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Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7_5_Min,
Combined Vector,
Combined Vector,
Combined Vector,
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Types: Citation;
Tags: 7.5 x 7.5 minute,
7_5_Min,
Combined Vector,
Combined Vector,
Combined Vector,
USGS National Boundary Dataset (NBD) in Wisconsin State or Territory (published 20240215) GeoPackage
Geospatial data is comprised of government boundaries.
Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface-water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface-water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface-water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine...
The U.S. Army Corps of Engineers' Upper Mississippi River Restoration (UMRR) program, through its Long Term Resource Monitoring (LTRM) element, collected aerial imagery of the systemic Upper Mississippi River System (UMRS) during the summer of 2020. A Land Cover/Land Use (LCU) spatial database was developed based on the 2020 aerial imagery, which adds a fourth systemic-wide database to the existing 1989, 2000, and 2010/11 LCU databases. While a crosswalk was used to update the 1989 LCU database (originally developed using a different classification system), the 2000, 2010/11, and 2020 LCU databases share the same classification, making them directly comparable from a classification standpoint. Furthermore, protocols...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Iowa,
USGS-EMA-LOW-MR Landscape Ecology,
USGS-EMA-LOW-PL Mississippi River,
Wisconsin,
aquatic vegetation,
The Watershed Boundary Dataset (WBD) is a comprehensive aggregated collection of hydrologic unit data consistent with the national criteria for delineation and resolution. It defines the areal extent of surface water drainage to a point except in coastal or lake front areas where there could be multiple outlets as stated by the "Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD)" "Standard" (https://pubs.usgs.gov/tm/11/a3/). Watershed boundaries are determined solely upon science-based hydrologic principles, not favoring any administrative boundaries or special projects, nor particular program or agency. This dataset represents the hydrologic unit boundaries to the 12-digit (6th level)...
The U.S. Geological Survey constructed a steady-state numerical groundwater flow model in cooperation with Des Moines Water Works (DMWW) to simulate groundwater flow conditions in the Des Moines River alluvial aquifer (DMRA) during winter low-flow conditions typical of December 2018-2020. The Des Moines River alluvial aquifer (DMRA) is an important source of water for Des Moines Water Works (DMWW), the municipal water utility that serves residential and commercial water needs in the city of Des Moines, Iowa and surrounding municipalities. A comprehensive understanding of groundwater flow processes in the DMRA is needed for DMWW to make decisions related to the management of this water resource. A three-layered model...
The Geographic Names Information System (GNIS) is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types.
This data represents the map extent for current and historical USGS topographic maps for the United States and Territories, including 1 X 2 Degree, 1 X 1 Degree, 30 X 60 Minute, 15 X 15 Minute, 7.5 X 7.5 Minute, and 3.75 X 3.75 Minute. The grid was generated using ESRI ArcInfo GIS software.
Layers of geospatial data include contours, boundaries, land cover, hydrography, roads, transportation, geographic names, structures, and other selected map features.
Wildlife species face threats from climate and land use change, which may exacerbate how extreme climatic events influence population persistence and biodiversity. Migratory waterbirds are especially vulnerable to hydrological drought via reduced availability of surface water habitats. We assessed how whooping cranes, an endangered species in the U.S. and Canada, modified habitat use and migration strategies during drought to understand this species’ resilience to changing conditions and adaptive capacity. The data included 8,555 night-roost sites used by 145 cranes, 2010–2022, under non-drought conditions, moderate drought, and extreme drought conditions.
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
This child item describes Python code used to query census data from the TigerWeb Representational State Transfer (REST) services and the U.S. Census Bureau Application Programming Interface (API). These data were needed as input feature variables for a machine learning model to predict public supply water use for the conterminous United States. Census data were retrieved for public-supply water service areas, but the census data collector could be used to retrieve data for other areas of interest. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Data retrieved by the census data collector code were used as input...
This map layer shows major ports in the United States, Puerto Rico, and the U.S. Virgin Islands. A port is a city, town, or urban area with a harbor where ships load or unload. This is a revised version of the July 2012 map layer.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Academics & scientific researchers,
Alabama,
Arizona,
Arkansas,
California,
This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their...
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Academics & scientific researchers,
Alabama,
Alabama,
Alaska,
Arizona,
Layered geospatial PDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features. This map is derived from GIS (geospatial information system) data. It represents a repackaging of GIS data in traditional map form, not creation of new information. The geospatial data in this map are from selected National Map data holdings and other government sources.
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