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Vegetation Dynamic Monitoring and Driving Factors Analysis in Chengdu in Recent 20 Years Based on Google Earth Engine

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Environmental Pollution Governance and Ecological Remediation Technology (ICEPG 2022)

Part of the book series: Environmental Science and Engineering ((ESE))

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Abstract

Vegetation dynamic monitoring and driving factor analysis are important contents of regional ecological environment assessment. Google Earth Engine (GEE), the MODIS NDVI remote sensing images of Chengdu from 2000 to 2021 were collected, and the maximum synthesis method, trend Finally, temperature, precipitation and artificial impervious area were selected to analyze the vegetation at the pixel scale. The results showed that: (1) Chengdu was mainly composed of medium and high coverage areas The results showed that: (1) Chengdu was mainly composed of medium and high coverage areas, accounting for 57.6% of the total area. Among them, high coverage areas were mainly distributed in the west of Chengdu, while low coverage areas and medium and low coverage areas were mainly distributed in the central urban area of Chengdu; (2) The (2) The vegetation coverage in Chengdu had not changed significantly in the past 20 years (P > 0.05). The area with improved vegetation accounted for 40% and the area with degraded vegetation accounted for 39%. Among them, the areas with significantly improved vegetation (Slope > 0.01) were mainly in Jinniu District, Chenghua District, Wuhou District, Among them, the areas with significantly improved vegetation (Slope > 0.01) were mainly in Jinniu District, Chenghua District, Wuhou District, Qingyang District and Jinjiang District, while the severely degraded areas (Slope < −0.01) were mainly in Pidu District and Xindu District, Qingbaijiang District, Shuangliu District and Wenjiang District; (3) At the regional scale, the central urban area of Chengdu showed a significant (3) At the regional scale, the central urban area of Chengdu showed a significant trend of degradation (P < 0.05, Slope = −0.0027/year), while Dayi County showed a significant trend of improvement (P < 0.05, Slope = 0.0011/year); (4) The overall temperature in Chengdu did not change significantly (P > 0.05), and the precipitation increased significantly in each pixel (P < 0.05, Slope = 10.63 mm/year), and the area with a larger increase was in the eastern part of Chengdu. In addition, the artificial impervious area showed a significant increasing trend (P < 0.05, Slope = 68.30 km2/year). The research results can provide a scientific basis for the formulation of ecological protection and restoration policies in Chengdu.

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References

  • Baoquan J (2013) Analysis of vegetation change and its causes in Beijing based on TM satellite image data. J Ecol 33(5):1654–1666

    Google Scholar 

  • Chen E, Zhao XJ (2022) Spatial and temporal variation of vegetation cover in the Bailong River basin from 2010 to 2020. Green Technol 24(10):1–7

    Google Scholar 

  • Chenghu Z, Weiming C, Jinkai Q et al (2009) Study on the 1:1 million digital landform classification system of China. J Earth Inf Sci 11(6):707–724

    Google Scholar 

  • Dazhong D, Keming C, Shiqian W et al (2009) Shale gas resource evaluation method and its application in Sichuan basin. Nat Gas Ind 29(5):33–39

    Google Scholar 

  • Fibing C (2008) Analysis and optimization of landscape patterns of green space systems in the Central City of Chengdu. Southwest University

    Google Scholar 

  • Goli Z, Ouyang H, Zhang X et al (2010) Vegetation cover change on the Tibetan Plateau and its response to climate change based on ecogeographic zoning. Geogr Studies, 2010, 29(11): 2004–2016.

    Google Scholar 

  • Gong P, Li X, Wang J et al (2020) Annual maps of global artificial impervious area (GAIA) between 1985 and 2018. Rem Sens Environ 236:111510

    Article  Google Scholar 

  • Gorelick N, Hancher M, Dixon M et al (2017) Google earth engine: planetary-scale geospatial analysis for everyone. Rem Sens Environ 202(1):18–27

    Article  Google Scholar 

  • Hao BF, Han XJ, Ma MG et al (2018) Research progress on the application of Google Earth Engine in earth and environmental sciences. Rem Sens Technol Appl 33(4):600–611

    Google Scholar 

  • Baorong H, Baoyin L, Zhisheng H et al (2018) A comprehensive study on the inflection point of ecological and environmental quality in China. Proc Chin Acad Sci 33(10):1072–1082

    Google Scholar 

  • Li H-X, Liu G-H, Fu B-J (2011) Response of vegetation growth to climate change and human activities in the Sanjiangyuan area based on NDVI. J Ecol 31(19):5495–5504

    Google Scholar 

  • Jun-Nan X, Chao P, Wei-Ming C et al (2018) Analysis of vegetation cover change in Yunnan Province based on MODIS-NDVI. J Earth Inf Sci 20(12):1830–1840

    Google Scholar 

  • Li F, Wang RS, Zhao D (2014) Urban eco-infrastructure based on ecosystem services: status, problems and prospects. J Ecol 34(1):190–200

