This presents the Hybrid Reference Layer style (World Edition) and provides a detailed reference layer for the world designed to be overlaid on imagery. The reference layer includes highways, major roads, minor roads, railways, water features, cities, parks, landmarks, and administrative boundaries. This vector tile layer provides unique capabilities for customization, high-resolution display, and use in mobile devices.This vector tile layer is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.This layer is used in the Imagery Hybrid web map included in ArcGIS Living Atlas of the World.See the Vector Basemaps group for other vector tile layers. Customize this StyleLearn more about customizing this vector basemap style using the Vector Tile Style Editor. Additional details are available in ArcGIS Online Blogs and the Esri Vector Basemaps Reference Document.

Services:2015_Parking (FeatureServer)AGO_MAP_2019 (FeatureServer)Bike_Racks_2020 (FeatureServer)BikeParking2017 (FeatureServer)Chicago_Central_Business_District (FeatureServer)Chicago_Wards_hosted (FeatureServer)ChicagoMayHwys (FeatureServer)Control_Points_Interlockings (FeatureServer)ControlPoints_Interlockings (FeatureServer)Cook_County_Districts_hosted (FeatureServer)CTA_Bus_Routes (FeatureServer)CTA_Bus_Routes_2019 (FeatureServer)cta_rail_lines (FeatureServer)CTABusRoutes2019 (FeatureServer)FRA_Crossings (FeatureServer)FreightRailroads (FeatureServer)Grade_Crossings (FeatureServer)Illinois_House_Districts (FeatureServer)Illinois_Senate_Districts (FeatureServer)Lines_COVID19 (FeatureServer)Metra_Bridges (FeatureServer)Metra_facilities (FeatureServer)metra_lines_2018 (FeatureServer)Metra_Routes_Test (FeatureServer)metra_stations_2018 (FeatureServer)MetraLines_2016 (FeatureServer)MetraLines2017 (FeatureServer)MetraLines2019_CreateRoutes (FeatureServer)MetraPoliceBeats (FeatureServer)MetraStations2017new (FeatureServer)Municipalities (FeatureServer)NICTD_South_Shore_Line (FeatureServer)NICTD_Stations (FeatureServer)Pace_ParkNRide_Facilities (FeatureServer)Pace_Routes_03_25_2019 (FeatureServer)PaceRoutes2020 (FeatureServer)Parking_Lots_2016 (FeatureServer)parking_lots_2017 (FeatureServer)Parking_Survey_2018_AGO_Published (FeatureServer)Parking_Survey_2018_Final (FeatureServer)Parking_Survey_2019_Final (FeatureServer)ParkingLots2017 (FeatureServer)Police_Beats_2020_Draft (FeatureServer)Police_tows (FeatureServer)Six_County_Service_Area (FeatureServer)Stations_COVID19 (FeatureServer)Tie_Substations (FeatureServer)TrainsPerDay (FeatureServer)US_Congressional_Districts (FeatureServer)Yards_Points (FeatureServer)yards_points_2019 (FeatureServer)Yards_Polygons (FeatureServer)yards_polygons_2018 (FeatureServer)

Parking citations with latitude / longitude in Mercator map projection which is a variant of Web Mercator, Google Web Mercator, Spherical Mercator, WGS 84 Web Mercator or WGS 84/Pseudo-Mercator and is the de facto standard for Web mapping applications. Additional information about Meractor projections - https://en.wikipedia.org/wiki/Mercator_projection The official EPSG identifier for Web Mercator is EPSG:3857. Additional information on projections can be read here: https://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Projection_basics_the_GIS_professional_needs_to_know For more information on Geographic vs Projected coordinate systems, read here: https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ For information on how to change map projections, read here: https://learn.arcgis.com/en/projects/make-a-web-map-without-web-mercator/

World Imagery provides one meter or better satellite and aerial imagery in many parts of the world and lower resolution satellite imagery worldwide. The map includes 15m TerraColor imagery at small and mid-scales (~1:591M down to ~1:288k) for the world. The map features Maxar imagery at 0.3m resolution for select metropolitan areas around the world, 0.5m resolution across the United States and parts of Western Europe, and 1m resolution imagery across the rest of the world. In addition to commercial sources, the World Imagery map features high-resolution aerial photography contributed by the GIS User Community. This imagery ranges from 0.3m to 0.03m resolution (down to ~1:280 in select communities). For more information on this map, including the terms of use, visit us online at https://goto.arcgisonline.com/maps/World_Imagery

This data set contains geolocation information of the infrastructure locations for the SnowEx20 Intensive Observation Period (IOP) and Time Series (TS) campaigns. Available scientific infrastructure locations in this data set are tower and sensor locations, aircraft flight lines, planned and actual snow pit locations, and time-lapse camera locations. Additionally, this data set contains areal snow depth and tree density classification matrix over the Grand Mesa, CO study area.

Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

These boundaries define the regions based on terrestrial and marine areas. These are intended to be used in by CA Nature to support activities related to Executive Order N-82-20. These include California's 30x30 effort, Climate Smart Land Strategies, and equitable access to open space. This layer is derived from the 4th California Climate Assessment regions, and enhanced using the California County Boundaries dataset (version 19.1) maintained by the California Department of Forestry and Fire Protection's Fire Resource Assessment Program, and the 3 Nautical Mile marine boundary for California sourced from the California Department of Fish and Wildlife.

New Parking Citations dataset here: https://data.lacity.org/Transportation/Parking-Citations/4f5p-udkv/about_data ---Archived as of September 2023--- Parking citations with latitude / longitude (XY) in US Feet coordinates according to the California State Plane Coordinate System - Zone 5 (https://www.conservation.ca.gov/cgs/rgm/state-plane-coordinate-system). For more information on Geographic vs Projected coordinate systems, read here: https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ For information on how to change map projections, read here: https://learn.arcgis.com/en/projects/make-a-web-map-without-web-mercator/

Yearly citation counts for the publication titled "Design and integration of a GIS-based data model for the regional hydrologic simulation in Meijiang watershed, China".

In response to Executive Order 13817 of December 20, 2017, the U.S. Geological Survey (USGS) coordinated with the Bureau of Land Management (BLM) to identify 36 nonfuel minerals or mineral materials considered critical to the economic and national security of the United States (U.S.) (https://pubs.usgs.gov/of/2018/1021/ofr20181021.pdf). Acquiring information on possible domestic sources of these critical minerals is the rationale for the USGS Earth Mapping Resources Initiative (Earth MRI). The program, which partners the USGS with State Geological Surveys, Federal agencies, and the private sector, aims to collect new geological, geophysical, and topographic (lidar) data in key areas of the U.S. to stimulate mineral exploration and production of critical minerals. The USGS has identified broad areas within the United States to target acquisition of geologic mapping, geophysical data, and (or) detailed topographic information to aid research, mineral exploration, and evaluation of m ...

Police citations for 2025. Data from the electronic citations issued by the Sacramento Police Department. This data is updated monthly. One citation could include multiple charges, and will therefore result in showing on multiple lines in the data, extract. Date/Time fields are string data types and will be viewed and downloaded in US/Pacific time. Contact SacGIS@cityofsacramento.org.

A Groundwater Body (GWB) under the Water Framework Directive (WFD) Art. 2 is defined as a distinct volume of groundwater within an aquifer or aquifers, whereas an aquifer is defined as a geological layer with significant groundwater flow. This definition of a GWB allows a wide scope of interpretations. EU Member States (MS) are under obligation to report the GWBs including the results of the GWB survey periodically according to the schedule of the WFD. Reportnet is used for the submission of GWB data to the EEA by MS and includes spatial data as GIS polygons and GWB characteristics in an XML schema.

The WISE provisional reference GIS WFD Dataset on GWBs combines spatial data consisting of several shape files and certain GWB attributes in a single table submitted by the MS according to Art. 13. The GWBs are divided into horizons, which represent distinct vertical layers of groundwater resources. All GWBs assigned to a certain horizon from one to five are merged into one shape file. GWBs assigned to horizons six or seven are combined in a single further shape file. Another two shape files comprise the GWBs of Reunion Island in the southern hemisphere and the GWBs from Switzerland as a non EU MS, all of which assigned to horizon 1.

The dbf tables of the shape files include the columns “EU_CD_GW” as the GWB identifier and “Horizon” describing the vertical positioning. The polygon identifier “Polygon_ID” was added subsequently, because some GWBs consist of several polygons with identical “EU_CD_GW”even in the same horizon. Some further GWB characteristics are provided with the Microsoft Excel file “GWB_attributes_2012June.xls” including the column “EU_CD_GW”, which serves as a key for joining spatial and attribute data. There is no corresponding spatial data for GWBs in the Microsoft Excel table without an entry in column “EU_CD_GW”. The spatial resolution is given for about a half of the GWBs in the column “Scale” of the xls file, which is varying between the MS from 1 : 10,000 to 1 : 1,000,000 and mostly in the range from 1 : 50,000 to 1 : 250,000. The processing of some of the GWB shape files by GIS routines as clip or intersect in combination with a test polygon resulted in errors. Therefore a correction of erroneous topological features causing routine failures was carried out. However, the GWB layer includes a multitude of in parts very tiny, distinct areas resulting in a highly detailed or fragmented pattern. In certain parts topological inconsistencies appear quite frequently and delineation methodologies are currently varying between the MS in terms of size and three dimensional positioning of GWBs. This version of the dataset has to be considered as a first step towards a consistent GWB picture throughout Europe, but it is not yet of a sufficient quality to support spatial analyses i.e. it is not a fully developed reference GIS dataset. Therefore, the layer is published as a preliminary version and use of this data is subject to certain restrictions outlined in the explanatory notes.

