Aljaddani (2026) Integrated Remote Sensing and Time Series Analysis for Long-Term Assessment of Vegetation Resilience: Synthesizing Climatic Variables and Land-Use/Land-Cover Trajectories in Al-Ahsa Oasis, Saudi Arabia

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Land
• Year: 2026
• Date: 2026-09-20
• Authors: Amal H. Aljaddani
• DOI: 10.3390/land15091758

Research Groups

• King Abdullah University of Science and Technology (KAUST)
• [Other research groups or institutions involved]

Short Summary

This study integrates vegetation, climate, and land-use frameworks to investigate the long-term dynamics of land-use/land-cover change in the Al-Ahsa Oasis over 41 years. The findings provide insights into vegetation resilience and support sustainable urban planning.

Objective

• Investigate the relationships between vegetation indicators and climatic variables at different time lags in the Al-Ahsa Oasis

Study Configuration

• Spatial Scale: Regional (Al-Ahsa Oasis, Saudi Arabia)
• Temporal Scale: 41-year period (1985–2025)

Methodology and Data

• Models used: Random forest classifier for LULC trajectory classification
• Data sources:
  • Satellite data from Landsat 5-TM, 7-ETM+, and 8-OLI sensors
  • ERA5-Land reanalysis for surface temperature
  • CHIRPS dataset for rainfall information

Main Results

• No statistically significant associations between vegetation indicators (NDVI and SAVI) and climatic variables (temperature and rainfall) across the four examined lags after detrending the time series.
• Positive associations in original, non-detrended time series mainly attributable to long-term trends rather than interannual climate–vegetation covariation.
• High accuracy of LULC trajectory classification with an overall accuracy of 0.939 and a kappa coefficient of 0.924.

Contributions

This study provides the first comprehensive analysis of vegetation resilience in the Al-Ahsa Oasis over 41 years, supporting sustainable urban planning and vegetation management.

Funding

• [List projects, programs, and reference codes that funded this research]
• This information is not provided in the original text.

Citation

@article{Aljaddani2026Integrated,
  author = {Aljaddani, Amal H.},
  title = {Integrated Remote Sensing and Time Series Analysis for Long-Term Assessment of Vegetation Resilience: Synthesizing Climatic Variables and Land-Use/Land-Cover Trajectories in Al-Ahsa Oasis, Saudi Arabia},
  journal = {Land},
  year = {2026},
  doi = {10.3390/land15091758},
  url = {https://doi.org/10.3390/land15091758}
}