    CAS  Google Scholar 

  • Luying Z, Wen M, Bo P (2020) Characteristics of climate change in Chengdu Plain. J Chengdu Univ Inf Eng 35(2):179–187

    Google Scholar 

  • Ma BX, Jing J, Xu Y et al (2021) Spatial and temporal variation of vegetation NPP in Yunnan-Guizhou-Gui karst region from 2000 to 2019 and its relationship with climate change. J Ecol Environ 30(12):2285–2293

    Google Scholar 

  • Na M, Yunfeng H, Dafang Z et al (2012) Vegetation cover pattern and dynamics in Zhenglan Banner, Inner Mongolia based on remote sensing and image dichotomous model. Geoscience 32(2):251–256

    Google Scholar 

  • Migliavacca M, Musavi T, Mahecha MD et al (2021) The three major axes of terrestrial ecosystem function. Nature 598(7881):468–472

    Article  CAS  Google Scholar 

  • Pan Q, Zheng H, Wang ZH et al (2021) Advances in the study of plant functional traits on ecosystem services. J Plant Ecol 45(10):1140–1153

    Article  Google Scholar 

  • Peng S, Ding Y, Liu W et al (2019) 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Syst Sci Data 11(4):1931–1946

    Article  Google Scholar 

  • Tamiminia H, Salehi B, Mahdianpari M et al (2020) Google earth engine for geo-big data applications: a meta-analysis and systematic review. ISPRS J Photogram Rem Sens Environ 164:152–170

    Article  Google Scholar 

  • Tao Z, Hong T (2018) A study of vegetation cover change and urban expansion in Beijing-Tianjin Hebei from 2001–2015 based on google earth engine. Rem Sens Technol Appl 33(4):593–599

    Google Scholar 

  • Wang BE, Fan GZ, Dong YP et al (2011) Characterization of climate and phenology in Sichuan and Chongqing. Geoscience 31(6):674–681

    CAS  Google Scholar 

  • Wang Z-H, Wang G-H, Wu C-Y (2002) Eco-industrial parks: a strategic choice for sustainable industrial development in China. Sci Technol Herald 20(0212):29–32

    Google Scholar 

  • Zhongbao X, Jiongxin X, Wei Z (2007) Impacts of climate change and human activities on vegetation cover changes on the Loess Plateau. Chin Sci Ser D 37(11):1504–1514

    Google Scholar 

  • Xudong S (2019) Practice and innovation of urban master planning in Chengdu. Planner 20:67–74

    Google Scholar 

  • Xueling G (2004) Study on the service function of vegetation ecosystem and its spatial characteristics in the Qinling Mountains. Northwestern University, Taiyuan

    Google Scholar 

  • Yi S, Mingguo M (2007) Analysis of vegetation cover changes in northwest China based on SPOT VEGETATION data. China Desert 27(1):89–93

    Google Scholar 

  • Yilun H, Guoxu J, Jihong L (2022) Interpretation of IPCC AR6 report: terrestrial and freshwater ecosystems and changes in their services. Adv Clim Chang Res 18(4):395–404

    Google Scholar 

  • Yiqi Y, Tiangui X (2021) Analysis of climate characteristics of Chengdu Plain Economic Zone. Highland Mount Meteorol Res 41(2):143–149

    Google Scholar 

  • Zhanfu L, Jin Z, Yating L et al (2020) Spatial and temporal evolution of urban greening level in China from 2000 to 2017 and its influencing factors. Geogr Arid Regions 43(2):481–490

    Google Scholar 

  • Zongxue X, Hao C, Meifang R et al (2020) Progress of urban flooding mechanism and risk assessment in China. Adv Water Sci 31(5):713–724

    Google Scholar 

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Authors and Affiliations

  1. College of Architecture and Environment, Sichuan University, Chengdu, 610065, China

    Peijuan Wu & Hong Fu

  2. School of Advavced Technology Xi’an Jiaotong-Liverpool University, Suzhou, 215000, China

    Zihan Jiang

Authors
  1. Peijuan Wu
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  2. Zihan Jiang
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  3. Hong Fu
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Corresponding author

Correspondence to Hong Fu .

Editor information

Editors and Affiliations

  1. School of Energy and Mining Engineering, China University of Mining and Technology(Beijing), Beijing, China

    Junwen Zhang

  2. University of Minnesota, St. Paul, MN, USA

    Roger Ruan

  3. University Tunku Abdul Rahman, Kampar, Malaysia

    Mohammed J. K. Bashir

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Wu, P., Jiang, Z., Fu, H. (2023). Vegetation Dynamic Monitoring and Driving Factors Analysis in Chengdu in Recent 20 Years Based on Google Earth Engine. In: Zhang, J., Ruan, R., Bashir, M.J.K. (eds) Environmental Pollution Governance and Ecological Remediation Technology. ICEPG 2022. Environmental Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-25284-6_5

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