This geologic map database is a reproduction of U.S. Geological Survey Miscellaneous Investigations Map I–2362: “Geologic Map and Structure Sections of the Clear Lake Volcanics, Northern California” (Hearn, Donnelly-Nolan, and Goff, 1995). The database consists of a geologic map, three structural cross sections and a table of petrographic data for each map unit by mineral type, abundance, and size. The Clear Lake Volcanics are in the California Coast Ranges about 150 km north of San Francisco. This Quaternary volcanic field has erupted intermittently since 2.1 million years ago. This volcanic field is considered a high-threat volcanic system (Ewert and others, 2005). The adjacent Geysers geothermal field, the largest power-producing geothermal field in the world, is powered by the magmatic heat source for the volcanic field. The geology of parts of the area underlain by the Cache Formation is based on mapping by Rymer (1981); the geology of parts of the areas underlain by the Sonoma Volcanics, Franciscan assemblage, and Great Valley sequence is based on mapping by McLaughlin (1978). Volcanic compositional map units are basalt, basaltic andesite, andesite, dacite, rhyodacite, and rhyolite, based on SiO2 content. Most ages are potassium-argon (K/Ar) ages determined for whole-rock samples and mineral separates by Donnelly-Nolan and others (1981), unless otherwise noted. A few ages are carbon-14 ages or were estimated from geologic relationships. Magnetic polarities are from Mankinen and others (1978; 1981) or were determined in the field by B.C. Hearn, Jr., using a portable fluxgate magnetometer. Thickness for most units is estimated from topographic relief except where drill-hole data were available. This database does not reproduce all elements of the original publication. Omissions include the chart and figures showing erupted volumes of different lava types through time, and the chart and diagram for the correlation of map units. Users of this database are highly encouraged to cross reference this database with the original publication.

Blank?Did you ever make a sweet map with loads of layers and data and the whole of it was so information-dense that the basemap behind it all was just unnecessary noise? Me too. Nothing against basemaps—they serve a noble purpose of providing spatial context to whatever phenomenon you are mapping. But sometimes your data is sufficient to make a basemap superfluous. Here is a little hack that you can use. A basemap to end all basemaps, as it were. Tile after tile of lightning-fast lightweight nothingness. It's like the Seinfeld of basemaps. A basemap about nothing.HELLLLLLLLLOOOOOOOOOOO! LA LA LAAAAA!Here is a picture of this map:Pretty nice, right? Ok, if you want a different color no problem. Here is a link to the vector tile style editor, which will let you paint this big blank canvas whatever color you like: https://developers.arcgis.com/vector-tile-style-editor/e9cacfd187904614884c16aa52a21cac/layersHappy Minimalist Mapping! John Nelson

These data provide an accurate high-resolution shoreline compiled from imagery of Galveston Bay, Clear Lake to La Porte, TX . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object Attribute Source Table (C-COAST)' was developed to conform the attribution of various sources of shoreline data into one attribution catalog. C-COAST is not a recognized standard, but was influenced by the International Hydrographic Organization's S-57 Object-Attribute standard so the data would be more accurately translated into S-57. This resource is a member of https://www.fisheries.noaa.gov/inport/item/39808

International boundaries provided by United Nations Clear Map. The United Nations Clear Map (hereinafter “Clear Map”) is a background reference web mapping service produced to facilitate “the issuance of any map at any duty station, including dissemination via public electronic networks such as Internet” and “to ensure that maps meet publication standards and that they are not in contravention of existing United Nations policies” in accordance with the in the Administrative Instruction on “Regulations for the Control and Limitation of Documentation – Guidelines for the Publication of Maps” of 20 January 1997 (http://undocs.org/ST/AI/189/Add.25/Rev.1) Clear Map is created for the use of the United Nations Secretariat and community. All departments, offices and regional commissions of the United Nations Secretariat including offices away from Headquarters using Clear Map remain bound to the instructions as contained in the Administrative Instruction and should therefore seek clearance from the UN Geospatial Information Section (formerly Cartographic Section) prior to the issuance of their thematic maps using Clear Map as background reference. Disclaimers: The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Credits (Attribution) Produced by: United Nations Geospatial Contributor: UNGIS, UNGSC, Field Missions CONTACT US: Your feedback is appreciated and should be sent directly to: Email:Clearmap@un.org / gis@un.org (UNCLASSIFIED) © UNITED NATIONS 2018 More information on the United Nations Clear Map website at https://geoportal.dfs.un.org/arcgis/sharing/rest/content/items/541557fd0d4d42efb24449be614e6887/data

The statewide New Hampshire Timber Clear Cut Inventory identifies patches of clear cut forest land, based on screen digitizing features visible in Landsat Thematic Mapper (TM) and SPOT panchromatic satellite imagery.Development of the New Hampshire Timber Clear Cut Inventory was made possible by financial support from the USDA Forest Service, the NH Department of Resources and Economic Development, and the NH Office of State Planning. Please cite as "New Hampshire GRANIT. 1995. New Hampshire Timber Clear Cut Inventory. New Hampshire GRANIT, Durham, NH."

