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The Grids Python Tool for Querying Spatiotemporal Multidimensional Water Data
2021
Water
Scientific datasets from global-scale earth science models and remote sensing instruments are becoming available at greater spatial and temporal resolutions with shorter lag times. Water data are frequently stored as multidimensional arrays, also called gridded or raster data, and span two or three spatial dimensions, the time dimension, and other dimensions which vary by the specific dataset. Water engineers and scientists need these data as inputs for models and generate data in these formats
doi:10.3390/w13152066
fatcat:ybtdzano5rbz5hspkwan6xjfz4