Skip to main content
Advanced Search

Filters: Tags: geographic information systems (GIS) (X)

49 results (144ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
(Hyperlink to Official Landing Page for Geospatial Fabric products) The Geospatial Fabric provides a consistent, documented, and topologically connected set of spatial features that create an abstracted stream/basin network of features useful for hydrologic modeling.The GIS vector features contained in this Geospatial Fabric (GF) data set cover the lower 48 U.S. states, Hawaii, and Puerto Rico. Four GIS feature classes are provided for each Region: 1) the Region outline ("one"), 2) Points of Interest ("POIs"), 3) a routing network ("nsegment"), and 4) Hydrologic Response Units ("nhru"). A graphic showing the boundaries for all Regions is provided at http://dx.doi.org/doi:10.5066/F7542KMD. These Regions are identical...
thumbnail
Groundwater-quality data collected between 1993 and 2015 were compiled from the U.S. Geological Survey (USGS) National Water Information System (NWIS) database for 722 wells in the San Joaquin Valley (SJV). Groundwater-quality data retrieved included lab analyses of complete major ion data (calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, alkalinity, bicarbonate, carbonate, silica, and TDS) for 613 samples, and an additional 109 samples with measured values of specific conductance. Most of these wells were sampled as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project or the USGS National Water Quality Assessment (NAWQA) Program. In addition...
This research examines the effects of climate change on the species composition of forests in the southern Great Lakes region in USA (Illinois, Indiana, and Ohio) by simultaneously addressing five key components necessary for realistic predictions of future forest composition. We simulated transient (1), species-level (2), forest response to climate change at a spatial scale that accounted for competitive effects (3), and regional site diversity (4), in the spatial configuration of forests within the regional landuse matrix (5). The JABOWA-II forest growth model was used to provide species-specific responses of 45 tree species to site conditions (e.g. climatic, edaphic) while accounting for competition for limited...
thumbnail
Predictions of raven occurrence in the absence of anthropogenic environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
thumbnail
This U.S. Geological Survey (USGS) metadata release consists of 17 different spatial layers in GeoTIFF format. They are: 1) average water capacity (AWC.zip), 2) percent sand (Sand.zip), 3) percent silt (Silt.zip), 4) percent clay (Clay.zip), 5) soil texture (TEXT_PRMS.zip), 6) land use/land cover (LULC.zip), 7) snow values (Snow.zip), 8) summer rain values (SRain.zip), 9) winter rain values (WRain.zip), 10) leaf presence values (keep.zip), 11) leaf loss values (loss.zip), 12) percent tree canopy (CNPY.zip), 13) percent impervious surface (Imperv.zip), 14) snow depletion curve numbers (Snow.zip), 15) rooting depth (RootDepth.zip), 16) permeability values (Lithology_exp_Konly_Project.zip), and 17) water bodies. All...
Growing concern about climate change and energy security has led to increasing interest in developing renewable, domestic energy sources for meeting electricity, heating and fuel needs in the United States. Illinois has significant potential to produce bioenergy crops, including corn, soybeans, miscanthus (Miscanthus giganteus), and switchgrass (Panicum virgatum). However, land requirements for bioenergy crops place them in competition with more traditional agricultural uses, in particular food production. Additionally, environmental and economic conditions, including soil quality, climate, and variable agricultural costs, vary significantly across Illinois. The intent of this study is to examine the spatial and...
thumbnail
This U.S. Geological Survey (USGS) Data Release represents geospatial and tabular data on irrigation water use in Kansas. The data release was produced in compliance with open data requirements. The dataset consists of 3 separate items with similar attributes aggregated to different geographic extents: 1. Kansas counties; 2. Kansas regional planning areas used in the Kansas Water Plan; and 3. Kansas irrigation water-use analysis regions. Reported 2014 water withdrawn for irrigation, acres irrigated, and application rates along with the published application rate statistics from the previous 4 years (2010–13) are shown with the 2014 statistics and are used to calculate a 5-year average. The 2014 annual total...
thumbnail
This U.S. Geological Survey (USGS) Data Release provides derivative statistics of water used by Kansas irrigators in the Kansas irrigation water-use analysis regions. The published application rate statistics from the previous 4 years (2010–13) are shown with the 2014 statistics and are used to calculate a 5-year average. The 2014 annual total precipitation and the current 30-year climatic normal (based on 1981–2010) are also shown by region. The amount of water used, irrigated acres, and application rates are further grouped by crop type. The amount of water used and irrigated acres are further grouped by irrigation method. Total reported irrigation water use in 2014 was 3.3 million acre-feet of water applied to...
thumbnail
(Hyperlink to Official Landing Page for Geospatial Fabric products) This dataset contains a set of attributes describing the "nhru" GIS features (Hydrologic Response Units)in the Geospatial Fabric Features dataset(http://dx.doi.org/doi:10.5066/F7542KMD) that have been developed in support of the USGS PRMS watershed model. These tables are organized according to Geospatial Fabric Region; see the thumbnail of the Geospatial Fabric Features Regions (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Each table contains a key field, "hru_id", that can be used to relate to the nhru feature class in the Geospatial Fabric Feature dataset for the corresponding Region. The methodologies used to derive the...
thumbnail
(Hyperlink to Official Landing Page for Geospatial Fabric products) This dataset contains a set of attributes describing the "nhru" GIS features (Hydrologic Response Units)in the Geospatial Fabric Features dataset(http://dx.doi.org/doi:10.5066/F7542KMD) that have been developed in support of the USGS PRMS watershed model. These tables are organized according to Geospatial Fabric Region; see the thumbnail of the Geospatial Fabric Features Regions (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Each table contains a key field, "hru_id", that can be used to relate to the nhru feature class in the Geospatial Fabric Feature dataset for the corresponding Region. The methodologies used to derive the...
thumbnail
A 1-m resolution, continuous surface, bathymetric digital elevation model (DEM) of the northern portion of San Francisco Bay, which includes San Pablo Bay, Carquinez Strait, and portions of Suisun Bay, was constructed from bathymetric surveys collected from 1999 to 2016. In 2014 and 2015 the California Ocean Protection Council (OPC) contracted the collection of bathymetric surveys of large portions of San Francisco Bay. A total of 93 surveys were collected using a combination of multibeam and interferometric side-scan sonar systems. Of those 93 surveys, 75 consist of swaths of data ranging from 18- to just over 100-meters wide. These swaths were separated by data gaps ranging from 10- to just over 300-meters wide....
thumbnail
Predictions of raven occurrence in the absence of natural environmental effects. Raven point counts were related to landscape covariates using Bayesian hierarchical occupancy models and the means of the posterior distributions for relevant effects were used to generate the predictions.
Rising global demand for energy, high energy prices, climate change, and the threat of terrorism all point to the need for greater energy efficiency and conservation in the United States. While technological innovation is plainly needed, our laws and institutional arrangements must also play an important role. The United States has scores of legal and policy tools from which to choose to improve energy efficiency and curb energy consumption. This Article, which grows out of a Spring 2006 seminar at theWidener University School of Law, evaluates a handful of these tools: transit-oriented development; fuel taxation; real-time pricing for electricity use; public benefit funds; improving the efficiency of existing residential...
thumbnail
(Hyperlink to Official Landing Page for Geospatial Fabric products) This dataset contains a set of attributes describing the "nhru" GIS features (Hydrologic Response Units)in the Geospatial Fabric Features dataset(http://dx.doi.org/doi:10.5066/F7542KMD) that have been developed in support of the USGS PRMS watershed model. These tables are organized according to Geospatial Fabric Region; see the thumbnail of the Geospatial Fabric Features Regions (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Each table contains a key field, "hru_id", that can be used to relate to the nhru feature class in the Geospatial Fabric Feature dataset for the corresponding Region. The methodologies used to derive the...


