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Environmental Management

Erschienen in:

29.06.2023

Exploring the Spatial Pattern of Urban Forest Ecosystem Services based on i-Tree Eco and Spatial Interpolation: A Case Study of Kyoto City, Japan

verfasst von: Yusong Xie, Satoshi Hirabayashi, Shizuka Hashimoto, Shozo Shibata, Jiefeng Kang

Erschienen in: Environmental Management | Ausgabe 5/2023

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Abstract

Urban forest, as an essential urban green infrastructure, is critical in providing ecosystem services to cities. To enhance the mainstreaming of ecosystem services in urban planning, it is necessary to explore the spatial pattern of urban forest ecosystem services in cities. This study provides a workflow for urban forest planning based on field investigation, i-Tree Eco, and geostatistical interpolation. Firstly, trees across an array of land use types were investigated using a sampling method. Then i-Tree Eco was applied to quantify ecosystem services and ecosystem service value in each plot. Based on the ecosystem services estimates for plots, four interpolation methods were applied and compared by cross-validation. The Empirical Bayesian Kriging was determined as the best interpolation method with higher prediction accuracy. With the results of Empirical Bayesian Kriging, this study compared urban forest ecosystem services and ecosystem service value across land use types. The spatial correlations between ecosystem service value and four types of point of interest in urban places were explored using the bivariate Moran’s I statistic and the bivariate local indicators of spatial association. Our results show that the residential area in the built-up area of Kyoto city had higher species richness, tree density, ecosystem services, and total ecosystem service value. Positive spatial correlations were found between ecosystem service value and the distribution of urban space types including the tourist attraction distribution, urban park distribution, and school distribution. This study provides a specific ecosystem service-oriented reference for urban forest planning based on land use and urban space types.

Vorheriger Artikel Environmental effects of a management method used after fire on development of temperate Scots pine ecosystem: a 15-year study from Poland

Nächster Artikel From Conservation to Connection: Exploring the Role of Nativeness in Shaping People’s Relationships with Urban Trees

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Abushammala MFM, Basri NEA, Basri H, Kadhum AAH, El-Shafie AH (2013) Empirical gas emission and oxidation measurement at cover soil of dumping site: Example from Malaysia. Environ Monit Assess 185(6):4919–4932. https://doi.org/10.1007/s10661-012-2913-5CrossRef

Agyeman PC, Kebonye NM, John K, Borůvka L, Vašát R, Fajemisim O (2022) Prediction of nickel concentration in peri-urban and urban soils using hybridized empirical bayesian kriging and support vector machine regression. Sci Rep 12(1):3004. https://doi.org/10.1038/s41598-022-06843-yCrossRef

Akashi T (2007). Urban land use planning system in Japan. Japan International Cooperation Agency.

Baró F, Haase D, Gómez-Baggethun E, Frantzeskaki N (2015) Mismatches between ecosystem services supply and demand in urban areas: A quantitative assessment in five European cities. Ecol Indic 55:146–158CrossRef

Broomhead DS, Lowe D (1988) Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks. Complex Syst 2:321–355

Chen C, Park T, Wang X, Piao S, Xu B, Chaturvedi RK, Fuchs R, Brovkin V, Ciais P, Fensholt R, Tømmervik H, Bala G, Zhu Z, Nemani RR, Myneni RB (2019) China and India lead in greening of the world through land-use management. Nat Sustainability 2(2):122–129. https://doi.org/10.1038/s41893-019-0220-7CrossRef

Collins CMT, Cook-Monie I, Raum S (2019) What do people know? Ecosystem services, public perception and sustainable management of urban park trees in London. U K Urban Forestry Urban Green 43:126362. https://doi.org/10.1016/j.ufug.2019.06.005CrossRef

Dangulla M, Latifah Abd M, Mohammad Firuz R, Mohd Rusli Y (2020) Urban tree composition, diversity and structural characteristics in North-western Nigeria. Urban Forestry Urban Green 48:126512CrossRef

