Point data representing CTA park and ride locations. Details include number of spaces, cost, and rail station. To view or use these files, compression software and special GIS software, such as ESRI ArcGIS is required. Projected Coordinate System: NAD_1983_StatePlane_Illinois_East_FIPS_1201_Feet

Curnamona Province MGA GIS DVDVersion 2 of the Curnamona Province dataset was produced as a co-operative venture between Primary Industries and Resources South Australia (PIRSA), GA (Geoscience Australia) and DMR (New South Wales Department of Mineral Resources). It contains data from South Australia and New South Wales.For a generalised map of Dataset Locations, click here. * Coordinate projection MGA Zone 54 (GDA94). * Dataset size 2.4 Gb * Available formats: ESRI shapefile (ArcGIS, ArcView), MapInfo on DVD-ROM. Users must provide their own software. * DVD-ROM Dataset Price AUD$20. To purchase online, please link to SARIG and go to the Products section.

Available at the Map and Data Library. CD #163.

Lidar Digital Elevation Models (DEMs) at 2-meter resolution have been used to derive watershed boundaries for the State of Maine. Geographic Information Systems (GIS) software was used to hydrologically enforce lidar DEMs and delineate watershed boundaries at pre-existing pour point locations (Price, 2016). The watershed boundaries are comparable in size to the 12-digit Hydrologic Unit catchments and have a 12-digit Hydrologic Unit Code (HUC12) identifier attribute field that has a one-to-one match with the national WBD dataset (https://www.usgs.gov/national-hydrography/watershed-boundary-dataset). This data release consists of a zip file containing an ESRI polygon shapefile (vector GIS dataset). This work was conducted in cooperation with Maine Department of Transportation and Maine Office of GIS. Curtis Price, 20160606, WBD HU12 Pour Points derived from NHDPlus: U.S. Geological Survey data release, https://www.sciencebase.gov/catalog/item/5762b664e4b07657d19a71ea

Esri Disaster Response Program (DRP) assistance request form. Use this website to request assistance.

Download In State Plane Projection Here The 2017 Digital Terrain Model (DTM) is a 2 foot pixel resolution raster in Erdas IMG format. This was created using the ground (class = 2) lidar points and incorporating the breaklines. The DTMs were developed using LiDAR data. LiDAR is an acronym for LIght Detection And Ranging. Light detection and ranging is the science of using a laser to measure distances to specific points. A specially equipped airplane with positioning tools and LiDAR technology was used to measure the distance to the surface of the earth to determine ground elevation. The classified points were developed using data collected in April to May 2017. The LiDAR points, specialized software, and technology provide the ability to create a high precision three-dimensional digital elevation and/or terrain models (DEM/DTM). The use of LiDAR significantly reduces the cost for developing this information. The DTMs are intended to correspond to the orthometric heights of the bare surface of the county (no buildings or vegetation cover). DTM data is used by county agencies to study drainage issues such as flooding and erosion; contour generation; slope and aspect; and hill shade images. This dataset was compiled to meet the American Society for Photogrammetry and Remote Sensing (ASPRS) Accuracy Standards for Large-Scale Maps, CLASS 1 map accuracy. The U.S. Army Corps of Engineers Engineering and Design Manual for Photogrammetric Production recommends that data intended for this usage scale be used for any of the following purposes: route location, preliminary alignment and design, preliminary project planning, hydraulic sections, rough earthwork estimates, or high-gradient terrain / low unit cost earthwork excavation estimates. The manual does not recommend that these data be used for final design, excavation and grading plans, earthwork computations for bid estimates or contract measurement and payment. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

The percent and rate (per 100,000 persons) of eligible Maricopa County residents (based on residential address) who have received COVID-19 vaccine are mapped by ZIP code and city of residence. Maricopa County resident vaccine data: Arizona State Immunization Information System (ASIIS) via ADHS. Vaccine-Eligible Maricopa County population: Census 2020 estimates calculated by the geographic information system (GIS) software company, Esri.View the map and data dashboard at: https://www.maricopa.gov/COVID19VaccineData

