Spatiotemporal Assessment of Desertification Sensitivity in Ningxia, China, Using the MEDALUS Framework and Random Forest Classification (2001–2022)

Munaza Nawaz; Wilson Kalisa; Zakria Zaheen; Moughal Tauqir; Jiahua Zhang; Adnan Abbas Shah; Kalim Ullah

doi:10.62762/JGEO.2025.205415

Article Information

Published in Journal of Geoscience and Earth Observation

Volume/Issue Volume 1, Issue 1, 2026

Pages 39-54

Abstract

In semi-arid regions, desertification is a critical environmental degradation factor. This study analyzes land degradation and desertification vulnerability dynamics in Ningxia, China (2001–2022) using the MEDALUS framework with a Random Forest classifier. Land-cover change was significant due to irrigation and agricultural expansion, with farmland increasing to 65.29% of the landscape while grassland shrank to 10.13%, intensifying ecological pressure. Bare land followed a U-shaped trend, reaching 9.17% in 2022, indicating increased soil exposure. Soil quality remained moderately stable, with 70–80% of land retaining integrity despite ongoing degradation. Vegetation quality fluctuated considerably, as poor vegetation quality decreased from 42.42% in 2001 to 36.6% in 2022, with scattered local recovery. Management quality improved due to irrigation modernization and policy implementation, while long-term aridity moderately constrained climatic conditions. The Desertification Sensitivity Index (DSI) varied over time: low-desertification areas accounted for 44.47% in 2001, while high-desertification areas comprised 29.06%. By 2011, conservation efforts increased stable areas to 48.26%. However, in 2022, high-desertification areas persisted across 9,552.49 km², primarily in northern and central regions characterized by poor soil and uneven rainfall. This research provides robust scientific evidence to inform land management, vegetation rehabilitation, and climate adaptation strategies in vulnerable drylands.

Graphical Abstract

Spatiotemporal Assessment of Desertification Sensitivity in Ningxia, China, Using the MEDALUS Framework and Random Forest Classification (2001–2022)

Keywords

desertification MEDALUS random forest Ningxia land degradation remote sensing dryland ecosystems google earth engine (GEE)

Data Availability Statement

Data will be made available on request.

Funding

This work was supported by the Natural Science Foundation of Shandong Province under Grant ZR2023QD073, Grant ZR2024QD156, and Grant ZR2020GF067, and by the Central Guiding Local Science and Technology Development Fund of Shandong under Grant YDZX2023019.

Conflicts of Interest

The authors declare no conflicts of interest.

AI Use Statement

The authors declare that no generative AI was used in the preparation of this manuscript.

Ethical Approval and Consent to Participate

Not applicable.

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APA Style

Nawaz, M., Kalisa, W., Zaheen, Z., Tauqir, M., Zhang, J., Shah, A. A., & Ullah, K. (2026). Spatiotemporal Assessment of Desertification Sensitivity in Ningxia, China, Using the MEDALUS Framework and Random Forest Classification (2001–2022). Journal of Geoscience and Earth Observation, 1(1), 39–54. https://doi.org/10.62762/JGEO.2025.205415

