The Human Geography Map (World Edition) web map provides a detailed vector basemap with a monochromatic style and content adjusted to support Human Geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Base, a simple basemap consisting of land areas in a very light gray only.The vector tile layers in this web map are 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.Learn more about this basemap from the cartographic designer in Introducing a Human Geography Basemap.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.

Derek H. Alderman, Joshua F.J. Inwood, Ethan BottoneThe mapping behind the movement: On recovering the critical cartographies of the African American Freedom Struggle,Geoforum,Volume 120,2021,Pages 67-78,ISSN 0016-7185,https://doi.org/10.1016/j.geoforum.2021.01.022.(https://www.sciencedirect.com/science/article/pii/S0016718521000300)Abstract: Responding to recent work in critical cartographic studies and Black Geographies, the purpose of this paper is to offer a conceptual framework and a set of evocative cartographic engagements that can inform geography as it recovers the seldom discussed history of counter-mapping within the African American Freedom Struggle. Black resistant cartographies stretch what constitutes a map, the political work performed by maps, and the practices, spaces, and political-affective dimensions of mapping. We offer an extended illustration of the conventional and unconventional mapping behind USA anti-lynching campaigns of the late 19th and early 20th centuries, highlighting the knowledge production practices of the NAACP and the Tuskegee Institute’s Monroe Work, and the embodied counter-mapping of journalist/activist Ida B. Wells. Recognizing that civil rights struggles are long, always unfolding, and relationally tied over time and space, we link this look from the past to contemporary, ongoing resistant cartographical practices as scholars/activists continue to challenge racialized violence and advance transitional justice, including the noted memory-work of the Equal Justice Initiative. An understanding of African American traditions of counter-mapping is about more than simply inserting the Black experience into our dominant ideas about cartography or even resistant mapping. Black geographies has much to teach cartography and geographers about what people of color engaged in antiracist struggles define as geographic knowledge and mapping practices on their own terms—hopefully provoking a broader and more inclusive definition of the discipline itself.Keywords: African American; Anti-lynching; Black geographies; Civil rights; Counter-mapping; Critical cartography

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Point Sur to Point Arguello map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Point Sur to Point Arguello map area data layers. Data layers are symbolized as shown on the associated map sheets.

Take a looks at the Harvard Map Collection's interactive exhibit 'Embellishing the Map,' which explores the myriad varieties and uses of embellishments found on the library's extraordinary collection of maps.This exhibition presents maps chosen from the Harvard Map Collection that display how European cartographers, mainly from the Low Countries of the 16th and 17th centuries, embellished maps with a variety of illustrative, non-cartographic elements. With echoes of the classical world’s anxiety of the “horror vacuii” (fear of empty spaces), the uncharted and unknown spaces are populated with sea creatures and animals, from the mythic and fantastic to the zoologically accurate, and many varieties of ships plying the open seas. All in their natural habitat, which is to say located on the land and seas of the map, not as artistic embellishments in cartouches or title panels (something for another exhibition, perhaps). The sources for the cartographic fauna run the gamut from classical sources (the histories of Herodotus and Pliny the Elder), Medieval bestiaries and compendiums of the natural world (Hortus Sanitatis), to accounts from the ever peripatetic explorers. The maps are presented in loosely geographic order, beginning (where everything begins) with the heavens, then, after a medieval view of the known world, moves from the Western Hemisphere eastward to the Pacific Ocean. Besides the few modern, more thematic maps that have been included for contrast, chronologically this exhibition effectively ends before the ascendancy of the Royally sponsored French cartographers of the 18th century. The maps of Delisle, Bellin, d’Anville and the distinguished Cassini dynasty migrate the sea creatures, animals and ships to the pages and articles of Diederot’s grand Encyclopedia. What now is presented on the map reflects the science of cartography and measurement reigning supreme, not alas (as seen in the 1541 map “Tabula noua partis Africae”), a King riding a bridled Sea Carp!

NOTICE TO PROVISIONAL 2023 LAND USE DATA USERS: Please note that on December 6, 2024 the Department of Water Resources (DWR) published the Provisional 2023 Statewide Crop Mapping dataset. The link for the shapefile format of the data mistakenly linked to the wrong dataset. The link was updated with the appropriate data on January 27, 2025. If you downloaded the Provisional 2023 Statewide Crop Mapping dataset in shapefile format between December 6, 2024 and January 27, we encourage you to redownload the data. The Map Service and Geodatabase formats were correct as posted on December 06, 2024.

Thank you for your interest in DWR land use datasets.

