in

Spatio-temporal land-use dynamics and landscape ecological risk assessment in an artificial oasis, Northwestern China


Abstract

Understanding long-term land-use changes and their ecological consequences is essential for managing fragile artificial oasis systems in arid regions. This study analyzes annual land-use/land-cover (LULC) dynamics in the Alar Reclamation Area (northwestern China) from 1990 to 2019 using multi-temporal Landsat imagery, maximum NDVI composites, and a supervised SVM classifier. We produced annual LULC maps, quantified area changes and transition matrices, computed landscape pattern metrics (e.g., patch density, edge density), detected abrupt change points, and evaluated ecological risk using a landscape disturbance–vulnerability framework. Socioeconomic and climatic drivers (population, agricultural production value, cotton price, temperature and precipitation) were integrated to explain observed transformations and used in CA–Markov scenario simulations. Key findings: (1) cultivated land, orchards and construction land expanded substantially (net increases of 1147.2 km², 674.2 km² and 36.5 km², respectively), largely at the expense of unused land and natural vegetation; (2) a structural turning point occurred around 2005, associated with policy and market drivers; (3) landscape fragmentation increased, and ecological risk concentrated in reclamation belts adjacent to the Tarim River; (4) scenario simulations show that high-intensity development would markedly raise ecological risk, whereas conservation-oriented management can mitigate risk. The study identifies trade-offs between agricultural development and ecosystem stability, highlights salt-crust degradation and increased erosion as key ecological concerns, and provides spatially explicit evidence to inform land-use planning. Limitations include reliance on medium-resolution imagery and limited in-situ measurements; we therefore recommend future integration of higher-resolution imagery and process-based erosion monitoring.

Similar content being viewed by others

Spatio-temporal evolution and multi-scenario simulation of land use landscape pattern in northern Guangxi

Analysis study on the change of orchard area in Alar reclamation in the past 30 years

Analysis of cultivated land changes and driving factors in the Alar Reclamation Area (1990–2019) based on multi-temporal Landsat data and machine learning algorithms

Data availability

The datasets used or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Huang, J. & Wang, Y. Ventilation potential simulation based on multiple scenarios of land-use changes catering for urban planning goals in the metropolitan area. Journal Clean. production (Dec 10) 483, 144301 (2024).

    Google Scholar 

  2. Joloro, H., Tilaki, G. A. D., Memarian, H. & Kooch, Y. Spatial–temporal assessment of land use changes and forest restoration on carbon sequestration using the invest model in central alborz, iran. Modeling Earth Syst. Environment https://doi.org/10.1007/s40808-025-02452-6 (2025).

    Google Scholar 

  3. Sajida, N., Yang, C., Ahsan, W. A. & Wang, Z. Integrating land use changes, biomass dynamics, and water quality for wetland restoration: a case study of Chaohu lake Shibalianwei wetland, China. J. Geoscience Environ. Prot. 13 (4), 27 (2025).

    Google Scholar 

  4. Fu, M., Jiao, L. & Su, J. Urban land system change: Spatial heterogeneity and driving factors of land use intensity in wuhan, China. Habitat Int. 159 (2025).

  5. Ning, J., Li, P., He, X., Ren, X. & Li, F. Impacts of land use changes on the spatiotemporal evolution of groundwater quality in the yinchuan area, china, based on long-term monitoring data. Phys. Chem. Earth 136, 103722 (2024).

    Google Scholar 

  6. Duran-Bautista, E. H., Yalanda-Sepulveda, K., Martínez-Trivio, K. & Gamboa, J. Land-use changes impact responses of termite functional and taxonomic diversity in the colombian amazon. Biotropica https://doi.org/10.1111/btp.13366 (2024).

    Google Scholar 

  7. Fu, Y. et al. Distinct assembly patterns of soil antibiotic resistome revealed by land-use changes over 30 years. Environ. Sci. Technol. 58 (23), 11 (2024).

    Google Scholar 

  8. Bai, Y., Zhou, Y. & Feng, Q. Land use change and climatic-topographic factors drive Spatial heterogeneity of soil pH in karst watersheds of Southwest China. Catena 26, 1109540–1109540 (2025).

    Google Scholar 

  9. Kabisch, N., Selsam, P., Kirsten, T., Lausch, A. & Bumberger, J. A multi-sensor and multi-temporal remote sensing approach to detect land cover change dynamics in heterogeneous urban landscapes. Ecol. Ind. 99, 273–282 (2019).

    Google Scholar 

  10. Shen, S., Yue, P. & Fan, C. Quantitative assessment of land use dynamic variation using remote sensing data and landscape pattern in the Yangtze river delta, China. Sustainable Comput. 23 (Sep.), 111–119 (2019).

