Sentinel-2 Level-1C imagery with on-the-fly renderings for visualization. This imagery layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.Sentinel-2 imagery can be applied across a number of industries, scientific disciplines, and management practices. Some applications include, but are not limited to, land cover and environmental monitoring, climate change, deforestation, disaster and emergency management, national security, plant health and precision agriculture, forest monitoring, watershed analysis and runoff predictions, land-use planning, tracking urban expansion, highlighting burned areas and estimating fire severity.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean Sea Temporal CoverageThis layer includes a rolling collection of Sentinel-2 imagery acquired within the past 14 months.This layer is updated daily with new imagery.The revisit time for each point on Earth is every 5 days.The number of images available will vary depending on location. Product LevelThis service provides Level-1C Top of Atmosphere imagery.Alternatively, Sentinel-2 Level-2A is also available. Image Selection/FilteringThe most recent and cloud free images are displayed by default.Any image available within the past 14 months can be displayed via custom filtering.Filtering can be done based on attributes such as Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More… Visual RenderingDefault rendering is Natural Color (bands 4,3,2) with Dynamic Range Adjustment (DRA).The DRA version of each layer enables visualization of the full dynamic range of the images.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Bathymetric with DRA, Color-Infrared with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn Ratio, NDVI Colormap. Multispectral BandsBandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available. NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request. Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS, or alternatively access EarthExplorer or the Copernicus Data Space Ecosystem to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

The Surface Management Agency (SMA) Geographic Information System (GIS) dataset depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. The SMA feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency’s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details.

The SMA Withdrawals feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA Withdrawal is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SMA Withdrawals will include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency’s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details.

Road edges are defined as the edge of the improved surface including the improved shoulder but do not include the unimproved shoulder, only the travel part of the road. The road network is compiled to include all open intersections. Features do not overlap sidewalks, but have the sidewalk area cut out of the road polygons. Overlapping features are acceptable if one of the features is hidden. Road: A generally named thoroughfare, that is usually paved and can be public or private. Unimproved thoroughfares are excluded. Road polygons are formed by a combination of road edge, curb, sidewalk, street intersection closure line, and map sheet edge. Paved Median Island: Perimeter of non-traffic paved areas that separate traffic lanes in opposing directions. Unpaved Median Island: Perimeter of non-traffic grassy, unpaved areas that separate traffic lanes in opposing directions. Paved Traffic Island: Perimeter of non-traffic concrete areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features do not overlap sidewalks. Unpaved Traffic Island: Perimeter of non-traffic unpaved, grassy areas in the middle of streets designed to segregate traffic flow. This does not include linear barriers, e.g., Jersey barriers, walls or guardrails, or point barriers, such as impact attenuators. Features do not overlap sidewalks. Alley: Perimeter of alleys first plotted photogrammetrically from other indicators such as building footprints, fence lines, curb lines, walls, paved or unpaved drives, and map sheet edge. Alley polygons are closed along the lines where they intersect with road polygons. Paved Drive: A paved driveway for a building or entranceway for a parking lot. Driveways are neither streets nor alleys, but provide access to public facilities, such as a drive to a monument, museum, hotel, large estate, sports field or golf course, grounds of the U.S. Capitol, etc. If a driveway is less than 200 feet and leads to a parking lot, the entire paved area is captured as Parking Lot. Driveways are photogrammetrically compiled as polygons and not compiled from individual vectors on different levels. Parking Lot: Generally paved surfaces used for cars to park on. Paved drives usually form entrances to these features, if the drive is more than 200 feet. If the driveway is less than 200 feet leading into the parking lot, the entire paved area is captured as Parking Lot. Parking lots sharing a common boundary with linear features must have the common segment captured once, but coded as both polygon and line. Small parking areas, where individuals park their cars in the middle of a block off a public alley, are not captured as parking lots. These are either public space (e.g., alleys) or private space where owners permit parking to occur. Intersection: A location where more than one road comes together. For standard cross streets, intersection polygons are bounded by curbs and four closure lines at street intersection crosswalks (outer line) or placed arbitrarily where crosswalks could logically be placed. For "T" intersections, the polygons are bounded by curbs and three such closure lines. Complex intersections can have more closure lines. Entire traffic circles are coded as intersections. Hidden Road: A section of a road that passes underneath a bridge or overpass and is not visible in an aerial photograph, but the location can be interpreted based on the road on either side of the bridge. Hidden Median: A road median that exists underneath a bridge or overpass and is not fully visible in an aerial photograph, but the location can be interpreted based on the information visible on either side of the bridge.

