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Spatiotemporal trends and the change detection of the yearly eco-environmental quality in the Yellow River Basin, China

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Abstract

As a critical ecological security and economic corridor in China, monitoring the ecological quality of the Yellow River Basin (YRB) is essential for China’s ecological protection and sustainable economic development. In this study, we constructed a modified Remote Sensing Ecological Index (MRSEI) to investigate the spatiotemporal dynamics of ecological quality in the YRB from 2001 to 2023. Meanwhile, we incorporated the Aridity Index (AI) and the temperature (T). Furthermore, Multiple Linear Regression and Random Forest models were employed to quantify the contributions of moisture (NDMI), urbanization (NDBI), and productivity (NPP) to ecological variance. Finally, land cover type conversion was employed to interpret ecological variations detected by the MRSEI dynamic ratio. The primary results are as follows: (1) Ecological quality in the middle reaches of the YRB significantly improved from 2001 to 2010, remaining relatively stable from 2011 to 2023. (2) No significant correlation was observed between temperature (T) and MRSEI, but significant correlations between Aridity Index (AI) and MRSEI were observed during 2001–2010 in the Windbreak and Sand Fixation Functional Zone (WSFZ, r2001−2010=0.520 ± 0.225, p < 0.01) and Soil Conservation Functional Zone (SCFZ, r2001−2010=0.467 ± 0.350, p < 0.01). (3) The dominant land cover conversion types include barred land-to-cropland conversion (3640.44 km2) and cropland/barren land-to-grassland conversion (3212.19 km2; 1507.25 km2) in regions where ecological conditions improved from 2001 to 2023. (4) Form 2001–2023, NDMI (Surface Moisture), contributes 52%-56% to ecological dynamics, while the water cycle budget exerts a governing influence on basin-wide ecological quality. This study offers critical insights for promoting ecological protection and sustainable development in the functional zones of the YRB.

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Data availability

Ye, H., and Li, X. (2025). Dataset of the yearly Eco-Environmental Quality in the Yellow River Basin [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.16872271 .

References

  1. Men, D. & Pan, J. Incorporating network topology and ecosystem services into the optimization of ecological network: A case study of the Yellow River Basin. Sci. Total Environ. 912, 169004 (2024).

    Google Scholar 

  2. Li, C. et al. Comprehensive evaluation of the high-quality development of the ecological and economic belt along the Yellow River in Ningxia. Sustainability 15 (15), 11486 (2023).

    Google Scholar 

  3. Zhang, B. et al. Construction of watershed ecological security patterns with integrated of spatial variability: A case study of the Yellow River Basin, China. Ecol. Ind. 159, 111663 (2024).

    Google Scholar 

  4. Feng, L. et al. Effects of mosaic biological soil crusts on vascular plant establishment in a coastal saline land of the Yellow River Delta, China. J. Plant Ecol. 14(5), 781–792 (2021).

  5. Guo, S. et al. Threshold effect of ecosystem services in response to climate change, human activity and landscape pattern in the upper and middle Yellow River of China. Ecol. Ind. 136, 108603 (2022).

    Google Scholar 

  6. Cui, Q., Xia, J., Yang, H., Liu, J. & Shao, P. Biochar and effective microorganisms promote Sesbania cannabina growth and soil quality in the coastal saline-alkali soil of the Yellow River Delta, China. Sci. Total Environ. 756, 143801 (2021).

  7. Wu, H., Shi, P., Qu, S., Zhang, H. & Ye, T. Establishment of watershed ecological water requirements framework: A case study of the Lower Yellow River, China. Sci. Total Environ. 820, 153205 (2022).

    Google Scholar 

  8. Wang, S. et al. Identification and optimization of ecological corridors in the middle reaches of the Yellow River Basin. J. Clean. Prod. 145676. (2025).

  9. Ying, X. et al. Combining AHP with GIS in synthetic evaluation of eco-environment quality-A case study of Hunan Province, China. Ecol. Model. 209 (2–4), 97–109 (2007).

    Google Scholar 

  10. Romero-Calcerrada, R. & Luque, S. Habitat quality assessment using Weights-of-Evidence based GIS modelling: The case of Picoides tridactylus as species indicator of the biodiversity value of the Finnish forest. Ecol. Model. 196 (1–2), 62–76 (2006).

    Google Scholar 

  11. Yu, S. et al. Measurement of land ecological security in the middle and lower reaches of the Yangtze River Base on the PSR Model. Sustainability 15 (19), 14098 (2023).

    Google Scholar 

  12. Ge, J. et al. IRSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin. Sci. Rep. 14 (1), 14506 (2024).

    Google Scholar 

  13. Yan, Z., Zhou, Z., Liu, J., Wang, H. & Li, D. Water use characteristics and impact factors in the Yellow River basin, China. Water Int. 45 (3), 148–168 (2020).

    Google Scholar 

  14. Wang, Y., Kong, X., Guo, K., Zhao, C. & Zhao, J. Spatiotemporal change in vegetation cover in the Yellow River Basin between 2000 and 2022 and driving forces analysis. Front. Ecol. Evol. 11, 1261210 (2023).

