Designing profitable and climate-smart farms using virtual reality

35. Song C, Yang J, Wu F, Xiao X, Xia J, Li X. Response characteristics and influencing factors of carbon emissions and land surface temperature in Guangdong Province, China. Urban Climate. 2022; 46. https://doi.org/10.1016/j.uclim.2022.101330 36. Ren J, Yang J, Wu F, Sun W, Xiao X, Xia JC. Regional thermal environment changes: Integration of sat- ellite data and land use/land cover. iScience. 2023; 26(2):105820. Epub 2023/01/24. https://doi.org/10. 1016/j.isci.2022.105820 PMID: 36685034; PubMed Central PMCID: PMC9852933. 37. Zhang D, Zhou C, He B-J. Spatial and temporal heterogeneity of urban land area and PM2.5 concentra- tion in China. Urban Climate. 2022; 45. https://doi.org/10.1016/j.uclim.2022.101268 38. Qiao Z, Liu L, Qin Y, Xu X, Wang B, Liu Z. The Impact of Urban Renewal on Land Surface Temperature Changes: A Case Study in the Main City of Guangzhou, China. Remote Sensing. 2020; 12(5). https:// doi.org/10.3390/rs12050794 39. Chen Y, Yang J, Yu W, Ren J, Xiao X, Xia JC. Relationship between urban spatial form and seasonal land surface temperature under different grid scales. Sustainable Cities and Society. 2023; 89. https:// doi.org/10.1016/j.scs.2022.104374 40. Han D, Xu X, Qiao Z, Wang F, Cai H, An H, et al. The roles of surrounding 2D/3D landscapes in park cooling effect: Analysis from extreme hot and normal weather perspectives. Building and Environment. 2023; 231. https://doi.org/10.1016/j.buildenv.2023.110053 41. Norton D, Suryaningrum F, Buckley H, Case B, Cochrane H, Forbes A, et al. Achieving win-win out-

comes for pastoral farming and biodiversity conservation in New Zealand. New Zealand Journal of Ecol- ogy. 2020; 44(2). https://doi.org/10.20417/nzjecol.44.15 42. Grêt-Regamey A, Celio E, Klein TM, Wissen Hayek U. Understanding ecosystem services trade-offs with interactive procedural modelling for sustainable urban planning. Landscape and Urban Planning. 2013; 109(1):107–16. https://doi.org/10.1016/j.landurbplan.2012.10.011 43. Sheppard SRJ. Landscape visualisation and climate change: the potential for influencing perceptions and behaviour. Environmental Science & Policy. 2005; 8(6):637–54. https://doi.org/10.1016/j.envsci. 2005.08.002 44. Cesium. Bring the real world to Unreal Engine, Cesium, Retrieved January 12, 2023 from https:// cesium.com/platform/cesium-for-unreal/. 2023. 45. Liu X, Tvinnereim E, Grimsrud KM, Lindhjem H, Velle LG, Saure HI, et al. Explaining landscape prefer- ence heterogeneity using machine learning-based survey analysis. Landscape Research. 2021; 46 (3):417–34. https://doi.org/10.1080/01426397.2020.1867713 46. van Berkel DB, Verburg PH. Spatial quantification and valuation of cultural ecosystem services in an agricultural landscape. Ecological Indicators. 2014; 37:163–74. https://doi.org/10.1016/j.ecolind.2012. 06.025 47. van Zanten BT, Verburg PH, Koetse MJ, van Beukering PJH. Preferences for European agrarian land- scapes: A meta-analysis of case studies. Landscape and Urban Planning. 2014; 132:89–101. https:// doi.org/10.1016/j.landurbplan.2014.08.012

48. Norde´n A, Coria J, Jo¨nsson AM, Lagergren F, Lehsten V. Divergence in stakeholders’ preferences: Evi- dence from a choice experiment on forest landscapes preferences in Sweden. Ecological Economics. 2017; 132:179–95. https://doi.org/10.1016/j.ecolecon.2016.09.032 49. Klein LR, Hendrix WG, Lohr VI, Kaytes JB, Sayler RD, Swanson ME, et al. Linking ecology and aesthet- ics in sustainable agricultural landscapes: Lessons from the Palouse region of Washington, U.S.A. Landscape and Urban Planning. 2015; 134:195–209. https://doi.org/10.1016/j.landurbplan.2014.10. 019 50. Sahraoui Y, Clauzel C, Foltête J-C. A metrics-based approach for modelling covariation of visual and ecological landscape qualities. Ecological Indicators. 2021; 123. https://doi.org/10.1016/j.ecolind.2020. 107331 51. Swaffield S, McWilliam W. Landscape aesthetic experience and ecosystem services In Dymond JR ed. Ecosystem services in New Zealand–conditions and trends. Manaaki Whenua Press, Lincoln, New Zealand. 2013. 52. Finger R, Swinton SM, El Benni N, Walter A. Precision Farming at the Nexus of Agricultural Production and the Environment. Annual Review of Resource Economics. 2019; 11(1):313–35. https://doi.org/10. 1146/annurev-resource-100518-093929 53. Ingram J, Maye D. What Are the Implications of Digitalisation for Agricultural Knowledge? Frontiers in Sustainable Food Systems. 2020; 4. https://doi.org/10.3389/fsufs.2020.00066 54. Weersink A, Fraser E, Pannell D, Duncan E, Rotz S. Opportunities and Challenges for Big Data in Agri-

cultural and Environmental Analysis. Annual Review of Resource Economics. 2018; 10(1):19–37. https://doi.org/10.1146/annurev-resource-100516-053654 PLOS ONE Designing profitable and climate-smart farms using virtual reality PLOS ONE | https://doi.org/10.1371/journal.pone.0286723 June 2, 2023 15 / 16