Soils and soil moisture greatly influence the water cycle and have impacts on runoff, flooding and agriculture. Soil type and soil particle composition (sand, clay, silt) affect soil moisture and the ability of the soil to retain water. Soil moisture is also affected by levels of evaporation and plant transpiration, potentially leading to near dryness and eventual drought.Measuring and monitoring soil moisture can ensure the fitness of your crops and help predict or prepare for flash floods and drought. The GLDAS soil moisture data is useful for modeling these scenarios and others, but only at global scales. Dataset SummaryThe GLDAS Soil Moisture layer is a time-enabled image service that shows average monthly soil moisture from 2000 to the present at four different depth levels. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. The GLDAS soil moisture data is useful for modeling, but only at global scales. Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.Depth: This layer has four depth levels. By default they are summed, but you can view each using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter. It is also possible to toggle between depth layers using raster functions, accessed through the Image Display tab.Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.This layer has query, identify, and export image services available. This layer is part of a larger collection of earth observation maps that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the earth observation layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about earth observations layers and the Living Atlas of the World. Follow the Living Atlas on GeoNet.

This layer includes Landsat GLS multispectral imagery for use in visualization and analysis. This layer is time enabled and includes a number band combinations and indices rendered on demand. The layer includes Landsat 7 ETM+, Landsat 5 TM, and Landsat 4 imagery at 30m, and includes Landsat MSS imagery at 60m.Geographic CoverageWorld-wide imagery coverage.Temporal CoverageThis imagery layer includes data from epochs 2010, 2005, 2000, 1990 and 1975. Analysis ReadyThis imagery layer is analysis ready with Top of Atmosphere (TOA) correction applied.The TOA reflectance values (ranging 0 – 1 by default) are scaled using a range of 0 – 10,000.The scale is equivalent to other TOA reflectance products, including those provided by the USGS.Image Selection/FilteringNewer images are displayed by default on top.The entire archive is accessible via custom filtering.A number of fields are available for filtering, including Acquisition Date, Estimated Cloud Cover, and Product ID.By setting the filter to Best is lesser than QQQQ one can control to see the best N scenes, where QQQQ=N*1million.NOTE: Turning off all filters, and loading the entire archive, may affect performance.Visual RenderingDefault layer is Agriculture (bands 5,4,1) with Dynamic Range Adjustment (DRA). Brighter green indicates more vigorous vegetation.The DRA version of each layer enables visualization of the full dynamic range of the images.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions can be created.Similar Imagery Layers are also available: Panchromatic and Pansharpened.Multispectral Bands

Band

Wavelength (µm)

Landsat 7 ETM+

Landsat 4-5 TM

Landsat MSS

1

0.45 – 0.52

0.45 – 0.52

N/A

2

0.52 – 0.60

0.52 – 0.60

0.5 – 0.6

3

0.63 – 0.69

0.63 – 0.69

0.6 – 0.7

4

0.77 – 0.90

0.76 – 0.90

0.7 – 0.8

5

1.55 – 1.75

1.55 – 1.75

0.8 – 1.1

6

2.09 – 2.35

2.08 – 2.35

N/A

Other Layer Usage Notes...Overviews exist with a spatial resolution of 300m and are updated weekly based on the best and latest imagery available at that time.To work with individual source images at all scales, either use the ‘Lock Raster’ functionality or add a query filter to restrict the display to a specified image or group of images.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.Images can be exported up to a maximum of 2,000 columns x 2,000 rows per request.This ArcGIS Server dynamic Imagery Layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image Services API.WCS and WMS compatibility means this imagery can be consumed as WCS or WMS services.Landsat Web App via Unlock Earth's Secrets.Data SourceLandsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted by the Amazon Web Services as part of their Public Data Sets program. Users can access full scenes from Landsat on AWS, or alternatively access LandsatLook to review and download full scenes from the complete USGS archive.The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit GLS.