description: Beach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations continue to grow, and community infrastructures are threatened by erosion, there is increased demand for accurate information regarding past and present shoreline changes. There is also need for a comprehensive analysis of shoreline movement that is regionally consistent. To meet these national needs, the USGS National Assessment of Shoreline Change Project has collected and analyzed a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. This dataset consists of short-term (~30 years) shoreline change rates. Rate calculations were computed using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end-point rate method based on available shorelines to provide an approximately 30-yr short-term rate. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates. To make these results more accessible to the public and other agencies, the USGS created this web service. This web service was created utilizing ESRI ArcServer. This service meets open geospatial consortium standards. The data compilation used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Historic Shorelines by State. The reference baseline used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Offshore Baseline. The locations of the transects used in the change rate calculation are available in a service with the title USGS Map service: National Shoreline Change - Intersection Points. The geographic information system (GIS) data layers from this web service are cataloged by state for ease of access.; abstract: Beach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations continue to grow, and community infrastructures are threatened by erosion, there is increased demand for accurate information regarding past and present shoreline changes. There is also need for a comprehensive analysis of shoreline movement that is regionally consistent. To meet these national needs, the USGS National Assessment of Shoreline Change Project has collected and analyzed a comprehensive database of digital vector shorelines by compiling shoreline positions from pre-existing historical shoreline databases and by generating historical and modern shoreline data. This dataset consists of short-term (~30 years) shoreline change rates. Rate calculations were computed using the Digital Shoreline Analysis System (DSAS), an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using an end-point rate method based on available shorelines to provide an approximately 30-yr short-term rate. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates. To make these results more accessible to the public and other agencies, the USGS created this web service. This web service was created utilizing ESRI ArcServer. This service meets open geospatial consortium standards. The data compilation used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Historic Shorelines by State. The reference baseline used to derive the shoreline change rates is available in a service with the title USGS Map service: National Shoreline Change - Offshore Baseline. The locations of the transects used in the change rate calculation are available in a service with the title USGS Map service: National Shoreline Change - Intersection Points. The geographic information system (GIS) data layers from this web service are cataloged by state for ease of access.

As part of the Maine Beach Mapping Program (MBMAP), MGS surveys annual alongshore shoreline positions (see Beach_Mapping_Shorelines). Using these shoreline positions and guidance from the USGS Digital Shoreline Analysis System (DSAS). DSAS is referenced as Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Ergul, Ayhan, 2009, Digital Shoreline Analysis System (DSAS) version 4.0— An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2008-1278. For more information on DSAS and the methodology DSAS employs, please see: https://woodshole.er.usgs.gov/project-pages/DSAS/. The supporting DSAS User Guide which describes how DSAS works and how statistics are calculated is available here: http://www.maine.gov/dacf/mgs/hazards/beach_mapping/DSAS_manual.pdf. MGS wrote a database procedure following protocols outlined in DSAS that allows for the calculation of different shoreline change rates and supporting statistics. This was done so that MGS no longer needed to depend on USGS updates to the DSAS software to keep current with ArcGIS software updates. The script casts shoreline-perpendicular transects at a set spacing (in this case, 10-m intervals along the shoreline), from a preset baseline (located landward of the monitored shorelines), and calculates a range of shoreline change statistics, including: Process Time: The time when the statistics were calculated. TransectID: The ID of the transect (including the group or line section ID; for example, 1-1, is line 1, transect 1) SCE: Shoreline Change Envelope. The distance, in meters, between the shoreline farthest from and closests to the baseline at each transect. NSM: Net Shoreline Movement. The distance, in meters, between the oldest and youngest shorelines for each tranect. EPR: End Point Rate. A shoreline change rate, in meters/year, calculated by dividing the NSM by the time elapsed between the oldest and youngest shorelines at each transect. LRR: Linear Regression Rate. A shoreline change rate, in meters/year, calculated by fitting a least-squares regression line to all of the shoreline points for a particular transect. The distance from the baseline, in meters, is plotted against the shoreline date, and slope of the line that provides the best fit is the LRR. LR2: The R-squared statistic, or coefficient of determination. The percentage of variance in the data that is explained by a regression, or in this case, the LRR value. It is a dimensionless index that ranges from 1.0 (a perfect fit, with the best fit line explaining all variation) to 0.0 (a bad fit, with the best fit line explaining little to no variation) and measures how successfully the best fit line (LRR) accounts for variation in the data. LCI95: Standard error of the slope at the 95% confidence interval. Calculated by muliplying the standard error, or standard deviation, of the slope by the two-tailed test statistic at the user-specified confidence percentage. For example if a reported LRR is 1.34 m/yr and a calculated LCI95 is 0.50, the band of confidence around the LRR is +/- 0.50. In other words, you can be 95% confidence that the true rate of change is between 0.84 and 1.84 m/yr. LRR_ft: The Linear Regression Rate, converted to feet/year. LCI95_ft: The LCI95, converted to feet. EPR_ft: The End Point Rate converted to feet.