Ding Q, Wang Y, Zhuang D (2018) Comparison of the common spatial interpolation methods used to analyze potentially toxic elements surrounding mining regions. J Environ Manag 212:23–31. https://doi.org/10.1016/j.jenvman.2018.01.074CrossRef

Eisenman T. S, Churkina G, Jariwala S. P, Kumar P, Lovasi G. S, Pataki D. E, Weinberger K. R, Whitlow T. H (2019) Urban trees, air quality, and asthma: An interdisciplinary review. Landscape and Urban Planning 187:47–59. https://doi.org/10.1016/j.landurbplan.2019.02.010CrossRef

Gong C, Xian C, Ouyang Z (2022) Assessment of NO2 Purification by Urban Forests Based on the i-Tree Eco Model: Case Study in Beijing. China For 13(3):369

Gribov A, Krivoruchko K (2020) Empirical Bayesian kriging implementation and usage. Sci Total Environ 722:137290. https://doi.org/10.1016/j.scitotenv.2020.137290CrossRef

Gruebner O, Khan MMH, Lautenbach S, Müller D, Kraemer A, Lakes T, Hostert P (2011) A spatial epidemiological analysis of self-rated mental health in the slums of Dhaka. Int J Health Geographics 10(1):36. https://doi.org/10.1186/1476-072X-10-36CrossRef

Hirabayashi S, Kroll CN, Nowak DJ (2012) I-Tree eco dry deposition model descriptions. Citeseer: Princeton, NJ, USA.

Honjo T, Takakura T (1984) Thermal Effect Greenspace in Urban Area. Agrometeorology 40(3):257–261

i-Tree (2019) I-Tree Manuals, Guides & Workbooks. https://www.itreetools.org/support/resources-overview/i-tree-manuals-workbooks

Jin J, Yang J (2020) Effects of sampling approaches on quantifying urban forest structure. Landsc Urban Plan 195:103722. https://doi.org/10.1016/j.landurbplan.2019.103722CrossRef

Johnston K, Hoef JMV, Krivoruchko K, Lucas N (2001) Using ArcGIS^TM Geostatistical Analyst. Redlands: Esri, 380.

Kalwij JM (2012) Review of ‘The Plant List, a working list of all plant species. J Vegetation Sci 23(5): 5. https://doi.org/10.1111/j.1654-1103.2012.01407.xCrossRef

Kang J, Hirabayashi S, Shibata S (2022) Urban Forest Ecosystem Services Vary with Land Use and Species: A Case Study of Kyoto City. Forests 13(1):1. https://doi.org/10.3390/f13010067CrossRef

Kawaguchi M, Hirabayashi S, Hirase K, Kaga H, Akazawa H (2021) Estimation of monetary value of street trees by i-Tree Eco using tree health surveys in Suita City, Osaka Prefecture. Landsc Res 14:1–12

Krivoruchko K (2012) Empirical Bayesian kriging. ArcUser Fall 6(10):1145

Krivoruchko K, Gribov A (2019) Evaluation of empirical Bayesian kriging. Spat Stat 32:100368. https://doi.org/10.1016/j.spasta.2019.100368CrossRef

Kyoto City Official Website. (2010). Kyoto City Green Plan. https://www.city.kyoto.lg.jp/kensetu/page/0000077122.html

Kyoto City Statistics Portal. (2019). Demographic statistics of Kyoto City. 京都市統計ポータル. https://www2.city.kyoto.lg.jp/sogo/toukei/

Kyoto Prefecture. (2016). Shrines and temples in Kyoto. https://www.pref.kyoto.jp/tokei/monthly/tokeikyoto/tk2016/tkroom201611.pdf

