Spatial Dynamics and Ecosystem Services in Diverse Forest Landscapes: Integrating AI and Geospatial Techniques

The study of forest ecosystems, encompassing natural, protected, and urban environments, has gained increasing significance due to their critical role in maintaining biodiversity, supporting ecosystem services, and mitigating climate change impacts. Current research rapidly evolves through geospatial analysis, geovisualization, and artificial intelligence (AI), helping identify spatial dynamics and changes in forested areas. Despite progress, significant knowledge gaps remain, particularly in understanding land-use transitions, ecosystem service provision, and their interactions with urbanization and climate variability. Contemporary studies reveal the potential of integrating advanced Geographic Information Systems (GIS) with remote sensing data to facilitate a detailed assessment of forest dynamics.

This Research Topic aims to employ cutting-edge AI tools, including machine learning algorithms and deep neural networks, to enhance the detection, classification, and prediction of forest changes. The objective is to assess and model forest dynamics over time, focusing on ecosystem service hotspots, forest fragmentation, and degradation patterns. By leveraging AI-driven models, this research will provide automated solutions for high-resolution mapping of diverse forest types and dynamics, offering valuable insights into the impacts of environmental pressures.

To gather further insights into forest ecosystems, we focus on the integration of spatial modeling and AI technologies. The initial scope highlights forest dynamics' monitoring boundaries and limitations: natural, protected, and urban settings. We welcome articles addressing, but not limited to, the following themes:

- AI-enhanced 3D geovisualization for scenario analysis and stakeholder engagement

- Advanced GIS techniques and remote sensing for forest change detection

- Mapping ecosystem service flows and hotspots

- AI models for forest fragmentation and degradation analysis

- Predicting forest dynamics under different land-use and policy regimes

Appendix: Articles can include original research, reviews, and case studies focusing on methodological advancements, practical applications, and cross-disciplinary approaches.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: Forest dynamics, Spatial modelling, GIS and cartography, Geovisualization, Sustainable forest management

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.