Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This layer contains pre-processed address points for Sacramento County, California, which can be added to OpenStreetMap. This data was shared by the County as open data through the Esri Community Maps program and its new option for data sharing.This layer contains 662,634 address points for the County, with complete address info (e.g. housenumber, street, city, state, ZIP code) for each point. The processed address points referenced above were created using these Esri Data Processing Steps for Buildings and Addresses, developed and refined while doing data prep for several city and county communities in the United States.OSM Editor ToolsThis layer is accessible through new tools in OSM editors (e.g. updated version of RapiD) that enable OSM mappers to display the features on a map, select an individual feature to inspect its geometry and tags, and then use the feature for editing. OSM mappers should review the individual features and tags, and make any edits and additions that are appropriate, before selecting other features to edit and uploading edits to OSM.
This data release provides remotely sensed data, field measurements, and MATLAB code associated with an effort to produce image-derived velocity maps for a reach of the Sacramento River in California's Central Valley. Data collection occurred from September 16-19, 2024, and involved cooperators from the Intelligent Robotics Group from the National Aeronautics and Space Administration (NASA) Ames Research Center and the National Oceanographic and Atmospheric Administration (NOAA) Southwest Fisheries Science Center. The remotely sensed data were obtained from an Uncrewed Aircraft System (UAS) and are stored in Robot Operating System (ROS) .bag files. Within these files, the various data types are organized into ROS topics including: images from a thermal camera, measurements of the distance from the UAS down to the water surface made with a laser range finder, and position and orientation data recorded by a Global Navigation Satellite System (GNSS) receiver and Inertial Measurement Unit (IMU) during the UAS flights. This instrument suite is part of an experimental payload called the River Observing System (RiOS) designed for measuring streamflow and further detail is provided in the metadata file associated with this data release. For the September 2024 test flights, the RiOS payload was deployed from a DJI Matrice M600 Pro hexacopter hovering approximately 270 m above the river. At this altitude, the thermal images have a pixel size of approximately 0.38 m but are not geo-referenced. Two types of ROS .bag files are provided in separate zip folders. The first, Baguettes.zip, contains "baguettes" that include 15-second subsets of data with a reduced sampling rate for the GNSS and IMU. The second, FullBags.zip, contains the full set of ROS topics recorded by RiOS but have been subset to include only the time ranges during which the UAS was hovering in place over one of 11 cross sections along the reach. The start times are included in the .bag file names as portable operating system interface (posix) time stamps. To view the data within ROS .bag files, the Foxglove Studio program linked below is freely available and provides a convenient interface. Note that to view the thermal images, the contrast will need to be adjusted to minimum and maximum values around 12,000 to 15,000, though some further refinement of these values might be necessary to enhance the display. To enable geo-referencing of the thermal images in a post-processing mode, another M600 hexacopter equipped with a standard visible camera was deployed along the river to acquire images from which an orthophoto was produced: 20240916_SacramentoRiver_Ortho_5cm.tif. This orthophoto has a spatial resolution of 0.05 m and is in the Universal Transverse Mercator (UTM) coordinate system, Zone 10. To assess the accuracy of the orthophoto, 21 circular aluminum ground control targets visible in both thermal and RGB (red, green, blue) images were placed in the field and their locations surveyed with a Real-Time Kinematic (RTK) GNSS receiver. The coordinates of these control points are provided in the file SacGCPs20240916.csv. Please see the metadata for additional information on the camera, the orthophoto production process, and the RTK GNSS survey. The thermal images were used as input to Particle Image Velocimetry (PIV) algorithms to infer surface flow velocities throughout the reach. To assess the accuracy of the resulting image-derived velocity estimates, field measurements of flow velocity were obtained using a SonTek M9 acoustic Doppler current profiler (ADCP). These data were acquired along a series of 11 cross sections oriented perpendicular to the primary downstream flow direction and spaced approximately 150 m apart. At each cross section, the boat from which the ADCP was deployed made four passes across the channel and the resulting data was then aggregated into mean cross sections using the Velocity Mapping Toolbox (VMT) referenced below (Parsons et al., 2013). The VMT output was further processed as described in the metadata and ultimately led to a single comma delimited text file, SacAdcp20240918.csv, with cross section numbers, spatial coordinates (UTM Zone 10N), cross-stream distances, velocity vector components, and water depths. To assess the sensitivity of thermal image velocimetry to environmental conditions, air and water temperatures were recorded using a pair of Onset HOBO U20 pressure transducer data loggers set to record pressure and temperature. Deploying one data logger in the air and one in the water also provided information on variations in water level during the test flights. The resulting temperature and water level time series are provided in the file HoboDataSummary.csv with a one-minute sampling interval. These data sets were used to develop and test a new framework for mapping flow velocities in river channels in approximately real time using images from an UAS as they are acquired. Prototype code for implementing this approach was developed in MATLAB and is also included in the data release as a zip folder called VelocityMappingCode.zip. Further information on the individual functions (*.m files) included within this folder is available in the metadata file associated with this data release. The code is provided as is and is intended for research purposes only. Users are advised to thoroughly read the metadata file associated with this data release to understand the appropriate use and limitations of the data and code provided herein.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This is the official Street Centerline dataset for the County of Sacramento and the incorporated cities within. The Street Range Index table is a distinct list of street names within the Centerline dataset along with the existing address range for each street by zip code.The Street Name Index table is a distinct list of street names within the Centerline dataset.