map background search result map search result map GIS Features of the Geospatial Fabric for National Hydrologic Modeling Geospatial Fabric Attribute Tables for PRMS Soils Parameters based on SSURGO (Preliminary) Geospatial Fabric Attribute Tables for PRMS Landcover Parameters based on NLCD2001 (Preliminary) Geospatial Fabric Attribute Tables for PRMS Topographic Parameters based on NHDPlus DEMs (Preliminary) Irrigation water use in Kansas, 2014 Reported 2014 water withdrawn for irrigation, acres irrigated, and application rates in Kansas irrigation water-use analysis regions (spatial and tabular data). Modern groundwater-quality, depth, and well-construction data for selected wells in the San Joaquin Valley, California, 1993-2015 Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (MLLW) Data Layers for the National Hydrologic Model, version 1.1 Digital elevation model (DEM) of northern San Francisco Bay, California, created using bathymetry data collected between 1999 and 2016 (MLLW) Modern groundwater-quality, depth, and well-construction data for selected wells in the San Joaquin Valley, California, 1993-2015 Irrigation water use in Kansas, 2014 Reported 2014 water withdrawn for irrigation, acres irrigated, and application rates in Kansas irrigation water-use analysis regions (spatial and tabular data). Raven study site locations in the Great Basin, derived from survey locations 2007 - 2016 Prediction of raven occurrence intersected with high impact areas for sage-grouse populations in the Great Basin, 2007-2016 (Fig. 5A) Predictions of raven occurrence in the absence of natural environmental effects in the Great Basin, 2007-2016 (Fig. 4A) Predictions of raven occurrence in the absence of anthropogenic environmental effects in the Great Basin, 2007-2016 (Fig. 4B) Data Layers for the National Hydrologic Model, version 1.1 GIS Features of the Geospatial Fabric for National Hydrologic Modeling Geospatial Fabric Attribute Tables for PRMS Soils Parameters based on SSURGO (Preliminary) Geospatial Fabric Attribute Tables for PRMS Landcover Parameters based on NLCD2001 (Preliminary) Geospatial Fabric Attribute Tables for PRMS Topographic Parameters based on NHDPlus DEMs (Preliminary)