The Utah Bikeways dataset provides a detailed representation of planned on-street and pathway bikeway features in the state and serves as a comprehensive resource for understanding the state's cycling infrastructure. The data includes various attributes such as the name of the bikeway, the city and county it traverses, and specific details about the facility type (e.g., dedicated bike lanes, shared-use paths). It also includes an estimated Level of Traffic Stress (LTS) score and the source of the data.The Utah Planned Bikeways data is intended for planning, analysis, and visualization of planned cycling routes and infrastructure at various scales within Utah. Users should be aware that while efforts are made to keep the data current, recent changes in infrastructure are not immediately reflected. Data updates are sourced through periodic coordination between transportation agencies (UDOT and Utah's four MPOs), local government GIS and active transportation contacts, and through user submissions with the Utah Bikeways app. For current/existing features, users should use the Utah Bikeways dataset.The Planned Bikeways data is maintained within two separate statewide editing layers stewarded by UGRC -- Roads and Trails and Pathways. This more user-friendly dataset is derived by UGRC using a python script that combines bike facilities in the two editing layers. It merges and formats the data into a single schema, determines the best bike feature, and which side of the road the best feature is on. The script also calculates a Level of Traffic Stress metric that represents the amount of discomfort people feel when they ride their bicycles near traffic. Finally, the data is split into existing and planned features, for use in the Utah Bikeways app.

Connecticut Roads and Trails is 1:24,000-scale base map data. It depicts the location of all roads and trails published on the USGS topographic quadrangle maps. For base map purposes, use this layer with other 1:24,000-scale base map data such as Hydrography, Railroads, Airports, and Towns. The Roads and Trails layer includes information within Connecticut and is derived from the Roads and Trails Master layer, which includes all road and trail features depicted on all of the U.S. Geological Survey (USGS) 7.5 minute topographic quadrangle maps that cover the State of Connecticut. This layer may be used as a possible data source for other 1:24,000-scale layers having features that should coincide with the roads and trails on the USGS topographic quadrangle maps. Not intended for maps printed at map scales greater or more detailed than 1:24,000 scale (1 inch = 2,000 feet.)

Connecticut Roads and Trails is a 1:24,000-scale, feature-based layer that includes road and trail features on the U.S. Geological Survey (USGS) 7.5 minute topographic quadrangle maps for the State of Connecticut. This layer only includes features located in Connecticut. The layer is based on information from USGS topographic quadrangle maps published between 1969 and 1984 and does not represent the road network in Connecticut at any one particular point in time. The layer does not depict current conditions and excludes many roads that have been built, modified, or removed since the time these topographic quadrangle maps were published. The layer includes Interstate highways, US routes, state routes, local roads, unpaved roads, traffic circles, bridges, cul-de-sacs, trails, etc. It does not include route number, street name, house address, traffic direction, or traffic volume information for these features. Nor does it represent a complete or current network of hiking trails. Features are linear and represent road centerlines. Attribute information is comprised of codes to cartographically represent (symbolize) road and trail features on a map. This layer was originally published in 1994. The 2005 edition includes the same road features published in 1994, but the attribute information has been slightly modified and made easier to use.