The California Department of Water Resources (DWR) has been collecting land use data throughout the state and using it to develop agricultural water use estimates for statewide and regional planning purposes, including water use projections, water use efficiency evaluations, groundwater model developments, climate change mitigation and adaptations, and water transfers. These data are essential for regional analysis and decision making, which has become increasingly important as DWR and other state agencies seek to address resource management issues, regulatory compliances, environmental impacts, ecosystem services, urban and economic development, and other issues. Increased availability of digital satellite imagery, aerial photography, and new analytical tools make remote sensing-based land use surveys possible at a field scale that is comparable to that of DWR’s historical on the ground field surveys. Current technologies allow accurate large-scale crop and land use identifications to be performed at desired time increments and make possible more frequent and comprehensive statewide land use information. Responding to this need, DWR sought expertise and support for identifying crop types and other land uses and quantifying crop acreages statewide using remotely sensed imagery and associated analytical techniques. Currently, Statewide Crop Maps are available for the Water Years 2014, 2016, 2018- 2022 and PROVISIONALLY for 2023.

Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer: https://gis.water.ca.gov/app/CADWRLandUseViewer.

For Regional Land Use Surveys follow: https://data.cnra.ca.gov/dataset/region-land-use-surveys.

For County Land Use Surveys follow: https://data.cnra.ca.gov/dataset/county-land-use-surveys.

For a collection of ArcGIS Web Applications that provide information on the DWR Land Use Program and our data products in various formats, visit the DWR Land Use Gallery: https://storymaps.arcgis.com/collections/dd14ceff7d754e85ab9c7ec84fb8790a.

Recommended citation for DWR land use data: California Department of Water Resources. (Water Year for the data). Statewide Crop Mapping—California Natural Resources Agency Open Data. Retrieved “Month Day, YEAR,” from https://data.cnra.ca.gov/dataset/statewide-crop-mapping.

CONABIO provides online cartography through cartographic metadata distributed following the guidelines in the Standards for Digital Geospatial Metadata of FGDC-NBII (Federal Geographic Data Committee – National Biological Information Infrastructure), 1996. The cartographic information is queried through a database that is organized based on themes (biotic, physical and social aspects, regionalization and others), scales, and geographic area. The metadata content is presented as basic information, reports of the information (methodology) and spatial data information. The cartography is available online at no charge in distinct formats like: export file for Arc/Info (.E00) and shape file (ESRI), and DXF (Drawing eXchange Format). Maps is presented in cartographic projections: Lambert Conic Conformal, UTM and geographic coordinates system. GIF format of map images can be obtained as well.

This web map presents a vector basemap of OpenStreetMap (OSM) data hosted by Esri. Esri created this vector tile basemap from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. This version of the map is rendered using OSM cartography. The OSM Daylight map will be updated every month with the latest version of OSM Daylight data.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site:www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this enhanced vector basemap available to the ArcGIS user and developer communities.

The Digital Geologic Map of the U.S. Geological Survey Mapping in the Western Portion of Amistad National Recreation Area, Texas is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Eddie Collins, Amanda Masterson and Tom Tremblay (Texas Bureau of Economic Geology); Rick Page (U.S. Geological Survey); Gilbert Anaya (International Boundary and Water Commission). Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (wpam_metadata.txt; available at http://nrdata.nps.gov/amis/nrdata/geology/gis/wpam_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (wpam_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of Amistad National Recreation Area.

Abstract

This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme.

Cartographic masks for map products COO_120, used for clear annotation and masking unwanted features from report maps.

Dataset History

Masks created using the 'Features Outline Masks (Cartography)' tool on annotation layers within ArcCatalog.

Dataset Citation

Bioregional Assessment Programme (2015) Cartographic masks for map products COO 120 v02. Bioregional Assessment Source Dataset. Viewed 27 November 2017, http://data.bioregionalassessments.gov.au/dataset/9d711dbb-cfe7-42bc-ab60-f6a1086c33a8.

The Digital Geologic Map of International Boundary and Water Commission Mapping in Amistad National Recreation Area, Texas and Mexico is composed of GIS data layers complete with ArcMap 9.3 layer (.LYR) files, two ancillary GIS tables, a Map PDF document with ancillary map text, figures and tables, a FGDC metadata record and a 9.3 ArcMap (.MXD) Document that displays the digital map in 9.3 ArcGIS. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Eddie Collins, Amanda Masterson and Tom Tremblay (Texas Bureau of Economic Geology); Rick Page (U.S. Geological Survey); Gilbert Anaya (International Boundary and Water Commission). Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation sections(s) of this metadata record (ibwc_metadata.txt; available at http://nrdata.nps.gov/amis/nrdata/geology/gis/ibwc_metadata.xml). All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.1. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data is available as a 9.3 personal geodatabase (ibwc_geology.mdb), and as shapefile (.SHP) and DBASEIV (.DBF) table files. The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of Amistad National Recreation Area.