The Clear-sky Reflectance Map product describes the reflection that would be registered by the solar MTG channels in cloud free conditions, using the actual satellite position and including (possible) atmospheric effects.

This map depicts example algae sampling and experiment sites at the lake at Kern Point in Sequoia National Park. Sites including photos and descriptions of activities that may be part of a typical algae survey performed by the Sierra Nevada Network Inventory and Monitoring Program. Sites represent examples of activities that may be part of an algae survey and are not intended to represent actual sites used in real sampling or experiments. Not all photos included in these data points were taken at Kern Point.Map intended for use in: Monroe M and Eddy A. 2020. Clear Waters: Join a Field Crew to Track Change in Sierra Nevada Lakes. Found at https://irma.nps.gov/DataStore/Reference/Profile/2271901. National Park Service, Fort Collins, CO.For additional information, please see: Heard AM and Others. 2012. Sierra Nevada Network Lake Monitoring Protocol: Protocol Narrative. Natural Resource Report. NPS/SIEN/NRR—2012/551. National Park Service. Fort Collins, Colorado (https://irma.nps.gov/DataStore/Reference/Profile/2186803)

SafeGraph Places provides baseline information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

SafeGraph Places is a point of interest (POI) data offering with varying coverage depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

SafeGraph provides clean and accurate geospatial datasets on 51M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation. Easily ingest this data to power your map products today.

This series of 1:250 000 scale colour maps covers the provincial extent of Alberta and is comprised of 50 maps that are individually named using the National Topographic System (NTS) map sheet identifier. These maps display: Alberta Township System (ATS), contours (50m intervals), major hydrographic features, municipalities, major roads, railways, and select geo-administrative features (parks, reserves, etc.).

The Chicago Park District issues swim advisories at beaches along Chicago's Lake Michigan lakefront based on E. coli levels. This map shows predicted E. coli levels -- with bubble size corresponding to predicted level -- and whether the predicted E. coli level was at least 235 Colony Forming Units (CFU) per 100 ml of water (red bubbles).

This map updates daily and its predictions depend on data from https://data.cityofchicago.org/Parks-Recreation/Beach-Lab-Data/2ivx-z93u. It will show no predictions from midnight until the new day's predictions have been generated.

The Digital Geologic-GIS Map of the Clear Creek Mountain Quadrangle, Utah is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (clcm_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (clcm_geology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (zion_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (zion_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (clcm_geology_metadata_faq.pdf). Please read the zion_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Utah Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (clcm_geology_metadata.txt or clcm_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

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 GAL_210, used for clear annotation and masking unwanted features from report maps. Dataset History A shapefile was created for the use of masking data to highlight text. Method: * A new polygon shapefile was created with no contentShow full descriptionAbstract 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 GAL_210, used for clear annotation and masking unwanted features from report maps. Dataset History A shapefile was created for the use of masking data to highlight text. Method: * A new polygon shapefile was created with no content * The shapefile was then populated in an ArcMap editing session by digitizing polygons which surround text. * ArcMAP's Advanced Drawing Option was then used to mask data behind text. Dataset Citation Bioregional Assessment Programme (2015) Cartographic masks for map products GAL210. Bioregional Assessment Source Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/4bb5f4f2-bae9-44da-a5d7-398622e164df.

Abstract

This dataset was derived by the Bioregional Assessment Programme. The parent dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This dataset contains cartographic mask polygon shapefiles for maps created in COO 230. These polygons are used for clear annotation and to mask-out unwanted features in report maps.

Dataset History

Polygon mask features were created using the 'Features Outline Masks (Cartography)' tool (ArcMap) on annotation layers in maps for product COO 2.3.

For this dataset, masks were created from the annotations created from the following layer (dataset):

1. PopulatedPlaces Feature Class from the "GEODATA TOPO 250K Series 3" dataset (GUID: a0650f18-518a-4b99-a553-44f82f28bb5f).

Masks polygons were also created for clear visualisation of graticules and state annotation graphics, as well as other cartographic labels and graphics in the same maps.