Description based on the metadata provided by the WMDs.NWFWMD: Watershed Delineation for NWFWMD. Custodian - Danny Layfield.The Northwest Florida Water Management District maintains the following GIS Data Dictionary as a public service, by granting the public and government agencies access to the Districts GIS data.Data is provided on an "as is" basis. In no event will the District or its staff be liable for any direct, indirect, incidental, special, consequential, or other damages, including loss of profit, arising out of the use of these data even if the District has been advised of the possibility of such damages.The spatial datasets are provided as zipped (.zip) ESRI shapefiles or geodatabases. The data are provided in UTM Zone 16N / NAD 83, map units metershttp://www.nwfwmd.state.fl.us/data-publications/gis-mapping/gis-data-directorySRWMD: Hydrography basin major. USGS24"SBAS" was orginally created by USGS as part of a cooperative effort between the USGS and DEP to create a statewide basin or watershed map. SRWMD has modified and added some watersheds because of local knowledge and needs of the District. A number of items have also been added to the coverage. Surfacewater watersheds are topographic land features which contain a unique hydrologic area of surface drainage. Suwannee River Water Management has choosen to call this a watershed map instead of a basin map as previously called. These spatial data sets provide SRWMD and other government agencies with a consolidated resource for watershed information at various levels of geographic extent. The data sets are intended to support watershed analysis, planning, permitting, regulatory, and other functions at SRWMD. They have been edited and modified by the District to reflect better information available at the regional level, and to better meet the specific needs of the GIS users at SRWMD. A guide to the Watershed coverage is available from SRWMD at md_lib/basins/items.doc. A spreadsheet that expains the attribution of both the polygon and arc attribute tables is also located at md_lib/basins/sbas_items.doc. Additional information about the original watershed maps created by USGS is available from the following sources: U.S. Geological Survey, 1994. Metadata for Hydrologic units maps of the Conterminous United States, 1:250,000-scale (nominal), ARC/INFO format. < http://water.usgs.gov/lookup/getspatial?/huc250k> U.S. Geological Survey, 1990. Land Use and Land Cover Digital Data from 1:250,000- and 1:100,000-Scale Maps. Data Users Guide 4, 33 pp, Reston, Virginia. U.S. Environmental Protection Agency, 1996. Metadata for Hydrologic Unit Boundaries of the Conterminous United States, 1:250,000-scale (nominal), ARC/INFO Format, < http://www.epa.gov/nsdi/projects/catunit.htm>Note: This data was created by the Suwannee River Water Management District (SRWMD) to be used for planning purposes only. SRWMD shall not be held liable for any injury or damage caused by the use of data distributed as a public records request regardless of their use or application. SRWMD does not guarantee the accuracy, or suitability for any use of these data, and no warranty is expressed or implied. In no event will the SRWMD, its staff, or the contributing agencies be liable for any direct, indirect, incidental, special, consequential or other damages, including loss of profit, arising from the use of these data, even if the District has been advised of the possibility of such damages. Users of this data should therefore do so at their own risk. For more information please contact the SRWMD at 386-362-1001.http://www.srwmd.state.fl.us/index.aspx?NID=319SJRWMD: This coverage was originally created in September 2000 by GIS staff in the Resource Management Dept. It was created in Arc/Info, using the SJRWMD surface water drainage basins layer as a guideline. The swbasins were combined and shifted in places, to delineate ecology based areas for regulatory mitigation review. The changes came from a Board-appointed Advisory Committee and were approved by the Board and adopted by rule.The coverage corresponds to the basin boundaries found in the ERP Applicant's Handbook in Figure 12.2.8-1 and Appendix M. This is a special layer created specifically for regulatory purposes; it is distinct from the standard SJRWMD Surface Water Drainage Basins Layer. This layer mitig basin reg is to delineate ecologically based areas for regulatory mitigation review. This data reflects all Mitigation Basin changes approved by the Governing Board and effective as of November 5, 2008.For more information contact St. Johns River Water Management District 386-312-2314.http://floridaswater.com/gisdevelopment/docs/themes.htmlSWFWMD: This layer illustrates the extent of Comprehensive Watershed Management (CWM) watershed boundaries in the Southwest Florida Water Management District. This layer should be used for cartographic and resource management purposes.Watershed boundaries used in the Comprehensive Watershed Management (CWM) program. These boundaries were derived from the DBASINS coverage.These data were not collected under the supervision of a licensed Professional Surveyor and Mapper. Use of these data requires a general understanding of GIS.The data are being provided on an 'as is' basis. The District specifically disclaims any warranty, expressed or implied, including, but not limited to, the implied warranties or merchantability and fitness for a particular use. The entire risk as to quality and performance is with the user. In no event will the District or its staff be liable for any direct, indirect, incidental, special, consequential, or other damages, including loss of profit, arising out of the use of these data even if the District has been advised of the possibility of such damages. All data are intended for resource management use.For more information contact the Southwest Florida Water Management District (352) 796-7211. https://www.swfwmd.state.fl.us/data/gis/layer_library/category/physical_sparseSFWMD: Recreation of Figure 4.4.1 in Volume IV Basis of Review. 1989 Basins and Cumulative Impact Basins (fka Watersheds).For more information contact the South Florida Water Management District (561) 686-8800.http://www.sfwmd.gov/gisapps/sfwmdxwebdc/dataview.asp?