Laurent O, Hu J, Li L, Kleeman MJ, Bartell SM, Cockburn M, Escobedo L, Wu J (2016) A Statewide Nested Case–Control Study of Preterm Birth and Air Pollution by Source and Composition: California, 2001–2008. Environ Health Perspect 124(9):1479–1486. https://doi.org/10.1289/ehp.1510133CrossRef

Li F, Zhang F, Li X, Wang P, Liang J, Mei Y, Cheng W, Qian Y (2017) Spatiotemporal Patterns of the Use of Urban Green Spaces and External Factors Contributing to Their Use in Central Beijing. Int J Environ Res Public Health 14(3):237. https://doi.org/10.3390/ijerph14030237CrossRef

Li X, Jia B, Zhang W, Ma J, Liu X (2020) Woody plant diversity spatial patterns and the effects of urbanization in Beijing, China. Urban Forestry Urban Green 56:126873. https://doi.org/10.1016/j.ufug.2020.126873CrossRef

Lin J, Kroll CN, Nowak DJ (2021) An uncertainty framework for i-Tree eco: A comparative study of 15 cities across the United States. Urban Forestry Urban Green 60:127062. https://doi.org/10.1016/j.ufug.2021.127062CrossRef

Locke DH, Romolini M, Galvin M, O’Neil-Dunne JPM, Strauss EG (2009) Tree Canopy Change in Coastal Los Angeles, 2009–2014. 28.

Ma H, Tong Y (2022) Spatial differentiation of traditional villages using ArcGIS and GeoDa: A case study of Southwest China. Ecol Inform 68:101416. https://doi.org/10.1016/j.ecoinf.2021.101416CrossRef

Ma J, Li X, Baoquan J, Liu X, Li T, Zhang W, Liu W (2021) Spatial variation analysis of urban forest vegetation carbon storage and sequestration in built-up areas of Beijing based on i-Tree Eco and Kriging. Urban Forestry Urban Green 66:127413. https://doi.org/10.1016/j.ufug.2021.127413CrossRef

Ma X, Longley I, Gao J, Kachhara A, Salmond J (2019) A site-optimised multi-scale GIS based land use regression model for simulating local scale patterns in air pollution. Sci Total Environ 685:134–149. https://doi.org/10.1016/j.scitotenv.2019.05.408CrossRef

Ministry of the Environment, Government of Japan (2019) Manual for calculation and valuation of ecosystem services related to biodiversity conservation activities for enterprises (In Japanese). Ministry of the Environment, Government of Japan.

Namdar-Khojasteh D, Yeghaneh B, Maher A, Namdar-Khojasteh F, Tu J (2022) Assessment of the relationship between exposure to air pollutants and COVID-19 pandemic in Tehran city, Iran. Atmos Pollut Res 13(7):101474. https://doi.org/10.1016/j.apr.2022.101474CrossRef

Nowak DJ, Greenfield EJ, Hoehn RE, Lapoint E (2013) Carbon storage and sequestration by trees in urban and community areas of the United States. Environ Pollut 178:229–236CrossRef

Nowak DJ, Hirabayashi S, Bodine A, Greenfield E (2014) Tree and forest effects on air quality and human health in the United States. Environ Pollut 193:119–129CrossRef

Osaka City. (2021). Osaka City Green Plan. https://www.city.osaka.lg.jp/kensetsu/page/0000239835.html

Parsa V, Salehi E, Yavari A, van Bodegom P (2019) Analyzing temporal changes in urban forest structure and the effect on air quality improvement. Sustainable Cities Soc 48. https://doi.org/10.1016/j.scs.2019.101548

Qiao P, Li P, Cheng Y, Wei W, Yang S, Lei M, Chen T (2019) Comparison of common spatial interpolation methods for analyzing pollutant spatial distributions at contaminated sites. Environ Geochem Health 41(6):2709–2730. https://doi.org/10.1007/s10653-019-00328-0CrossRef

