Pierskalla, C., and King, B., 2018, Urban tourism attributes and overall satisfaction: An asymmetric impact-performance analysis, Urban Forestry & Urban Greening, 30, 169-181.
- Zhang, F., Zhou, B., Liu, L., Liu, Y., Fung, H.H., Lin, H., and Ratti, C., 2018, Measuring human perceptions of a large-scale urban region using machine learning, Landscape and Urban Planning, 180, 148-160.
- Zhou, H., He, S., Cai, Y., Wang, M., and Su, S., 2019, Social inequalities in neighborhood visual walkability: Using Street View imagery and deep learning technologies to facilitate healthy city planning, Sustainable Cities and Society, 50, 101605.
- Zhou, T., Koomen, E., and van Leeuwen, E.S., 2018, Residents’ preferences for cultural services of the landscape along the urban-rural gradient, Urban Forestry & Urban Greening, 29, 131-141.
- Zube, E.H., Sell, J.L., and Taylor, J.G., 1982, Landscape perception: Research, application and theory, Landscape Planning, 9, 1-33.
- Publisher :The Association of Korean Geographers
- Publisher(Ko) :한국지리학회
- Journal Title :Journal of the Association of Korean Geographers
- Journal Title(Ko) :한국지리학회지
- Volume : 10
- No :2
- Pages :277~291
- DOI :https://doi.org/10.25202/JAKG.10.2.6


Journal of the Association of Korean Geographers





