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        desc: "Abstract. Rock glaciers are key periglacial landforms in high mountain systems, serving as indicators of permafrost, contributors to mountain hydrology, and sentinels of climate change. Despite their scientific and practical importance, detailed knowledge of their distribution, characteristics, and ...",
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        desc: "Abstract. Solar-induced chlorophyll fluorescence (SIF) is a crucial proxy of photosynthetic processes in vegetation. In recent decades, advancements in remote sensing technology have facilitated long-term global SIF monitoring, significantly enhancing our understanding of vegetation dynamics on a ...",
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        desc: "Abstract. Identifying buried channels in 3D seismic volumes is essential for characterizing hydrocarbon reservoirs and offering insights into paleoclimate conditions, yet it remains a labor-intensive and time-consuming task. The data-driven deep learning methods are highly promising to automate the ...",
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        desc: "Abstract. Accurate quantification of the geospatial distribution of livestock in pastoral regions is important for assessing and maintaining grassland ecological security and sustainable development. Statistical livestock data based on static and macro-level administrative units cannot characterize ...",
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        desc: "Abstract. Satellite-derived solar-induced chlorophyll fluorescence (SIF) offers valuable opportunities for monitoring large-scale ecosystem functions. However, the inherent trade-off between satellite scan range and spatial resolution, along with incomplete spatial coverage and irregular temporal ...",
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        desc: "Abstract. The air-sea CO2 flux in the coastal ocean is a key component of the global carbon budget. However, due to the scarcity of data, the many sources and sinks of carbon and their complex interactions in these waters remain poorly understood. In 2021, the Tara schooner collected 14,000 km of ...",
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        desc: "Abstract. Accurate monitoring of crop yield is important for ensuring food security. However, exiting yield datasets with a coarse spatial resolution are inadequate for capturing small scale spatial heterogeneity. Current yield estimation methods, such as machine learning models or the assimilation ...",
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