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TY  - JOUR
AU  - Nawaz, Munaza
AU  - Kalisa, Wilson
AU  - Zaheen, Zakria
AU  - Tauqir, Moughal
AU  - Zhang, Jiahua
AU  - Shah, Adnan Abbas
AU  - Ullah, Kalim
PY  - 2026
DA  - 2026/04/16
TI  - Spatiotemporal Assessment of Desertification Sensitivity in Ningxia, China, Using the MEDALUS Framework and Random Forest Classification (2001–2022)
JO  - Journal of Geoscience and Earth Observation
T2  - Journal of Geoscience and Earth Observation
JF  - Journal of Geoscience and Earth Observation
VL  - 1
IS  - 1
SP  - 39
EP  - 54
DO  - 10.62762/JGEO.2025.205415
UR  - https://www.icck.org/article/abs/JGEO.2025.205415
KW  - desertification
KW  - MEDALUS
KW  - random forest
KW  - Ningxia
KW  - land degradation
KW  - remote sensing
KW  - dryland ecosystems
KW  - google earth engine (GEE)
AB  - In semi-arid regions, desertification is a critical environmental degradation factor. This study analyzes land degradation and desertification vulnerability dynamics in Ningxia, China (2001–2022) using the MEDALUS framework with a Random Forest classifier. Land-cover change was significant due to irrigation and agricultural expansion, with farmland increasing to 65.29% of the landscape while grassland shrank to 10.13%, intensifying ecological pressure. Bare land followed a U-shaped trend, reaching 9.17% in 2022, indicating increased soil exposure. Soil quality remained moderately stable, with 70–80% of land retaining integrity despite ongoing degradation. Vegetation quality fluctuated considerably, as poor vegetation quality decreased from 42.42% in 2001 to 36.6% in 2022, with scattered local recovery. Management quality improved due to irrigation modernization and policy implementation, while long-term aridity moderately constrained climatic conditions. The Desertification Sensitivity Index (DSI) varied over time: low-desertification areas accounted for 44.47% in 2001, while high-desertification areas comprised 29.06%. By 2011, conservation efforts increased stable areas to 48.26%. However, in 2022, high-desertification areas persisted across 9,552.49 km², primarily in northern and central regions characterized by poor soil and uneven rainfall. This research provides robust scientific evidence to inform land management, vegetation rehabilitation, and climate adaptation strategies in vulnerable drylands.
SN  - pending
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -

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@article{Nawaz2026Spatiotemp,
  author = {Munaza Nawaz and Wilson Kalisa and Zakria Zaheen and Moughal Tauqir and Jiahua Zhang and Adnan Abbas Shah and Kalim Ullah},
  title = {Spatiotemporal Assessment of Desertification Sensitivity in Ningxia, China, Using the MEDALUS Framework and Random Forest Classification (2001–2022)},
  journal = {Journal of Geoscience and Earth Observation},
  year = {2026},
  volume = {1},
  number = {1},
  pages = {39-54},
  doi = {10.62762/JGEO.2025.205415},
  url = {https://www.icck.org/article/abs/JGEO.2025.205415},
  abstract = {In semi-arid regions, desertification is a critical environmental degradation factor. This study analyzes land degradation and desertification vulnerability dynamics in Ningxia, China (2001–2022) using the MEDALUS framework with a Random Forest classifier. Land-cover change was significant due to irrigation and agricultural expansion, with farmland increasing to 65.29\% of the landscape while grassland shrank to 10.13\%, intensifying ecological pressure. Bare land followed a U-shaped trend, reaching 9.17\% in 2022, indicating increased soil exposure. Soil quality remained moderately stable, with 70–80\% of land retaining integrity despite ongoing degradation. Vegetation quality fluctuated considerably, as poor vegetation quality decreased from 42.42\% in 2001 to 36.6\% in 2022, with scattered local recovery. Management quality improved due to irrigation modernization and policy implementation, while long-term aridity moderately constrained climatic conditions. The Desertification Sensitivity Index (DSI) varied over time: low-desertification areas accounted for 44.47\% in 2001, while high-desertification areas comprised 29.06\%. By 2011, conservation efforts increased stable areas to 48.26\%. However, in 2022, high-desertification areas persisted across 9,552.49 km², primarily in northern and central regions characterized by poor soil and uneven rainfall. This research provides robust scientific evidence to inform land management, vegetation rehabilitation, and climate adaptation strategies in vulnerable drylands.},
  keywords = {desertification, MEDALUS, random forest, Ningxia, land degradation, remote sensing, dryland ecosystems, google earth engine (GEE)},
  issn = {pending},
  publisher = {Institute of Central Computation and Knowledge}
}

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