https://www.icpsr.umich.edu/web/ICPSR/studies/2913/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/2913/terms
The 1998 Dress Rehearsal was conducted as a prelude to the United States Census of Population and Housing, 2000, in the following locations: (1) Columbia, South Carolina, and surrounding areas, including the town of Irmo and the counties of Chester, Chesterfield, Darlington, Fairfield, Kershaw, Lancaster, Lee, Marlboro, Newberry, Richland, and Union, (2) Sacramento, California, and (3) Menominee County, Wisconsin, including the Menominee American Indian Reservation. This collection contains map files showing various levels of geography (in the form of Census Tract Outline Maps, Voting District/State Legislative District Outline Maps, and County Block Maps), TIGER/Line digital files, and Corner Point files for the Census 2000 Dress Rehearsal sites. The Corner Point data files contain the bounding latitude and longitude coordinates for each individual map sheet of the 1998 Dress Rehearsal Public Law (P.L.) 94-171 map products. These files include a sheet identifier, minimum and maximum longitude, minimum and maximum latitude, and the map scale (integer value) for each map sheet. The latitude and longitude coordinates are in decimal degrees and expressed as integer values with six implied decimal places. There is a separate Corner Point File for each of the three map types: County Block Map, Census Tract Outline Map, and Voting District/State Legislative District Outline Map. Each of the three map file types is provided in two formats: Portable Document Format (PDF), for viewing, and Hewlett-Packard Graphics Language (HP-GL) format, for plotting. The County Block Maps show the greatest detail and the most complete set of geographic information of all the maps. These large-scale maps depict the smallest geographic entities for which the Census Bureau presents data -- the census blocks -- by displaying the features that delineate them and the numbers that identify them. These maps show the boundaries, names, and codes for American Indian/Alaska Native areas, county subdivisions, places, census tracts, and, for this series, the geographic entities that the states delineated in Phase 2, Voting District Project, of the Redistricting Data Program. The HP-GL version of the County Block Maps is broken down into index maps and map sheets. The map sheets cover a small area, and the index maps are composed of multiple map sheets, showing the entire area. The intent of the County Block Map series is to provide a map for each county on the smallest possible number of map sheets at the maximum practical scale, dependent on the area size of the county and the density of the block pattern. The latter affects the display of block numbers and feature identifiers. The Census Tract Outline Maps show the boundaries and numbers of census tracts, and name the features underlying the boundaries. These maps also show the boundaries and names of counties, county subdivisions, and places. They identify census tracts in relation to governmental unit boundaries. The mapping unit is the county. These large-format maps are produced to support the P.L. 94-171 program and all other 1998 Dress Rehearsal data tabulations. The Voting District/State Legislative District Outline Maps show the boundaries and codes for voting districts as delineated by the states in Phase 2, Voting District Project, of the Redistricting Data Program. The features underlying the voting district boundaries are shown, as well as the names of these features. Additionally, for states that submit the information, these maps show the boundaries and codes for state legislative districts and their underlying features. These maps also show the boundaries of and names of American Indian/Alaska Native areas, counties, county subdivisions, and places. The scale of the district maps is optimized to keep the number of map sheets for each area to a minimum, but the scale and number of map sheets will vary by the area size of the county and the voting districts and state legislative districts delineated by the states. The Census 2000 Dress Rehearsal TIGER/Line Files consist of line segments representing physical features and governmental and statistical boundaries. The files contain information distributed over a series of record types for the spatial objects of a county. These TIGER/Line Files are an extract of selected geographic and cartographic information from the Census TIGER (Topological
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This layer contains pre-processed address points for Sacramento County, California, which can be added to OpenStreetMap. This data was shared by the County as open data through the Esri Community Maps program and its new option for data sharing.This layer contains 662,634 address points for the County, with complete address info (e.g. housenumber, street, city, state, ZIP code) for each point. The processed address points referenced above were created using these Esri Data Processing Steps for Buildings and Addresses, developed and refined while doing data prep for several city and county communities in the United States.OSM Editor ToolsThis layer is accessible through new tools in OSM editors (e.g. updated version of RapiD) that enable OSM mappers to display the features on a map, select an individual feature to inspect its geometry and tags, and then use the feature for editing. OSM mappers should review the individual features and tags, and make any edits and additions that are appropriate, before selecting other features to edit and uploading edits to OSM.