It should be underlined that the methodology used is still under discussion (Working Group C -Groundwater) and is not fully harmonised throughout the EU MS.

For the external publication the whole United Kingdom had to be removed due to licensing restrictions.

Yearly citation counts for the publication titled "Transport System Models and Big Data: Zoning and Graph Building with Traditional Surveys, FCD and GIS".

World Imagery provides one meter or better satellite and aerial imagery for most of the world’s landmass and lower resolution satellite imagery worldwide. The map is currently comprised of the following sources:Worldwide 15-m resolution TerraColor imagery at small and medium map scales.Vantor imagery basemap products around the world: Vivid Premium at 15-cm HD resolution for select metropolitan areas, Vivid Advanced 30-cm HD for more than 1,000 metropolitan areas, and Vivid Standard from 1.2-m to 0.6-cm resolution for the most of the world, with 30-cm HD across the United States and parts of Western Europe. More information on the Vantor products is included below. High-resolution aerial photography contributed by the GIS User Community. This imagery ranges from 30-cm to 3-cm resolution. You can contribute your imagery to this map and have it served by Esri via the Community Maps Program. Vantor Basemap ProductsVivid PremiumProvides committed image currency in a high-resolution, high-quality image layer over defined metropolitan and high-interest areas across the globe. The product provides 15-cm HD resolution imagery.Vivid AdvancedProvides committed image currency in a high-resolution, high-quality image layer over defined metropolitan and high-interest areas across the globe. The product includes a mix of native 30-cm and 30-cm HD resolution imagery.Vivid StandardProvides a visually consistent and continuous image layer over large areas through advanced image mosaicking techniques, including tonal balancing and seamline blending across thousands of image strips. Available from 1.2-m down to 30-cm HD. More on Vantor HD. Imagery UpdatesYou can use the Updates Mode in the World Imagery Wayback app to learn more about recent and pending updates. Accessing this information requires a user login with an ArcGIS organizational account. CitationsThis layer includes imagery provider, collection date, resolution, accuracy, and source of the imagery. With the Identify tool in ArcGIS Desktop or the ArcGIS Online Map Viewer you can see imagery citations. Citations returned apply only to the available imagery at that location and scale. You may need to zoom in to view the best available imagery. Citations can also be accessed in the World Imagery with Metadata web map. UseYou can add this layer to the ArcGIS Online Map Viewer, ArcGIS Desktop, or ArcGIS Pro. To view this layer with a useful reference overlay, open the Imagery Hybrid web map. FeedbackHave you ever seen a problem in the Esri World Imagery Map that you wanted to report? You can use the Imagery Map Feedback web map to provide comments on issues. The feedback will be reviewed by the ArcGIS Online team and considered for one of our updates.