Dataset Citation

Bioregional Assessment Programme (2016) Cartographic masks for map products COO 230. Bioregional Assessment Derived Dataset. Viewed 27 November 2017, http://data.bioregionalassessments.gov.au/dataset/a969c477-a943-4ad2-8964-b521ccdc3d19.

Dataset Ancestors

• Derived From GEODATA TOPO 250K Series 3

Abstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This dataset contains a cartographic mask polygon shapefiles for maps created in COO product 1.5. These polygons are used for clear annotation and to mask-out unwanted features in report maps.Show full descriptionAbstract The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement. This dataset contains a cartographic mask polygon shapefiles for maps created in COO product 1.5. These polygons are used for clear annotation and to mask-out unwanted features in report maps. Purpose For cartographic use only Dataset History Polygon mask features were created using the 'Features Outline Masks (Cartography)' tool (ArcMap) on annotation layers in maps for product CLM 1.2. For this dataset, masks were created from the annotations created from the following layer (dataset): PopulatedPlaces Feature Class from the "GEODATA TOPO 250K Series 3" dataset (GUID: a0650f18-518a-4b99-a553-44f82f28bb5f). Masks polygons were also created for clear visualisation of graticules and state annotation graphics in the same maps. Dataset Citation Bioregional Assessment Programme (XXXX) Cartographic masks for map products COO 150. Bioregional Assessment Derived Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/43131c46-d0d8-44de-a272-9487c1cd5f2b. Dataset Ancestors Derived From GEODATA TOPO 250K Series 3

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 114, 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 Bioregion…Show full descriptionAbstract 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 114, 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 114. Bioregional Assessment Source Dataset. Viewed 05 July 2017, http://data.bioregionalassessments.gov.au/dataset/f4263e67-6621-4023-b7ec-4f4f7f6e9dda.

Leading up to the 2020 Convention on Biological Diversity there is momentum around setting bold conservation targets. Yet it remains unclear how much of Earth's land area remains without significant human influence and where this land is located. We compare four recent global maps of human influences across Earth's land, Anthromes, Global Human Modification, Human Footprint, and Low Impact Areas, to answer these questions. Despite using various methodologies and data, these different spatial assessments independently estimate similar percentages of the Earth's terrestrial surface as having very low (20-34%) and low (48-56%) human influence. Three out of four spatial assessments agree on 46% of the non-permanent ice- or snow-covered land as having low human influence. However, much of the very low and low influence portions of the planet are comprised of cold (e.g., boreal forests, montane grasslands and tundra) or arid (e.g., deserts) landscapes. Only four biomes (boreal forests, deserts, temperate coniferous forests and tundra) have a majority of datasets agreeing that at least half of their area has very low human influence. More concerning, <1% of temperate grasslands, tropical coniferous forests and tropical dry forests have very low human influence across most datasets, and tropical grasslands, mangroves and montane grasslands also have <1% land identified as very low influence across all datasets. These findings suggest that about half of Earth's terrestrial surface has relatively low human influence and offers opportunities for proactive conservation actions to retain the last intact ecosystems on the planet. However, though the relative abundance of ecosystem areas with low human influence varies widely by biome, conserving these last intact areas should be a high priority before they are completely lost.

Here is a direct link to a pristine ArcGIS Online web map with this basemap all loaded and ready to go; a blank canvas!Blank?Did you ever make a sweet map with loads of layers and data and the whole of it was so information-dense that the basemap behind it all was just unnecessary noise? Me too. Nothing against basemaps—they serve a noble purpose of providing spatial context to whatever phenomenon you are mapping. But sometimes your data is sufficient to make a basemap superfluous. Here is a little hack that you can use. A basemap to end all basemaps, as it were. Tile after tile of lightning-fast lightweight nothingness. It's like the Seinfeld of basemaps. A basemap about nothing.HELLLLLLLLLOOOOOOOOOOO! LA LA LAAAAA!Here is a picture of this basemap:Pretty nice, right? Ok, if you want a different color no problem. Here is a link to the vector tile style editor, which will let you paint this big blank canvas whatever color you like: https://developers.arcgis.com/vector-tile-style-editor/e3ac9818c0c344538840e51e9f33f6cc/layersHappy Minimalist Mapping! John Nelson

See Methods in publication.

The depth grids show the depth of flooding on the Clear Fork Mohican River near Bellville, Ohio on local map backgrounds, based on stages of 9.0 ft to 17.0 ft at the USGS streamgage, Clear Fork Mohican River at Bellville, Ohio, 03131982.