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Ecosystem Service Value Estimation of Paddy Field Ecosystems Based on Multi-Source Remote Sensing Data

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  • Tiecheng Huang

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China)

  • Wenjiang Huang

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Kun Wang

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China)

  • Yongkang Li

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
    School of Resources and Environmental Sciences, Xinjiang University, Urumqi 830046, China)

  • Zhenhai Li

    (Geomatics College, Shandong University of Science and Technology, Qingdao 266590, China)

  • Yong’an Yang

    (Tianjin High Quality Agricultural Products Development Demonstration Center, Tianjin 301500, China)

Abstract

A paddy field ecosystem (PFE) is an important component of an agricultural land ecosystem and is also a special artificial wetland with extremely high value. Taking Tianjin (a municipality city in China) as the research area and using multi-source remote sensing data, we improved the accounting framework of the ecosystem service value (ESV) of PFEs and the calibration of model parameters. The ESV of PFEs was mapped at medium-high resolution and fine-grain at the provincial scale. The results showed that: (1) the net ESV of PFEs in Tianjin in 2019 was RMB 29.68 × 10 8 , accounting for 0.21% of GDP. The positive ESV was RMB 35.53 × 10 8 , the negative ESV was RMB 5.84 × 10 8 , and the average ESV per unit area was RMB 5.47 × 10 4 /ha; (2) as a proportion of the ESV of PFE, the value of climate regulation (61.27%) was greater than the value of carbon fixation and oxygen release (15.29%), which was greater than the value of primary products supply (8.08%). The production value of PFEs is far lower than their ESV; (3) the total net ESV in Baodi District was RMB 16.85 × 10 8 , accounting for 56.77% of Tianjin’s ESV, and the net ESV per unit area was RMB 5.72 × 10 4 /ha, both of which were higher than in other districts; (4) the pixel-based hot spots analysis showed that the number of hot spots (high-value ESV) and cold spots (low-value ESV) reached 98.00% (hot spots 56.9%, cold spots 41.1%) with a significant cluster distribution. The hot spots were mostly distributed in Baodi District (37.8%) and the cold spots were mostly distributed in Ninghe District (17.2%). The research results can support agricultural development, improve countermeasures according to local conditions, and provide theoretical support for regional land use planning, ecological compensation policy formulation and ecological sustainable development. Our methodology can be used to assess the impact of land use change on ESV.

Suggested Citation

  • Tiecheng Huang & Wenjiang Huang & Kun Wang & Yongkang Li & Zhenhai Li & Yong’an Yang, 2022. "Ecosystem Service Value Estimation of Paddy Field Ecosystems Based on Multi-Source Remote Sensing Data," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9466-:d:878331
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    References listed on IDEAS

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