    Google Scholar 

  15. Ren, Z., Tian, Z., Wei, H., Liu, Y. & Yu, Y. Spatiotemporal evolution and driving mechanisms of vegetation in the Yellow River Basin, China during 2000–2020. Ecol. Ind. 138, 108832 (2022).

    Google Scholar 

  16. Wiegand, T., Naves, J., Garbulsky, M. F. & Fernández, N. Animal habitat quality and ecosystem functioning: exploring seasonal patterns using NDVI. Ecol. Monogr. 78 (1), 87–103 (2008).

    Google Scholar 

  17. Xu, H., Wang, Y., Guan, H., Shi, T. & Hu, X. Detecting ecological changes with a remote sensing based ecological index (RSEI) produced time series and change vector analysis. Remote Sens. 11 (20), 2345 (2019).

    Google Scholar 

  18. Xu, H. Q. A remote sensing urban ecological index and its application. Acta Ecol. Sin. 33 (24), 7853–7862 (2010).

    Google Scholar 

  19. Geng, J. et al. Analysis of spatiotemporal variation and drivers of ecological quality in Fuzhou based on RSEI. Remote Sens. 14 (19), 4900 (2022).

    Google Scholar 

  20. Zhou, J. & Liu, W. Monitoring and evaluation of eco-environment quality based on remote sensing-based ecological index (RSEI) in Taihu Lake Basin, China. Sustainability 14 (9), 5642 (2022).

    Google Scholar 

  21. Zheng, Z., Wu, Z., Chen, Y., Guo, C. & Marinello, F. Instability of remote sensing based ecological index (RSEI) and its improvement for time series analysis. Sci. Total Environ. 814, 152595 (2022).

    Google Scholar 

  22. Liu, Y., Xiang, W., Hu, P., Gao, P. & Zhang, A. Evaluation of ecological environment quality using an improved remote sensing ecological index model. Remote Sens. 16 (18), 3485 (2024).

    Google Scholar 

  23. Wang, J., Jiang, L., Qi, Q. & Wang, Y. An ecological quality evaluation of large-scale farms based on an improved remote sensing ecological index. Remote Sens. 16 (4), 684 (2024).

    Google Scholar 

  24. Chen, N., Cheng, G., Yang, J., Ding, H. & He, S. Evaluation of urban ecological environment quality based on improved RSEI and driving factors analysis. Sustainability 15 (11), 8464 (2023).

    Google Scholar 

  25. Xu, C. et al. Effects of land use/cover change on carbon storage between 2000 and 2040 in the Yellow River Basin, China. Ecol. Ind. 151, 110345 (2023).

    Google Scholar 

  26. Wang, Y., Song, J., Li, Q. & Jiang, X. Exploration of the development of water-energy-food nexus and its endogenous and exogenous drivers in the Yellow River Basin, China. J. Environ. Manage. 378, 124735 (2025).

    Google Scholar 

  27. Yang, H. et al. Effects of different Tamarix chinensis-grass patterns on the soil quality of coastal saline soil in the Yellow River Delta, China. Sci. Total Environ. 772, 145501 (2021).

  28. Du, L., Dong, C., Kang, X., Qian, X. & Gu, L. Spatiotemporal evolution of land cover changes and landscape ecological risk assessment in the Yellow River Basin, 2015–2020. J. Environ. Manage. 332, 117149 (2023).

    Google Scholar 

  29. Zhao, J. et al. Carbon emission prediction model and analysis in the Yellow River basin based on a machine learning method. Sustainability 14 (10), 6153 (2022).

    Google Scholar 

  30. Peng, S. 1-km monthly precipitation dataset for China (1901–2022) (Beijing, China, 2020).

  31. Peng, S. 1-km monthly potential evapotranspiration dataset for China (1901–2023) National Tibetan (Plateau/Third Pole Environment Data Center [data set], 2022).

  32. Yang, J. & Huang, X. 30 m annual land cover and its dynamics in China from 1990 to 2019. Earth Syst. Sci. Data Discuss. 1–29. (2021).

  33. Zhang, Y. et al. Assessment of coastal ecological restoration effectiveness using an improved remote sensing ecological index: a case study of the Liaohe Estuary. Front. Ecol. Evol. 13, 1603614 (2025).

    Google Scholar 

  34. Sahin, S. An aridity index defined by precipitation and specific humidity. J. Hydrol. 444, 199–208 (2012).

    Google Scholar 

  35. Bolker, B. M. et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24 (3), 127–135 (2009).

    Google Scholar 

  36. Strobl, C., Malley, J. & Tutz, G. An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychol. Methods. 14 (4), 323–348 (2009).

    Google Scholar 

  37. Yang, W., Zhou, Y. & Li, C. Assessment of ecological environment quality in rare earth mining areas based on improved RSEI. Sustainability 15 (4), 2964 (2023).

    Google Scholar 

  38. Wen, C., Long, T., He, G., Jiao, W. & Jiang, W. Temporally enhanced RSEI and nighttime lights reveal long-term ecological changes and effective protection in China’s inaugural national parks. Ecol. Ind. 170, 112981 (2025).

