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Journal of Climate, ISSN 0894-8755, 3/2013, Volume 26, Issue 6, pp. 2137 - 2143
Quantile mapping is routinely applied to correct biases of regional climate model simulations compared to observational data. If the observations are of... 
Statistical variance | Simulations | Precipitation | Determinism | Winter | Rain gauges | Time series | Summer | Climate models | Modeling | VARIABILITY | METEOROLOGY & ATMOSPHERIC SCIENCES | TRENDS | Studies | Boundary conditions | General circulation models | Noise | Bias | Quantiles | Inflation | Mapping | Regional
Journal Article
Journal of Climate, ISSN 0894-8755, 9/2015, Volume 28, Issue 17, pp. 6938 - 6959
Quantile mapping bias correction algorithms are commonly used to correct systematic distributional biases in precipitation outputs from climate models.... 
Climate change | Simulations | Precipitation | Quantiles | Historical periods | Climate models | Data models | Correctional system | Calibration | Modeling | Trends | Statistical techniques | Bias | Extreme events | ENSEMBLE | SCENARIOS | DOWNSCALING EXTREMES | CLIMATE-CHANGE IMPACTS | CMIP5 | TEMPERATURE | MODELS | RAINFALL | METEOROLOGY & ATMOSPHERIC SCIENCES | UTILITY | INDEXES | Algorithms | Meteorology
Journal Article
Journal of Geochemical Exploration, ISSN 0375-6742, 08/2016, Volume 167, pp. 49 - 61
Geochemical maps provide invaluable evidence to guide decisions on issues of mineral exploration, agriculture, and environmental health. However, the high cost... 
South west England | Uncertainty | Modelling | Random forest | Quantile regression | Soil geochemistry | LAND-COVER CLASSIFICATION | REGRESSION | GEOCHEMISTRY & GEOPHYSICS | RANDOM FORESTS | SOUTHWEST ENGLAND | Mineral industry | Mining industry | Machine learning | High resolution | Quantiles | Forests | Accuracy | Maps | Geochemistry | Regression | Mathematical models
Journal Article
PLoS ONE, ISSN 1932-6203, 01/2012, Volume 7, Issue 1, p. e28922
Journal Article
Geoderma, ISSN 0016-7061, 04/2017, Volume 291, pp. 55 - 64
Digital Soil Mapping (DSM) products are simplified representations of more complex and partially unknown patterns of soil variations. Therefore, any prediction... 
Quantile regression forest | Regional scale | Digital soil mapping | Uncertainties | GlobalSoilMap | SOIL SCIENCE | CONTINUOUS DEPTH FUNCTIONS | SPATIAL PREDICTION | Usage | Mobile communication systems | Wireless communication systems | GSM (Global System for Mobile Communications) | Life Sciences
Journal Article
PARASITES & VECTORS, ISSN 1756-3305, 09/2019, Volume 12, Issue 1, pp. 1 - 13
Journal Article
Environmental Research Letters, ISSN 1748-9326, 2013, Volume 8, Issue 3, pp. 1 - 9
Journal Article
International Journal of Climatology, ISSN 0899-8418, 03/2018, Volume 38, Issue 4, pp. 1623 - 1633
Journal Article
International Journal of Climatology, ISSN 0899-8418, 06/2019, Volume 39, Issue 7, pp. 3160 - 3170
Journal Article
Remote Sensing of Environment, ISSN 0034-4257, 2006, Volume 102, Issue 3, pp. 364 - 376
Journal Article
Geoderma, ISSN 0016-7061, 03/2017, Volume 290, pp. 91 - 99
In this paper a spatial downscaling method is explored for generating appropriate farm scale digital soil maps. The digital soil map product to be downscaled... 
Quantile regression forest | Uncertainty | Digital soil mapping | Soil carbon auditing | Spatial downscaling | Soil carbon | AUSTRALIA | NEW-ZEALAND | SEQUESTRATION | FORESTS | SOIL SCIENCE | ORGANIC-CARBON | STOCKS | MAP | REGIONAL CLIMATE MODELS | Soils | Carbon content | Agriculture
Journal Article