This crash dataset does include crashes from 2023 up until the end of May that have been reviewed and loaded into the Maine DOT Asset Warehouse. This crash dataset is static and was put together as an example showing the clustering functionality in ArcGIS Online. In addition the dataset was designed with columns that include data items at the Unit and Persons levels of a crash. The feature layer visualization by default will show the crashes aggregated by the predominant crash type along the corridor. The aggregation settings can be toggled off if desired and crashes can be viewed by the type of crash. Both the aggregation and standard Feature Layer configurations do include popup settings that have been configured.As mentioned above, the Feature Layer itself has been configured to include a standard unique value renderer based on Crash Type and the layer also includes clustering aggregation configurations that could be toggled on or off if the user were to add this layer to a new ArcGIS Online Map. Clustering and aggregation options in ArcGIS Online provide functionality that is not yet available in the latest version of ArcGIS Pro (<=3.1). This additional configuration includes how to show the popup content for the cluster of crashes. Users interested in learning more about clustering and aggregation in ArcGIS Online and some more advanced options should see the following ESRI article (https://www.esri.com/arcgis-blog/products/arcgis-online/mapping/summarize-and-explore-point-clusters-with-arcade-in-popups/).Popups have been configured for both the clusters and the individual crashes. The individual crashes themselves do include multiple tables within a single text element. The bottom table does include data items that pertain to at a maximum of three units for a crash. If a crash includes just one unit then this bottom table will include only 2 columns. For each additional unit involved in a crash an additional column will appear listing out those data items that pertain to that unit up to a maximum of 3 units. There are crashes that do include more than 3 units and information for these additional units is not currently included in the dataset at the moment. The crash data items available in this Feature Layer representation includes many of the same data items from the Crash Layer (10 Years) that are available for use in Maine DOT's Public Map Viewer Application that can be accessed from the following link(https://www.maine.gov/mdot/mapviewer/?added=Crashes%20-%2010%20Years). However this crash data includes data items that are not yet available in other GIS Crash Departments used in visualizations by the department currently. These additional data items can be aggregated using other presentation types such as a Chart, but could also be filtered in the map. Users should refer to the unit count associated to each crash and be aware when a units information may not be visible in those situations where there are four or more units involved in a crash.