Rangel TFLVB, Diniz-Filho JAF, Bini LM (2006) Towards an integrated computational tool for spatial analysis in macroecology and biogeography: Spatial analysis in macroecology. Glob Ecol Biogeogr 15(4):321–327. https://doi.org/10.1111/j.1466-822X.2006.00237.xCrossRef

Raum S, Hand KL, Hall C, Edwards DM, O’Brien L, Doick KJ (2019) Achieving impact from ecosystem assessment and valuation of urban greenspace: The case of i-Tree Eco in Great Britain. Landsc Urban Plan 190:103590. https://doi.org/10.1016/j.landurbplan.2019.103590CrossRef

Riondato E, Pilla F, Sarkar Basu A, Basu B (2020) Investigating the effect of trees on urban quality in Dublin by combining air monitoring with i-Tree Eco model. Sustain Cities Soc 61:102356. https://doi.org/10.1016/j.scs.2020.102356CrossRef

Saiki T (2009) Facts and Considerations on the “Urbanization Rate” in Japan from the Perspective of Regional Economy. https://www.boj.or.jp/research/wps_rev/wps_2009/data/wp09j04.pdf

Seto KC, Shepherd JM (2009) Global urban land-use trends and climate impacts. Curr Opin Environ Sustainability 1:89–95CrossRef

Shabankareh MG, Amanipoor H, Battaleb-Looie S, Dravishi Khatooni J(2018) Zonation of coastal sediments based on the effective properties on the accumulation of heavy metals using the IDW and kriging method (case study: SW Iran). Geocarto Int 33(11):1257–1267 https://doi.org/10.1080/10106049.2017.1343393CrossRef

Shukla K, Kumar P, Mann GS, Khare M (2020) Mapping spatial distribution of particulate matter using Kriging and Inverse Distance Weighting at supersites of megacity Delhi. Sustain Cities Soc 54:101997. https://doi.org/10.1016/j.scs.2019.101997CrossRef

Song P, Kim G, Mayer A, He R, Tian G (2020) Assessing the Ecosystem Services of Various Types of Urban Green Spaces Based on i-Tree Eco. Sustainability 12(4):1630. https://doi.org/10.3390/su12041630CrossRef

Speak A, Escobedo FJ, Russo A, Zerbe S (2018) Comparing convenience and probability sampling for urban ecology applications. J Appl Ecol 55(5):2332–2342. https://doi.org/10.1111/1365-2664.13167CrossRef

Stone M (1974) Cross-Validatory Choice and Assessment of Statistical Predictions. J R Stat Soc: Ser B (Methodol) 36(2):111–133. https://doi.org/10.1111/j.2517-6161.1974.tb00994.xCrossRef

Szkop Z (2020) Evaluating the sensitivity of the i-Tree Eco pollution model to different pollution data inputs: A case study from Warsaw, Poland. Urban Forestry Urban Green 55:126859. https://doi.org/10.1016/j.ufug.2020.126859CrossRef

Tallis M, Taylor G, Sinnett D, Freer-Smith P (2011) Estimating the removal of atmospheric particulate pollution by the urban tree canopy of London, under current and future environments. Landsc Urban Plan 103(2):129–138. https://doi.org/10.1016/j.landurbplan.2011.07.003CrossRef

Tan X, Hirabayashi S, Shibata S (2021) Estimation of Ecosystem Services Provided by Street Trees in Kyoto, Japan. Forests 12(3):3. https://doi.org/10.3390/f12030311CrossRef

Taylor MS, Wheeler BW, White MP, Economou T, Osborne NJ (2015) Research note: Urban street tree density and antidepressant prescription rates—A cross-sectional study in London, UK. Landsc Urban Plan 136:174–179. https://doi.org/10.1016/j.landurbplan.2014.12.005CrossRef

Thaiutsa B, Puangchit L, Kjelgren R, Arunpraparut W (2008) Urban green space, street tree and heritage large tree assessment in Bangkok, Thailand. Urban Forestry Urban Green 7(3):219–229. https://doi.org/10.1016/j.ufug.2008.03.002CrossRef

