Harnessing Technology for Conservation: The Role of AI, Big Data, and GIS in Biodiversity Protection

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About this Research Topic

Submission deadlines

  1. Manuscript Submission Deadline 30 April 2026

  2. This Research Topic is currently accepting articles.

Background

The application of technology in the field of conservation has seen remarkable growth over recent years. With significant advancements in artificial intelligence (AI), big data, machine learning, remote sensing (RS), and geographic information systems (GIS), conservation efforts are undergoing transformative changes. These technologies enhance the ability to monitor ecosystems, predict environmental changes, and address threats such as poaching, illegal logging, and habitat degradation. By integrating data from various sources like satellite imagery, drones, and camera traps, conservationists can make well-informed decisions that lead to more effective biodiversity protection. Despite these innovations, challenges remain in fully optimizing the synergies between these technologies due to data accuracy issues, accessibility hurdles, and the need for specialized expertise.

This Research Topic aims to explore the integration of AI, big data, machine learning, remote sensing, and GIS in strengthening conservation efforts. It seeks to understand how these technologies can be used for predictive modeling of wildlife populations, assessment of ecosystem health, and detection of illegal activities such as poaching. Furthermore, the research will investigate how real-time monitoring systems provide actionable insights for immediate conservation actions. The objective is not only to uncover the potential benefits of these technologies but also to identify the challenges and limitations hindering their full application, such as issues related to data handling and the necessity for trained personnel.
To gather further insights in the application of technology in conservation, we welcome articles addressing, but not limited to, the following themes:

- Predictive modeling using AI and machine learning for wildlife and ecosystem monitoring
- The role of remote sensing and GIS in tracking large-scale environmental changes
- Real-time monitoring of illegal activities with satellite data and drones
- Challenges in data accuracy and the implementation of technology in conservation
- Impacts of innovative technologies on biodiversity protection strategies

Article types and fees

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

  • Brief Research Report
  • Community Case Study
  • Data Report
  • Editorial
  • FAIR² Data
  • FAIR² DATA Direct Submission
  • General Commentary
  • Hypothesis and Theory
  • Methods

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

Keywords: Innovative technology; artificial intelligence, big data, machine learning, remote sensing

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.

Topic editors

Manuscripts can be submitted to this Research Topic via the main journal or any other participating journal.

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