    Google Scholar 

  39. Wu, Z. et al. Satellite-based large-scale vegetation dynamics in ecological restoration programs of Northern China[J]. Int. J. Remote Sens. 40 (5–6), 2296–2312 (2019).

    Google Scholar 

  40. Yin, R. S., Yin, G. P. & Li, L. Y. Assessing China’s Ecological Restoration Programs: What’s Been Done and What Remains to Be Done? [J]. Environ. Manage. 45 (3), 442–453 (2010).

    Google Scholar 

  41. Niu, Q. F. et al. Ecological engineering projects increased vegetation cover, production, and biomass in semiarid and subhumid Northern China Vol. 30, 1620–1631 (Land Degradation & Development[J], 2019). 13.

  42. Qiao, X. et al. Spatiotemporal Changes in Vegetation Cover during the Growing Season and Its Implications for Chinese Grain for Green Program in the Luo River Basin[J]. Forests 15 (9), 1649–1649 (2024).

    Google Scholar 

  43. Cao, S. X., Chen, L. & Yu, X. X. Impact of China’s Grain for Green Project on the landscape of vulnerable arid and semi-arid agricultural regions: a case study in northern Shaanxi Province[J]. J. Appl. Ecol. 46 (3), 536–543 (2009).

    Google Scholar 

  44. Fan, M. & Xiao, Y. T. Impacts of the grain for Green Program on the spatial pattern of land uses and ecosystem services in mountainous settlements in southwest China[J] 21 (Global Ecology and Conservation, 2020).

  45. Kennedy, R. E., Yang, Z. Q. & Cohen, W. B. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr—A new algorithm[J]. Remote Sens. Environ. 114 (12), 2897–2910 (2010).

    Google Scholar 

  46. Wang, Y. et al. Coupling and Coordination Analysis of Land Use Function and Ecological Quality in Yellow River Basin, Henan Province, China. Sustainability 16 (23), 10699 (2024).

    Google Scholar 

  47. Yu, G. et al. Impact of land use/land cover change on ecological quality during urbanization in the lower Yellow River Basin: A case study of Jinan City. Remote Sens. 14 (24), 6273 (2022).

    Google Scholar 

  48. Ma, D., Huang, Q., Liu, B. & Zhang, Q. Analysis and dynamic evaluation of Eco-environmental Quality in the Yellow River Delta from 2000 to 2020. Sustainability 15 (10), 7835 (2023).

    Google Scholar 

  49. Yang, Z. et al. Analysis of ecological environmental quality change in the Yellow River Basin using the remote-sensing-based ecological index. Sustainability 14 (17), 10726 (2022).

    Google Scholar 

  50. Zhang, X., Wang, G., Xue, B., Wang, Y. & Wang, L. Spatiotemporal variation of evapotranspiration on different land use/cover in the inner Mongolia reach of the Yellow River Basin. Remote Sens. 14 (18), 4499 (2022).

    Google Scholar 

  51. Zhang, X., Wang, G. & Xue, B. Changes in vegetation cover and its influencing factors in the inner Mongolia reach of the yellow river basin from 2001 to 2018. Environ. Res. 215, 114253 (2022).

    Google Scholar 

  52. Shen, Z. & Gong, J. Spatial–Temporal Changes and Driving Mechanisms of Ecological Environmental Quality in the Qinghai–Tibet Plateau, China. Land 13 (12), 2203 (2024).

    Google Scholar 

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Funding

This work was supported by the National Key R&D Program of China (NO.2022YFF1303203), the National Natural Science Foundation of China (NO. 32271963).

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Authors and Affiliations

  1. Shandong Key Laboratory of Eco-Environmental Science for the Yellow River Delta, Shandong University of Aeronautics, Binzhou, 256603, China

    Hui Ye, Jiangbao Xia, Xiao Wang, Shuo Li, Qiqi Cao, Haidong Xu & Xiaodong Li

  2. Institute of Restoration Ecology, School of Chemical and Environmental Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China

    Xiao Wang

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  1. Hui Ye
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  3. Xiao Wang
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  4. Shuo Li
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  6. Haidong Xu
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  7. Xiaodong Li
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Contributions

Hui Ye: conceptualization; methodology; validation; formal analysis; writing—original draft preparation. Jiangbao Xia: review and supervision; funding acquisition. Xiao Wang: methodology; validation; formal analysis. Shuo Li: writing—original draft preparation. Qiqi Cao: conceptualization; writing—review and editing. Haidong Xu: writing—original draft preparation; writing—review and editing. Xiaodong Li: conceptualization; writing—review and editing; supervision; funding acquisition.

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Jiangbao Xia or Xiaodong Li.

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Ye, H., Xia, J., Wang, X. et al. Spatiotemporal trends and the change detection of the yearly eco-environmental quality in the Yellow River Basin, China.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-48716-8

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  • DOI: https://doi.org/10.1038/s41598-026-48716-8

Keywords

  • Yellow River Basin (YRB)
  • functional zones
  • the change detection
  • the yearly Eco-Environmental Quality
  • land cover type conversion

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