Tokyo Metropolitan Bureau of Environment. (2018, February 19). Tokyo Green Plan. Bureau of Environment. https://www.kankyo.metro.tokyo.lg.jp/basic/plan/nature/green_tokyo/whole_passage.html

Wang J, Liu R, Zhang P, Yu W, Shen Z, Feng C (2014) Spatial variation, environmental assessment and source identification of heavy metals in sediments of the Yangtze River Estuary. Mar Pollut Bull 87(1–2):364–373. https://doi.org/10.1016/j.marpolbul.2014.07.048CrossRef

Webster R (1985) Quantitative Spatial Analysis of SoD in the Field. Advances in Soil Science. Springer, New York, NY, 1–70.

Wolf KL, Lam ST, McKeen JK, Richardson GRA, van den Bosch M, Bardekjian AC (2020) Urban Trees and Human Health: A Scoping Review. Int J Environ Res Public Health 17(12):4371. https://doi.org/10.3390/ijerph17124371CrossRef

Wu J, Wang Y, Qiu S, Peng J (2019) Using the modified i-Tree Eco model to quantify air pollution removal by urban vegetation. Sci Total Environ 688:673–683. https://doi.org/10.1016/j.scitotenv.2019.05.437CrossRef

Yanto, Apriyono A, Santoso PB, Sumiyanto (2022) Landslide susceptible areas identification using IDW and Ordinary Kriging interpolation techniques from hard soil depth at middle western Central Java, Indonesia. Nat Hazards 110(2):1405–1416. https://doi.org/10.1007/s11069-021-04982-5CrossRef

Yao J, Liu M, Chen N, Wang X, He X, Hu Y, Wang X, Chen W (2021) Quantitative assessment of demand and supply of urban ecosystem services in different seasons: A case study on air purification in a temperate city. Lands Ecol. https://doi.org/10.1007/s10980-020-01112-7

Yao N, Konijnendijk van den Bosch CC, Yang J, Devisscher T, Wirtz Z, Jia L, Duan J, Ma L (2019) Beijing’s 50 million new urban trees: Strategic governance for large-scale urban afforestation. Urban Forestry Urban Green 44:126392. https://doi.org/10.1016/j.ufug.2019.126392CrossRef

Zhang S, Liu J, Song C, Chan C-S, Pei T, Wenting Y, Xin Z (2021) Spatial-temporal distribution characteristics and evolution mechanism of urban parks in Beijing, China. Urban Forestry Urban Green 64:127265. https://doi.org/10.1016/j.ufug.2021.127265CrossRef

Zhang Y, Wu Q, Zhao X, Hao Y, Liu R, Yang Z, Lu Z (2018) Study of carbon metabolic processes and their spatial distribution in the Beijing-Tianjin-Hebei urban agglomeration. Sci Total Environ 645:1630–1642. https://doi.org/10.1016/j.scitotenv.2018.07.033CrossRef

Zhong J, Li Z, Sun Z, Tian Y, Yang F (2020) The spatial equilibrium analysis of urban green space and human activity in Chengdu, China. J Clean Prod 259:120754. https://doi.org/10.1016/j.jclepro.2020.120754CrossRef

R Core Team (2022) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

Titel: Exploring the Spatial Pattern of Urban Forest Ecosystem Services based on i-Tree Eco and Spatial Interpolation: A Case Study of Kyoto City, Japan
verfasst von: Yusong Xie
Satoshi Hirabayashi
Shizuka Hashimoto
Shozo Shibata
Jiefeng Kang
Publikationsdatum: 29.06.2023
Verlag: Springer US
Erschienen in: Environmental Management / Ausgabe 5/2023
Print ISSN: 0364-152X
Elektronische ISSN: 1432-1009
DOI: https://doi.org/10.1007/s00267-023-01847-4

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