Mass-wasting events that displace water, whether they initiate from underwater sources (submarine landslides) or subaerial sources (subaerial-to-submarine landslides), have the potential to cause tsunami waves that can pose a significant threat to human life and infrastructure in coastal areas (for example towns, cruise ships, bridges, oil platforms, and communication lines). Sheltered inlets and narrow bays can be locations of especially high risk as they often have higher human populations, and the effects of water displacement from moving sediment can be amplified as compared to the effects from similarly sized mass movements in open water. In landscapes undergoing deglaciation, such as the fjords and mountain slopes adjacent to tidewater glaciers found in Southeast Alaska, glacial retreat and permafrost decay can destabilize rock slopes and increase landslide potential. Establishing and maintaining inventories of subaerial and submarine landslides in such environments is critical for identifying the magnitude and frequency of past events, as well as for assessing areas that may be susceptible to failures in the future. To maintain landslide inventories, multi-temporal surveys are needed. High-resolution digital elevation models (DEM) and aerial imagery can be used to establish and maintain subaerial landslide inventories, but repeat bathymetric surveys to detect submarine landslides are generally less available than their terrestrial counterparts. However, existing bathymetry can be used to establish a spatial inventory of landslides on the seafloor to provide a baseline for understanding the magnitude of past events and for locating areas of high submarine landslide susceptibility. These data can then be used to address how future failures and the tsunamis that they could trigger could impact surrounding areas. Here, we present an inventory of mapped landslide features in Glacier Bay, Alaska that includes landslide source areas, deposits, and scarps. This data release contains geographic information system (GIS) polygons and polylines for these mapped features; the underlying digital elevation model (DEM) raster compiled from available bathymetry from the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS); a slope map created from the compiled DEM; ¬and a derivative topographic openness map used to help identify the landslide features. Bathymetric DEMs used in the compilation cover 1012.5 sq. km, which represents approximately 80% of the total area of Glacier Bay. The DEMs were collected in 2001 and 2009 for the southern and northern parts of the bay, respectively. To minimize resolution bias and maximize mapping consistency while maintaining visual fidelity, we re-sampled all the original bathymetry (resolution ranging from 1 to 16 m) to 5 m, which represents the minimum resolution for the majority of mapped areas; the lower resolution areas generally covered deeper and flatter portions of the bay where fewer landslides were present. For mapping, we used a topographic openness map (Yokoyama and others, 2002) in combination with a traditional slope map (see Red Relief Image Map in Chiba and others, 2008), which allows for good discernment of subtle concavities and convexities in the bathymetry and is well-suited for identifying landslide scars and deposits. We classified mapped landslides based on their source area type and used two primary classification categories of “slide” and “debris flow”. We used a third category, “mixed”, to classify landslides that showed evidence of both types of source area contributing to the deposit. For each landslide classified as slide or mixed, we mapped the source area and deposit as separate polygons. For landslides classified as debris flow, we mapped only deposits. Since debris flow source areas are subaerial drainage basins, delineating them should be part of larger future subaerial landslide mapping efforts in Glacier Bay National Park and Preserve. Similarly, for mixed landslides, we delineated source areas as the slide contribution area and not the larger debris-flow drainage basin component.
For any source areas (for mixed and slide polygons) or deposits that included a subaerial portion, we used 2012 5-m IFSAR data, and Landsat and DigitalGlobe imagery to map subaerial parts of the polygons. IFSAR and Landsat data are available from Earth Explorer (https://earthexplorer.usgs.gov/) and DigitalGlobe imagery is available from DigitalGlobe (https://www.digitalglobe.com/). These data and images are not included in this data release. Thirty-five of the forty-four slide and mixed features initiated as subaerial landslides. However, in all cases, we only mapped landslides if we could identify a submarine deposit. For example, we did not map the subaerial Tidal Inlet landslide (Wieczorek and others, 2007) because we could not identify a submarine deposit associated with it. Additionally, we did not map subaerial and submarine deposits that appeared to be deposited by water-dominated flows (e.g., alluvial fans and fan deltas), or large submarine fans that likely resulted from turbidite flows, such as the one at the junction of Queen Inlet and Glacier Bay. Because we could not observe mapped submarine landslides in the field, we assigned a level of moderate (77 landslides) or high (31 landslides) confidence based on our certainty that the mapped features represented actual slope failures. We omitted low confidence landslides from the map. In total, we mapped 108 landslides, with 22, 64, and 22 classified as slide, debris flow, and mixed, respectively. The total area (source and deposit) for slide and mixed type landslides ranged from 0.026 to 2.35 sq. km. Debris-flow deposits ranged from 0.012 to 0.61 sq. km.
Finally, we mapped a total of 7,097 individual landslide scarps where we could not identify any clear associated deposits, and where the distance between lateral flanks was approximately 50 m or more. Though we did our best to map only arcuate-shaped scarps typically formed by landslides (that is, single-mass failures), as opposed to geomorphic features formed by gradual glacial or submarine-current-related erosion (for example, submarine canyon walls), we acknowledge that some mapped scarps may have been formed by processes other than landsliding. Thus, for purposes of landslide susceptibility mapping, these scarp data are intended to be used in conjunction with other data, such as slope angle, geologic substrate, or geomorphic units. Ultimately, the full dataset is meant to serve as a qualitative component to inform future submarine and subaerial landslide susceptibility assessments in Glacier Bay National Park and Preserve. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. References used: Chiba, T., Kaneta, S., and Suzuki, Y., 2008, Red relief image map: new visualization method for three dimensional data: The international archives of the photogrammetry, remote sensing and spatial information sciences, v. 37, no. B2, p. 1071–1076. Wieczorek, G.F., Geist, E.L., Motyka, R.J., Jakob, M., 2007, Hazard assessment of the tidal inlet landslide and potential subsequent tsunami, Glacier Bay National Park, Alaska: Landslides, v. 4 p. 205–215. Yokoyama, R., Shirasawa, M., and Pike, R.J., 2002, Visualizing topography by openness: a new application of image processing to digital elevation models: Photogrammetric engineering and remote sensing, v. 68, no. 3, p. 257–266.

