Ecological restoration evaluation of afforestation in Gudao Oilfield based on multi-source remote sensing data

被引:3
|
作者
Li, Xiuneng [1 ,2 ]
Li, Yongtao [3 ,4 ]
Wang, Hong [5 ]
Qin, Shuhong [1 ]
Wang, Xin [5 ]
Yang, Han [5 ]
Cornelis, Wim [2 ]
机构
[1] Hohai Univ, Sch Earth Sci & Engn, Nanjing 211100, Peoples R China
[2] Univ Ghent, Dept Environm, B-9000 Ghent, Belgium
[3] Shandong Acad Forestry Sci, Jinan 250014, Peoples R China
[4] Natl Observat & Res Stn Chinese Forest Ecosyst Yel, Dongying 257000, Peoples R China
[5] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
基金
中国国家自然科学基金;
关键词
Ecological evaluation; Oilfield ecological restoration; Forest management; RSEI; CHINA; WATER; TEMPERATURE; INDEX; VEGETATION; DIVERSITY; INCREASES; DELTA; SOIL;
D O I
10.1016/j.ecoleng.2023.107107
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The growing petroleum industry poses significant ecological challenges, prompting an increased focus on ecological restoration projects in onshore oilfields. Current efforts focus on revegetation in deforested oilfields, while research remains limited on alternative ecological restoration strategies aimed at establishing new eco-systems in oilfields. This study employed multi-source remote sensing data from 1985 to 2022 to calculate a remote sensing-based ecological index (RSEI) and constructed an integrated forest health index (IFHI), in order to evaluate the ecological restoration effects in the Gudao shelterbelt of Shengli Oilfield in the Yellow River Delta, and investigated the impact of oil extraction by considering forest phenology. The RSEI of the shelterbelt showed an upward trend and reached a Good level of ecological environment quality from 1990 to 2003, but it declined after that, indicating the potential of RSEI to quickly assess ecological restoration effects and guide management at different stages. Comparing the restoration effects of different tree species, a Robinia pseudoacacia L. (RP) and Fraxinus velutina Torr. (FV) mixed forest demonstrated the greatest capacity to improve environ-mental quality, with the most years (25 years) of the Good and Excellent levels and the highest IFHI value (1.52). In contrast, Ulmus pumila L. (UP) and Sophora japonica L. (SJ) were unsuitable for mixed planting for ecological restoration. The study also found that monospecific RP forests within 30 m of oil wells were significantly impacted by oil extraction (P <= 0.05), necessitating tailored forest management. The research aims to serve as a reference for ecological restoration in global onshore oil production areas, particularly in delta regions and sparsely vegetated areas.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] River Ecological Protection and Restoration Using Multi-source Remote Sensing Data
    Zhang, Xiangyong
    MOBILE NETWORKS & APPLICATIONS, 2023, 28 (06): : 2118 - 2129
  • [2] Dynamical monitoring of ecological environment quality of land consolidation based on multi-source remote sensing data
    Shan W.
    Jin X.
    Meng X.
    Yang X.
    Xu Z.
    Gu Z.
    Zhou Y.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2019, 35 (01): : 234 - 242
  • [3] Monitoring and Effect Evaluation of an Ecological Restoration Project Using Multi-Source Remote Sensing: A Case Study of Wuliangsuhai Watershed in China
    Jia, Xiang
    Jin, Zhengxu
    Mei, Xiaoli
    Wang, Dong
    Zhu, Ruoning
    Zhang, Xiaoxia
    Huang, Zherui
    Li, Caixia
    Zhang, Xiaoli
    LAND, 2023, 12 (02)
  • [4] MONITORING VEGETATION RESTORATION AFTER WILDFIRES IN TYPICAL BOREAL FORESTS BASED ON MULTI-SOURCE REMOTE SENSING DATA
    Jiang, Bohan
    Chen, Wei
    Wu, Yu
    Gao, Zhanping
    IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024, 2024, : 581 - 584
  • [5] A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data
    Zheng, Xiao
    Zhu, Jiaojun
    THEORETICAL AND APPLIED CLIMATOLOGY, 2017, 127 (1-2) : 465 - 480
  • [6] A new climatic classification of afforestation in Three-North regions of China with multi-source remote sensing data
    Xiao Zheng
    Jiaojun Zhu
    Theoretical and Applied Climatology, 2017, 127 : 465 - 480
  • [7] Study on Ecological Services Evaluation of Water Conservation using Multi-source Remote Sensing Products
    Wang, Y. L.
    Wu, L.
    Guo, Z. W.
    Huang, Y. B.
    INTERNATIONAL CONFERENCE ON ENVIRONMENTAL REMOTE SENSING AND BIG DATA (ERSBD 2021), 2021, 12129
  • [8] Summer maize LAI retrieval based on multi-source remote sensing data
    Pan, Fangjiang
    Guo, Jinkai
    Miao, Jianchi
    Xu, Haiyu
    Tian, Bingquan
    Gong, Daocai
    Zhao, Jing
    Lan, Yubin
    INTERNATIONAL JOURNAL OF AGRICULTURAL AND BIOLOGICAL ENGINEERING, 2023, 16 (02) : 179 - 186
  • [9] Multi-source remote sensing data fusion based on wavelet transformation algorithm
    Ding, JL
    Zhu, Q
    Zhang, Y
    Tiyip, T
    Liu, CS
    Sun, R
    Pan, XL
    ECOSYSTEMS DYNAMICS, ECOSYSTEM-SOCIETY INTERACTIONS, AND REMOTE SENSING APPLICATIONS FOR SEMI-ARID AND ARID LAND, PTS 1 AND 2, 2003, 4890 : 262 - 269
  • [10] Green Tide Information Extraction Based on Multi-source Remote Sensing Data
    Liang, Tingting
    Ke, Lina
    Fan, Jianchao
    Zhao, Jianhua
    2020 12TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2020, : 460 - 465