As part of the Maine Beach Mapping Program (MBMAP), MGS surveys annual alongshore shoreline positions (see Beach_Mapping_Shorelines). Using these shoreline positions and guidance from the USGS Digital Shoreline Analysis System (DSAS). DSAS is referenced as Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Ergul, Ayhan, 2009, Digital Shoreline Analysis System (DSAS) version 4.0— An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2008-1278. For more information on DSAS and the methodology DSAS employs, please see: https://woodshole.er.usgs.gov/project-pages/DSAS/. The supporting DSAS User Guide which describes how DSAS works and how statistics are calculated is available here: http://www.maine.gov/dacf/mgs/hazards/beach_mapping/DSAS_manual.pdf. MGS wrote a database procedure following protocols outlined in DSAS that allows for the calculation of different shoreline change rates and supporting statistics. This was done so that MGS no longer needed to depend on USGS updates to the DSAS software to keep current with ArcGIS software updates. The script casts shoreline-perpendicular transects at a set spacing (in this case, 10-m intervals along the shoreline), from a preset baseline (located landward of the monitored shorelines), and calculates a range of shoreline change statistics, including: Process Time: The time when the statistics were calculated. TransectID: The ID of the transect (including the group or line section ID; for example, 1-1, is line 1, transect 1) SCE: Shoreline Change Envelope. The distance, in meters, between the shoreline farthest from and closests to the baseline at each transect. NSM: Net Shoreline Movement. The distance, in meters, between the oldest and youngest shorelines for each tranect. EPR: End Point Rate. A shoreline change rate, in meters/year, calculated by dividing the NSM by the time elapsed between the oldest and youngest shorelines at each transect. LRR: Linear Regression Rate. A shoreline change rate, in meters/year, calculated by fitting a least-squares regression line to all of the shoreline points for a particular transect. The distance from the baseline, in meters, is plotted against the shoreline date, and slope of the line that provides the best fit is the LRR. LR2: The R-squared statistic, or coefficient of determination. The percentage of variance in the data that is explained by a regression, or in this case, the LRR value. It is a dimensionless index that ranges from 1.0 (a perfect fit, with the best fit line explaining all variation) to 0.0 (a bad fit, with the best fit line explaining little to no variation) and measures how successfully the best fit line (LRR) accounts for variation in the data. LCI95: Standard error of the slope at the 95% confidence interval. Calculated by muliplying the standard error, or standard deviation, of the slope by the two-tailed test statistic at the user-specified confidence percentage. For example if a reported LRR is 1.34 m/yr and a calculated LCI95 is 0.50, the band of confidence around the LRR is +/- 0.50. In other words, you can be 95% confidence that the true rate of change is between 0.84 and 1.84 m/yr. LRR_ft: The Linear Regression Rate, converted to feet/year. LCI95_ft: The LCI95, converted to feet. EPR_ft: The End Point Rate converted to feet.

As part of the Maine Beach Mapping Program (MBMAP), MGS surveys annual alongshore shoreline positions (see Beach_Mapping_Shorelines). Using these shoreline positions and guidance from the USGS Digital Shoreline Analysis System (DSAS). DSAS is referenced as Thieler, E.R., Himmelstoss, E.A., Zichichi, J.L., and Ergul, Ayhan, 2009, Digital Shoreline Analysis System (DSAS) version 4.0— An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2008-1278. For more information on DSAS and the methodology DSAS employs, please see: https://woodshole.er.usgs.gov/project-pages/DSAS/. The supporting DSAS User Guide which describes how DSAS works and how statistics are calculated is available here: http://www.maine.gov/dacf/mgs/hazards/beach_mapping/DSAS_manual.pdf. MGS wrote a database procedure following protocols outlined in DSAS that allows for the calculation of different shoreline change rates and supporting statistics. This was done so that MGS no longer needed to depend on USGS updates to the DSAS software to keep current with ArcGIS software updates. The script casts shoreline-perpendicular transects at a set spacing (in this case, 10-m intervals along the shoreline), from a preset baseline (located landward of the monitored shorelines), and calculates a range of shoreline change statistics, including: Process Time: The time when the statistics were calculated. TransectID: The ID of the transect (including the group or line section ID; for example, 1-1, is line 1, transect 1) SCE: Shoreline Change Envelope. The distance, in meters, between the shoreline farthest from and closests to the baseline at each transect. NSM: Net Shoreline Movement. The distance, in meters, between the oldest and youngest shorelines for each tranect. EPR: End Point Rate. A shoreline change rate, in meters/year, calculated by dividing the NSM by the time elapsed between the oldest and youngest shorelines at each transect. LRR: Linear Regression Rate. A shoreline change rate, in meters/year, calculated by fitting a least-squares regression line to all of the shoreline points for a particular transect. The distance from the baseline, in meters, is plotted against the shoreline date, and slope of the line that provides the best fit is the LRR. LR2: The R-squared statistic, or coefficient of determination. The percentage of variance in the data that is explained by a regression, or in this case, the LRR value. It is a dimensionless index that ranges from 1.0 (a perfect fit, with the best fit line explaining all variation) to 0.0 (a bad fit, with the best fit line explaining little to no variation) and measures how successfully the best fit line (LRR) accounts for variation in the data. LCI95: Standard error of the slope at the 95% confidence interval. Calculated by muliplying the standard error, or standard deviation, of the slope by the two-tailed test statistic at the user-specified confidence percentage. For example if a reported LRR is 1.34 m/yr and a calculated LCI95 is 0.50, the band of confidence around the LRR is +/- 0.50. In other words, you can be 95% confidence that the true rate of change is between 0.84 and 1.84 m/yr. LRR_ft: The Linear Regression Rate, converted to feet/year. LCI95_ft: The LCI95, converted to feet. EPR_ft: The End Point Rate converted to feet.