Computationally e cient geostatistical simulation for uncertainty propagation in models with spatially distributed parameters
Uncertainty is endemic in geospatial data due to the imperfect means of recording, processing, and representing spatial information. Propagating geospatial model inputs inherent uncertainty to uncertainty in model predictions is a critical requirement in each model's impact assessment and risk-...
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| Language: | English |
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2021
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| Online Access: | http://hdl.handle.net/11610/21413 |
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