Near real-time monitoring of global land-ocean cover dynamics
Lixing Wang, Tao Li, Xinyu Dou, Zhu Liu

TL;DR
This study presents an integrated near-real-time monitoring framework for global land and sea ice cover dynamics, revealing critical trends and safety thresholds relevant for climate policy and ecosystem management.
Contribution
It introduces a novel 5-day resolution global land-ocean cover dataset combining multi-source remote sensing and reanalysis data, with threshold analysis for climate safety assessment.
Findings
Forests cover 27% of global land, mainly in tropical regions.
Arctic sea ice occasionally drops below critical safety thresholds.
Temperature strongly negatively correlates with sea ice coverage (R = -0.78).
Abstract
Monitoring the dynamics of global land-ocean cover is fundamental for regulating the Earth's climate and sustaining terrestrial and marine ecosystems. However, existing datasets and research often exhibit limitations in temporal resolution and timeliness, lack coupled analysis of land cover and sea ice dynamics, and fail to incorporate the perspective of Earth system safety thresholds. Here, we developed an integrated monitoring framework by fusing multi-source remote sensing and reanalysis data, generating a 5-day resolution time series (2018-2025) of global land cover and sea ice coverage with near-real-time update capability. Our analysis reveals distinct latitudinal and regional patterns, with forests dominating (27.0% of global land area) tropical and subtropical regions. At the national scale, land cover composition and seasonal rhythms vary significantly, with countries like…
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