Zheng et al. (2025) GeoAI for Land Use Observations, Analysis, and Forecasting

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

Identification

• Journal: Land
• Year: 2025
• Date: 2025-10-15
• Authors: Wenfeng Zheng, Kenan Li, Xuan Liu
• DOI: 10.3390/land14102058

Research Groups

Not available in the provided text snippet.

Short Summary

This paper explores how Geographic Artificial Intelligence (GeoAI) is fundamentally transforming the observation, understanding, and governance of land systems.

Objective

• To analyze and demonstrate the transformative impact of Geographic Artificial Intelligence (GeoAI) on the methods and capabilities for observing, understanding, and governing land systems.

Study Configuration

• Spatial Scale: Land systems (broad geographical scope); specific scale (e.g., regional, national, global) not detailed in the provided text snippet.
• Temporal Scale: Not specified in the provided text snippet.

Methodology and Data

• Models used: Geographic artificial intelligence (GeoAI) approaches are central, but specific models (e.g., deep learning architectures, specific GIS algorithms) are not detailed in the provided text snippet.
• Data sources: Not specified in the provided text snippet.

Main Results

Not available in the provided text snippet, as the provided text is an introductory sentence.

Contributions

Not available in the provided text snippet, as the provided text is an introductory sentence.

Funding

Not available in the provided text snippet.

Citation

@article{Zheng2025GeoAI,
  author = {Zheng, Wenfeng and Li, Kenan and Liu, Xuan},
  title = {GeoAI for Land Use Observations, Analysis, and Forecasting},
  journal = {Land},
  year = {2025},
  doi = {10.3390/land14102058},
  url = {https://doi.org/10.3390/land14102058}
}