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Integrating Remote Sensing, IoT, and AI for Biodiversity Monitoring in Hainan Tropical Rainforest National Park

Author

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  • Maozheng Fu

    (Hainan Vocational University of Science and Technology, China)

  • Zhangzhong Huang

    (Hainan Vocational University of Science and Technology, China)

Abstract

The rapid rise of ecotourism has intensified the challenge of balancing development with ecological protection, especially in tropical rainforests. Conventional monitoring is constrained by low efficiency, delayed updates, and limited coverage. This study, using Hainan Tropical Rainforest National Park as a pilot, develops a collaborative “air-space-ground” dynamic monitoring system that integrates high-resolution satellite remote sensing, IoT sensor clusters, and deep learning–based recognition. The system enables real-time monitoring of biodiversity distribution, environmental parameters, and human activity impacts, while addressing spatiotemporal and data integration limits. Results show that multi-source data fusion reduces errors, with the NDVI error dropping to 0.02±0.005, and effectively detects vegetation degradation hotspots. Beyond technical advances, the system offers precise tools for ecological management and demonstrates a feasible pathway for aligning conservation with sustainable ecotourism.

Suggested Citation

  • Maozheng Fu & Zhangzhong Huang, 2025. "Integrating Remote Sensing, IoT, and AI for Biodiversity Monitoring in Hainan Tropical Rainforest National Park," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global Scientific Publishing, vol. 16(1), pages 1-18, January.
    • Handle: RePEc:igg:jaeis0:v:16:y:2025:i:1:p:1-18
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