The Human Geography Dark Map (World Edition) web map provides a detailed world basemap with a dark monochromatic style and content adjusted to support human geography information. Where possible, the map content has been adjusted so that it observes WCAG contrast criteria.This basemap, included in the ArcGIS Living Atlas of the World, uses 3 vector tile layers:Human Geography Dark Label, a label reference layer including cities and communities, countries, administrative units, and at larger scales street names.Human Geography Dark Detail, a detail reference layer including administrative boundaries, roads and highways, and larger bodies of water. This layer is designed to be used with a high degree of transparency so that the detail does not compete with your information. It is set at approximately 50% in this web map, but can be adjusted.Human Geography Dark Base, a simple basemap consisting of land areas in a very dark gray only.The vector tile layers in this web map are 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.Learn more about this basemap from the cartographic designer in A Dark Version of the Human Geography Basemap.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layers referenced in this map.

The Crisis Mapping Toolkit (CMT) is a collection of tools for processing geospatial data (images, satellite data, etc.) into cartographic products that improve understanding of large-scale crises, such as natural disasters. The cartographic products produced by CMT include flood inundation maps, maps of damaged or destroyed structures, forest fire maps, population density estimates, etc. CMT is designed to rapidly process large-scale data using Google Earth Engine and other geospatial data systems.

Abstract

This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme.

Cartographic masks for map products COO 116, used for clear annotation and masking unwanted features from report maps.

Dataset History

Masks created using the 'Features Outline Masks (Cartography)' tool on annotation layers (labels) within ArcMap.

Dataset Citation

Bioregional Assessment Programme (2015) Cartographic masks for map products COO 116. Bioregional Assessment Source Dataset. Viewed 05 July 2017, http://data.bioregionalassessments.gov.au/dataset/0b52e0d0-9a5c-413e-a60f-715ac23e03a4.

The USGS Topo base map service from The National Map is a combination of contours, shaded relief, woodland and urban tint, along with vector layers, such as geographic names, governmental unit boundaries, hydrography, structures, and transportation, to provide a composite topographic base map. Data sources are the National Atlas for small scales, and The National Map for medium to large scales.

Abstract This dataset was created within the Bioregional Assessment Programme for cartographic purposes. Data has not been derived from any source datasets. Metadata has been compiled by the Bioregional Assessment Programme. Cartographic masks for map products COO 112, used for clear annotation and masking unwanted features from report maps. ## Dataset History Masks created using the 'Features Outline Masks (Cartography)' tool on annotation layers (labels) within ArcMap. ## Dataset Citation Bioregional Assessment Programme (2015) Cartographic masks for map products COO 112. Bioregional Assessment Source Dataset. Viewed 05 July 2017, http://data.bioregionalassessments.gov.au/dataset/d82336ac-21e5-4146-88ec-51659f2524a7.

The dataset presents a list of laboratories set up in the humanities, digital humanities, and media studies within universities across the world in 1983-2018. The data are collected and organized in an interactive map designed in the digital StoryMapJS tool, creating a valuable visible representation of the laboratory concept from a geographical and historical perspective. Based on the interactive map, I analyze the history of the laboratory in the humanities within a global context from the 1980s to 2018. The dataset includes 214 laboratories.

Data collection

I identified laboratories by using different resources such as universities’ websites, articles, and research projects. Besides, I sent a questionnaire to the most relevant networks in October 2018 to identify even more labs created in (digital) humanities and media studies at universities.

Data organization

I collected data about each lab based on its website and other resources. I extracted the following data: year established, year ended (if applicable), lab’s name, university, city, country, affiliation and location (if provided), disciplines and keywords (based on labs’ statements and projects and aiming to situate a lab), selected projects (if provided), purpose (a short quotation of a lab’s statement published on its website), website, and geographical latitude and longitude. I organized all the data in chronological order according to year established in Google Sheets. Next, I used StoryMapJS, a free tool designed by the Northwestern University’s Knight Lab, to map my data.

Spatial coverage index compiled by East View Geospatial of set "Ukraine Cartographic Group (Maps)". Source data from UCG (publisher). Type: Thematic - Political and Administrative. Scale: Varies. Region: World.

The Google Maps dataset is ideal for getting extensive information on businesses anywhere in the world. Easily filter by location, business type, and other factors to get the exact data you need. The Google Maps dataset includes all major data points: timestamp, name, category, address, description, open website, phone number, open_hours, open_hours_updated, reviews_count, rating, main_image, reviews, url, lat, lon, place_id, country, and more.