Dataset for the textbook Computational Methods and GIS Applications in Social Science (3rd Edition), 2023 Fahui Wang, Lingbo Liu Main Book Citation: Wang, F., & Liu, L. (2023). Computational Methods and GIS Applications in Social Science (3rd ed.). CRC Press. https://doi.org/10.1201/9781003292302 KNIME Lab Manual Citation: Liu, L., & Wang, F. (2023). Computational Methods and GIS Applications in Social Science - Lab Manual. CRC Press. https://doi.org/10.1201/9781003304357 KNIME Hub Dataset and Workflow for Computational Methods and GIS Applications in Social Science-Lab Manual Update Log If Python package not found in Package Management, use ArcGIS Pro's Python Command Prompt to install them, e.g., conda install -c conda-forge python-igraph leidenalg NetworkCommDetPro in CMGIS-V3-Tools was updated on July 10,2024 Add spatial adjacency table into Florida on June 29,2024 The dataset and tool for ABM Crime Simulation were updated on August 3, 2023, The toolkits in CMGIS-V3-Tools was updated on August 3rd,2023. Report Issues on GitHub https://github.com/UrbanGISer/Computational-Methods-and-GIS-Applications-in-Social-Science Following the website of Fahui Wang : http://faculty.lsu.edu/fahui Contents Chapter 1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana Chapter 2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Case Study 2A: Estimating Drive Time and Transit Time in Baton Rouge, Louisiana Case Study 2B: Analyzing Distance Decay Behavior for Hospitalization in Florida Chapter 3. Spatial Smoothing and Spatial Interpolation Case Study 3A: Mapping Place Names in Guangxi, China Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana Case Study 3C: Detecting Spatiotemporal Crime Hotspots in Baton Rouge, Louisiana Chapter 4. Delineating Functional Regions and Applications in Health Geography Case Study 4A: Defining Service Areas of Acute Hospitals in Baton Rouge, Louisiana Case Study 4B: Automated Delineation of Hospital Service Areas in Florida Chapter 5. GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Case Study 5: Measuring Accessibility of Primary Care Physicians in Baton Rouge Chapter 6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Case Study 6: Analyzing Population Density Patterns in Chicago Urban Area >Chapter 7. Principal Components, Factor and Cluster Analyses and Application in Social Area Analysis Case Study 7: Social Area Analysis in Beijing Chapter 8. Spatial Statistics and Applications in Cultural and Crime Geography Case Study 8A: Spatial Distribution and Clusters of Place Names in Yunnan, China Case Study 8B: Detecting Colocation Between Crime Incidents and Facilities Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago Chapter 9. Regionalization Methods and Application in Analysis of Cancer Data Case Study 9: Constructing Geographical Areas for Mapping Cancer Rates in Louisiana Chapter 10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City Chapter 11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio Case Study 11B: Location-Allocation Analysis of Hospitals in Rural China Chapter 12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations Case Study 12A. Examining Zonal Effect on Urban Population Density Functions in Chicago by Monte Carlo Simulation Case Study 12B: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana Chapter 13. Agent-Based Model and Application in Crime Simulation Case Study 13: Agent-Based Crime Simulation in Baton Rouge, Louisiana Chapter 14. Spatiotemporal Big Data Analytics and Application in Urban Studies Case Study 14A: Exploring Taxi Trajectory in ArcGIS Case Study 14B: Identifying High Traffic Corridors and Destinations in Shanghai Dataset File Structure 1 BatonRouge Census.gdb BR.gdb 2A BatonRouge BR_Road.gdb Hosp_Address.csv TransitNetworkTemplate.xml BR_GTFS Google API Pro.tbx 2B Florida FL_HSA.gdb R_ArcGIS_Tools.tbx (RegressionR) 3A China_GX GX.gdb 3B BatonRouge BR.gdb 3C BatonRouge BRcrime R_ArcGIS_Tools.tbx (STKDE) 4A BatonRouge BRRoad.gdb 4B Florida FL_HSA.gdb HSA Delineation Pro.tbx Huff Model Pro.tbx FLplgnAdjAppend.csv 5 BRMSA BRMSA.gdb Accessibility Pro.tbx 6 Chicago ChiUrArea.gdb R_ArcGIS_Tools.tbx (RegressionR) 7 Beijing BJSA.gdb bjattr.csv R_ArcGIS_Tools.tbx (PCAandFA, BasicClustering) 8A Yunnan YN.gdb R_ArcGIS_Tools.tbx (SaTScanR) 8B Jiangsu JS.gdb 8C Chicago ChiCity.gdb cityattr.csv ...

This is a link to the Automated Geographic Reference Center (AGRC) that houses GIS data for the state of Utah. This includes geoscience, cadastre, elevation and terrain, digital aerial photography, roads, aquifer data, etc. Several GIS datasets used in the Utah FORGE project originated from this site.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The Geoscience Australia Onshore Seismic GIS layer is layer showing the locations of Onshore Seismic Survyes carried out by Geoscience Australia and it's predecessors, Australian Geological Survey Organisation (AGSO) and the Bureau of Mineral Resources (BMR). The layer contains URL link to free downloadable data. The data includes processed data in SEGY format. The metadata includes acquisition reports, processing reports, processed images and so on. The data acquisition was carried out in Australia from 1949 to present by Geoscience Australia and various partners such as State and Geologcial Survey Organisations. The set of reflection and refraction data comprises over 12,000 km of coverage, and provides an insight into the variations in crustal architecture in the varied geological domains.

Dataset History

First published 2014. Will be updated as latest data becomes available.

http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_f229d5de-356c-573c-e044-00144fdd4fa6/Geoscience+Australia+Onshore+Seismic+GIS+layer

The data acquisition was carried out in Australia from 1949 to present by Geoscience Australia and various partners such as State and Geologcial Survey Organisations.

Dataset Citation

Geoscience Australia (2014) Geoscience Australia onshore seismic GIS layer. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/d83e995a-41ac-41a7-806b-87b09de98065.

The ETo Zones Map allows users to view the grass-reference evapotranspiration (ETo) Zones for the State of California. The map was developed by DWR and UC Davis in 1999 and divides the State into 18 zones based on long-term monthly average ETo. The ETo values were calculated using data from various data sources, including CIMIS weather stations that had at least five years of archived data. This dataset is the version from 1999.