Found 270 datasets matching "Predictor Data".
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This data release contains input data used in model development and TIF raster files used to predict the probability of low dissolved oxygen (DO) and high dissolved iron (Fe) in groundwater within...
Search relevance: 88.86 | Views last month: 1 -
Statewide maps of the probability of exceeding a given concentration of either uranium (U) or radon (Rn) in New Hampshire groundwater (represented as statewide rasters) are the product of...
Search relevance: 86.12 | Views last month: 0 -
This data release contains input data used in model development and TIF raster files used to predict the probability of high arsenic (As) and high manganese (Mn) in groundwater within the glacial...
Search relevance: 82.62 | Views last month: 0 -
Multi Order Hydrologic Position (MOHP) raster datasets: Distance from Stream to Divide (DSD) and Lateral Position (LP) have been produced nationally for the 48 contiguous United States at 30-meter...
Search relevance: 80.23 | Views last month: 0 -
Multi Order Hydrologic Position (MOHP) raster datasets: Distance from Stream to Divide (DSD) and Lateral Position (LP) have been produced nationally for the 48 contiguous United States at a...
Search relevance: 78.76 | Views last month: 0 -
Data includes information collected during the 2007 NLA Survey. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.
Search relevance: 75.30 | Views last month: 0 -
This data release includes three types of data used in habitat modeling, and predictions from the habitat models. (1) Predictor rasters for proportion urban development within 1-km radius,...
Search relevance: 54.06 | Views last month: 0 -
The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for Mount Rainier National Park. The vegetation map is a...
Search relevance: 48.66 | Views last month: 0 -
The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for Olympic National Park. The vegetation map is a geotiff...
Search relevance: 48.17 | Views last month: 0 -
The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for Olympic National Park. The vegetation map is a...
Search relevance: 46.08 | Views last month: 6 -
Please review Zhang et al. (2021) for details on study design and datasets (https://doi.org/10.1016/j.watres.2022.118443). In summary, predictor and response variable data was acquired from the...
Search relevance: 38.81 | Views last month: 0 -
We developed a second iteration of habitat suitability models for Lesser Prairie Chicken leks, across their range. The first modeling iteration used lek data collected from 2002 to 2012, land...
Search relevance: 36.46 | Views last month: 0 -
This data release contains data used to develop models and maps that estimate the occurrence of lithium in groundwater used as drinking water throughout the conterminous United States. An extreme...
Search relevance: 36.08 | Views last month: 9 -
This dataset contains global monthly climatology of oceanic total alkalinity (AT). Total alkalinity (AT) monthly climatology was created from a neural network approach (Broullón et al., 2019). The...
Search relevance: 35.61 | Views last month: 1 -
This dataset contains global monthly climatology of oceanic total alkalinity (AT). Total alkalinity (AT) monthly climatology was created from a neural network approach (Broullón et al., 2019). The...
Search relevance: 35.24 | Views last month: 0 -
This dataset contains global monthly climatology of oceanic total dissolved inorganic carbon (DIC). (DIC) monthly climatology was created from a neural network approach (Broullón et al., 2020)....
Search relevance: 34.62 | Views last month: 0 -
An extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate in shallow groundwater across the conterminous United States (CONUS). Nitrate was...
Search relevance: 34.12 | Views last month: 0 -
A three-dimensional extreme gradient boosting (XGB) machine learning model was developed to predict the distribution of nitrate in groundwater across the conterminous United States (CONUS)....
Search relevance: 33.84 | Views last month: 0 -
* This research used public drinking water nitrate violations data from across the conterminous United States as response variables, and various predictor variables from EPA's StreamCat dataset...
Search relevance: 33.79 | Views last month: 2 -
Learn about the techniques used to create weights for the 2022 National Survey on Drug Use and Health (NSDUH) at the person level. The report reviews the generalized exponential model (GEM) used...
Search relevance: 33.60 | Views last month: 0