Abstract

This dataset was derived by the Bioregional Assessment Programme from the

GABATLAS - Cadna-Owie-Hooray Aquifer and Equivalents - Thickness and Extent (GUID: bc55589c-1c6f-47ba-a1ac-f81b0151c630), GABATLAS - Adori-Springbok Aquifer - Thickness and Extent (GUID: 6df0da09-5e9f-4656-b2f8-b87e5dbfde92), GABATLAS - Birkhead-Walloon Aquitard - Thickness and Extent (GUID: a5912292-10cd-42e2-aefe-49aae2eead4b), GABATLAS - Hutton Aquifer and Equivalents - Thickness and Extent (GUID: 97def8b6-2c88-41cf-b77a-3433dfdc4470), GABATLAS - Evergreen-Poolowanna Aquitard and Equivalents - Thickness and Extent (GUID: b9c0d451-e7f0-4810-95eb-51fa6d9f552b), GABATLAS - Precipice Aquifer & Equivalents - Thickness and Extent (GUID: aeeead0e-9637-4f6f-b870-df4bc66dc81c) and GABATLAS - Rolling Downs Aquitard - Thickness and Extent (GUID: 0c4f0e0e-2d1d-4dee-9a57-36ecdd1d9a1f) datasets. You can find a link to the parent datasets in the Lineage Field in this metadata statement. The History Field in this metadata statement describes how this dataset was derived.

Cartographic masks for map products COO 113, used to enable clear annotation in report maps by masking unwanted features and the area outside of the Great Artesian Basin from.

Purpose

To enable clear annotation in report maps for product COO 1.1.3, by masking unwanted features and the area outside of the Great Artesian Basin from.

Dataset History

Hydrogeology formation polygon extents from the GABATLAS - Cadna-owie-Hooray Aquifer and Equivalents - Thickness and Extent (GUID: bc55589c-1c6f-47ba-a1ac-f81b0151c630), GABATLAS - Adori-Springbok Aquifer - Thickness and Extent (GUID: 6df0da09-5e9f-4656-b2f8-b87e5dbfde92), GABATLAS - Birkhead-Walloon Aquitard - Thickness and Extent (GUID: a5912292-10cd-42e2-aefe-49aae2eead4b), GABATLAS - Hutton Aquifer and Equivalents - Thickness and Extent (GUID: 97def8b6-2c88-41cf-b77a-3433dfdc4470), GABATLAS - Evergreen-Poolowanna Aquitard and Equivalents - Thickness and Extent (GUID: b9c0d451-e7f0-4810-95eb-51fa6d9f552b), GABATLAS - Precipice Aquifer & Equivalents - Thickness and Extent (GUID: aeeead0e-9637-4f6f-b870-df4bc66dc81c) and GABATLAS - Rolling Downs Aquitard - Thickness and Extent (GUID: 0c4f0e0e-2d1d-4dee-9a57-36ecdd1d9a1f) datasets were merged together. This merged output was then clipped from a rectangular polygon with an arbitrary extent of:

Degrees:

North - 4.59227640453251

West - 115.709908155637

East - 172.674204635436

South - -50.431469899816

Annotation masks were created using the 'Features Outline Masks (Cartography)' tool on annotation layers (labels) within ArcMap.

Dataset Citation

Bioregional Assessment Programme (2015) Cartographic masks for map products COO 113. Bioregional Assessment Derived Dataset. Viewed 27 November 2017, http://data.bioregionalassessments.gov.au/dataset/3222f91a-25c4-4cc8-a418-8425485d87d0.

Dataset Ancestors

• Derived From GABATLAS - Adori-Springbok Aquifer - Thickness and Extent

• Derived From GABATLAS - Evergreen-Poolowanna Aquitard and Equivalents - Thickness and Extent

• Derived From GABATLAS - Birkhead-Walloon Aquitard - Thickness and Extent

• Derived From GABATLAS - Precipice Aquifer & Equivalents - Thickness and Extent

• Derived From GABATLAS - Rolling Downs Aquitard - Thickness and Extent

• Derived From GABATLAS - Cadna-owie-Hooray Aquifer and Equivalents - Thickness and Extent

• Derived From GABATLAS - Hutton Aquifer and Equivalents - Thickness and Extent

Satellite images are becoming more accurate and are considered realistic as opposed to more abstract road maps. There is no consensus on the importance of satellite images in the process of memorizing a route from a map image. Especially if the route is displayed on the internet using dynamic (animated) cartographic visualization. We know that the animation is graphically attractive, but it causes some perceptual problems. This study examines the influence of the satellite image on the effectiveness and efficiency of memorizing the animated route. The routes of three difficulty levels, based on satellite and road background, are compared. The results show that the satellite background is not a significant factor influencing the efficiency and effectiveness of route memorizing. Recordings of the eye movement confirm this. The study reveals that there are intergroup differences in participants' visual behavior.