    Google Scholar 

  11. Ge, L. et al. Uncovering interactive impacts of climate extremes and land use change on soil erosion using a coupled RUSLE-OPGD framework. Catena 261, 109507–109507 (2025).

    Google Scholar 

  12. Zhao, L. et al. Land use/cover changes in the oriental migratory locust area of china: implications for ecological control and monitoring of locust area. Agriculture Ecosyst. & Environment 303, 107110 (2020).

    Google Scholar 

  13. Yao, R. et al. A novel grid-based technique for quantifying groundwater quality under land use/land cover changes to support improved groundwater management. J. Hydrol. 662 (PC), 133955–133955 (2025).

    Google Scholar 

  14. Wang, X. et al. Linking land use change, ecosystem services and human well-being: a case study of the Manas river basin of xinjiang, China. Ecosyst. Serv. 27, 113–123 (2017).

    Google Scholar 

  15. Pinto, B. R. et al. Changes in land use and buffaloes trampling effects on soil health in environmentally vulnerable areas of an Atlantic forest biome in Southern São Paulo State, Brazil. Geoderma Reg. 43, e01011–e01011 (2025).

    Google Scholar 

  16. Bi, Y. et al. The response of non-point source pollution to land use changes based on the SWAT and PLUS models in an agricultural river basin of Yangtze River, China. J. Hydrol. 663 (PB), 134331–134331 (2025).

    Google Scholar 

  17. Matsa, M., Mupepi, O., Musasa, T. & Defe, R. A gis and remote sensing aided assessment of land use/cover changes in resettlement areas; a case of ward 32 of mazowe district, zimbabwe. J. Environ. Management 276, 111312 (2020).

    Google Scholar 

  18. Zhou, J. et al. Transitions in slope runoff generation mechanisms induced by land use change in the Loess Plateau, China. Catena 261, 109517–261109517 (2025).

    Google Scholar 

  19. MAASHI, M. Forecasting land use changes in crop classification and drought using remote sensing. J. Arid Land. 17 (05), 575–589 (2025).

    Google Scholar 

  20. Changnon, S. A. & Demissie, M. Detection of changes in streamflow and floods resulting from climate fluctuations and land use-drainage changes. Clim. Change. 32 (4), 411–421 (1996).

    Google Scholar 

  21. Romero, H., Ihl, M., Rivera, A., Zalazar, P. & Azocar, P. Rapid urban growth, land-use changes and air pollution in santiago, Chile. Atmos. Environ. 33 (24–25), 4039–4047 (1999).

    Google Scholar 

  22. Wang, R. et al. A flood susceptibility prediction method for climate change scenarios driven by coupled land simulation and Spatiotemporal dual Convolution synergy. J. Hydrol. 664 (PA), 134366–134366 (2026).

    Google Scholar 

  23. Zhang, H., Zhou, Q., Yang, J. & Xiang, H. Change and driving factors of eco-environmental quality in Beijing green belts: from the perspective of nature-based solutions. Ecol. Ind. 166 (000), 12 (2024).

    Google Scholar 

  24. Gang, S., Kong, X., Jia, T., Lv, M. & Li, L. Analysis of the Spatiotemporal evolution and driving factors of land use change in Jinan springs area of the Northern karst region, China from 1986 to 2022. Discover Appl. Sci. 7 (4), 1–22 (2025).

    Google Scholar 

  25. Hu, B. et al. Driving factors of rural land-use change from a multi-scale perspective: a case study of the loess plateau in china. Land (2012). 14(3) (2025).

Download references

Funding

This study was supported by Scientific Research Project of Xichang University, titled “Land Use Change and Ecological Risk Assessment in Northwestern China Based on Remote Sensing Technology,” and the Project of Xichang University (No. LGLZ202301).

Author information

Authors and Affiliations

Authors

Contributions

**Qi Song: ** Writing—original draft and Writing—review & editing. **Lina Li: ** Conceptualization and Methodology.

Corresponding author

Correspondence to
Lina Li.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Song, Q., Li, L. Spatio-temporal land-use dynamics and landscape ecological risk assessment in an artificial oasis, Northwestern China.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-32741-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41598-025-32741-0

Keywords

  • Land use change
  • Arid region
  • Long time series
  • Driving factors


Source: Ecology - nature.com

Unraveling effects of environmental factors on arsenic accumulation in rice under field conditions using a Bayesian state space model

Urbanization accelerates soil degradation in peri-urban compared to rural farms

Back to Top