XU Dong, BAI Tingting, CHEN Wei-Qiang, SONG Yongze, ZHOU Yuyu, GENG Jing, ZHAO Liu, 2025. Toward an Intelligent and Near-real-time Framework for Global Ecological Monitoring: Advances, Challenges, and the GIEHP Initiative. Chinese Geographical Science, 35(6): 1217−1239. DOI: 10.1007/s11769-025-1567-5
Citation: XU Dong, BAI Tingting, CHEN Wei-Qiang, SONG Yongze, ZHOU Yuyu, GENG Jing, ZHAO Liu, 2025. Toward an Intelligent and Near-real-time Framework for Global Ecological Monitoring: Advances, Challenges, and the GIEHP Initiative. Chinese Geographical Science, 35(6): 1217−1239. DOI: 10.1007/s11769-025-1567-5

Toward an Intelligent and Near-real-time Framework for Global Ecological Monitoring: Advances, Challenges, and the GIEHP Initiative

  • Global ecological monitoring faces unprecedented challenges from accelerating climate change, biodiversity loss, urban expansion, and unsustainable resource use. Although existing scientific programs and monitoring platforms have improved data accessibility and methodological standards, they remain constrained by three critical bottlenecks: near-real-time performance, intelligent analysis, and comprehensive coverage. Overcoming these shortcomings is essential to advance global change science, climate governance, and sustainable development. This review synthesized recent progress in international ecological monitoring, including major scientific initiatives, thematic and integrated monitoring platforms, and emerging remote sensing cloud systems. These systems have collectively promoted open data sharing, standardized observation protocols, and cross-domain integration. However, critical challenges remain in achieving near-real-time observation, interpretable intelligent modeling, and globally balanced coverage, which limit the transition toward an intelligent and fully consistent monitoring framework. Building on this foundation, we introduce the Global Intelligent Ecological Horizon Project (GIEHP), an exploratory framework aimed at constructing the world’s first Digital Earth Atlas with long-term consistency and high-dimensional integration. GIEHP represents a pathway toward integrating multi-source observations, intelligent modeling, and cloud-cluster computation to achieve near-real-time, multi-scale, and globally consistent monitoring. Its pilot applications illustrate the potential for unified mapping of key ecological indicators and provide a methodological reference for advancing intelligent, data-driven environmental governance. This review not only summarized the progress and limitations of existing monitoring systems but also outlines a forward-looking framework for the next generation of global ecological monitoring. Achieving a truly intelligent, near-real-time, and globally consistent system requires sustained international collaboration, interdisciplinary integration, and open data sharing. We call on the global scientific community to advance this vision and provide robust knowledge support for ecological restoration, climate adaptation, and sustainable development.
  • loading

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return