Results 241 to 250 of about 1,045,155 (298)
Efficient large-scale land cover change detection using Google Earth Engine: Climate-driven vegetation dynamics in Asian drylands (2001-2022). [PDF]
Wu J, Wei S, Hao H, Chen M, Ismail S.
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Impact of Erbium and Gadolinium on <i>Xenopus laevis</i> Embryo Development: A Study of Rare Earth Element Toxicity. [PDF]
Fogliano C +10 more
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Economic valuation of farmland using natural-attribute-based indicators: A case study of Hefei, China. [PDF]
Yuan L, Fan X, Feng B.
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Mapping digital popularity: Analyzing the network attention patterns of national forest parks based on Douyin (Tiktok) data. [PDF]
Zhang S, Gu Q.
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Experimental study on the disintegration characteristics of rare earth tailings improved by BF-MICP. [PDF]
Guo Z, Cao X, Wu J, Zhong Y, Liu Q.
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Data assimilation methods in the Earth sciences
Advances in Water Resources, 2008Abstract Although remote sensing data are often plentiful, they do not usually satisfy the users’ needs directly. Data assimilation is required to extract information about geophysical fields of interest from the remote sensing observations and to make the data more accessible to users. Remote sensing may provide, for example, measurements of surface
Rolf H Reichle
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Optical methods in Earth Sciences
Optics and Lasers in Engineering, 2002Mankind progress was started by systematic observations of Earth and celestial rhythms. As soon as the technology of the first modern optical instruments became available, they were applied to astronomical and geodetical measurements. Modern science itself originates from the Copernican revolution based on new observations and interpretation of Earth ...
De Natale G +3 more
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Earth-Science Reviews, 2021
Abstract Spatiotemporal forecasting (STF) extends traditional time series forecasting or spatial interpolation problem to space and time dimensions. Here, we review the statistical, physical and artificial intelligence (AI) methods, data and model uncertainties, predictability and future directions for STF problems.
Lei Xu +4 more
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Abstract Spatiotemporal forecasting (STF) extends traditional time series forecasting or spatial interpolation problem to space and time dimensions. Here, we review the statistical, physical and artificial intelligence (AI) methods, data and model uncertainties, predictability and future directions for STF problems.
Lei Xu +4 more
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