Purpose and intended use - This data set is used for analysis by the ADWR Recharge and Recovery group and is displayed in several ADWR GIS applications.Description of USF Program: An Underground Storage Facility (USF) Permit(A.R.S. § 45-811.01) allows the permit holder to operate a facility that stores water in the aquifer. The criteria a USF must meet in order to be permitted include:1. The project must be hydrologically feasible;2. The applicant must demonstrate financial and technical capability;3. The applicant must agree in writing to obtain any required floodplain use permit from the county flood control district before beginning any construction activities;4. The project may not cause unreasonable harm to land or other water users within the area of impact; and5. The project will continue to be monitored to ensure storage does not cause the migration of poor quality water. A Constructed Underground Storage Facility Permit allows for water to be stored in an aquifer by using some type of constructed device, such as an injection well or percolation basin. A Managed Underground Storage Facility Permit allows for water to be discharged to a naturally water-transmissive area such as a streambed that allows the water to percolate into the aquifer without the assistance of a constructed device. All surface flows entering and exiting a managed underground storage facility must be measured at the facility boundaries in a manner consistent with the Department’s measuring device rules (R12-15-905 & 906 ).Data creation methodologies, processing, and quality - Locations have been determined using aerial imagery, handheld GPS equipment, or materials supplied by permittees. Underground Storage Facility (71- ) feature class was dissolved over the rechargeUSF feature class and is maintained by ADWR. Each shape was created to reflect the permitted recharge boundaries of basins, wells, and river channels. This is a dissolved version of the LIB.rechargeUSF dataset and is displayed in multiple applications.Data limitations – ADWR staff have worked to improve the accuracy of features within this dataset , however ADWR makes no claims regarding the data quality. For instance, the dataset may not capture all current features of facilities or permits. Please refer to ADWR Data Disclaimer.Currency – This data is updated as new Underground Storage Facilities are permitted/inspected or when inaccuracies come to attention of the Recharge team.Last Updated September 2024.Contact– Hydrogeologist, Planning and Permitting Division, Recharge and Recovery Section, (602)771-8737https://www.azwater.gov/form/recharge-contact-formAttribute information - Program: Number associated with the USF program. This is 71 for USFs.Certificate: 6 digit number which follows “71-” and identifies each underground storage facilityConveyance: 4 digit number identifying a permit’s conveyance number. This typically increases by one whenever a permit modification or renewal is issued for the facility. This number follows the Program and Certificate which when combined follows a format of: 71-xxxxxx.xxxx. Phase: listed if a component is associated with a particular phase in the USF permitStatus: Active if currently able to use for recharge. Inactive if not.Map_Label: Name for display on map. Shortened from “Name”Water_Type: Water type that facility is permitted to store, (i.e. CAP, effluent, etc.)Permitted_Volume: Maximum permitted volume for the entire USF. This does not include any phased volumes.

The region is the top tier of local government in New Zealand. There are 16 regions of New Zealand (Part 1 of Schedule 2 of the Local Government Act 2002). Eleven are governed by an elected regional council, while five are governed by territorial authorities (the second tier of local government) who also perform the functions of a regional council and thus are known as unitary authorities. These unitary authorities are Auckland Council, Nelson City Council, Gisborne, Tasman, and Marlborough District Councils. The Chatham Islands Council also perform some of the functions of a regional council, but is not strictly a unitary authority. Unitary authorities act as regional councils for the purposes of a wide range of Acts and regulations. Regional council areas are based on water catchment areas. Regional councils are responsible for the administration of many environmental and public transport matters.Regional Councils were established in 1989 after the abolition of the 22 local government regions. The local government act 2002, requires the boundaries of regions to confirm as far as possible to one or more water catchments. When determining regional boundaries, the local Government commission gave consideration to regional communities of interest when selecting water catchments to included in a region. It also considered factors such as natural resource management, land use planning and environmental matters. Some regional boundaries are conterminous with territorial authority boundaries but there are many exceptions. An example is Taupo District, which is split between four regions, although most of its area falls within the Waikato Region. Where territorial local authorities straddle regional council boundaries, the affected area have been statistically defined in complete area units. Generally regional councils contain complete territorial authorities. The unitary authority of the Auckland Council was formed in 2010, under the Local Government (Tamaki Makarau Reorganisation) Act 2009, replacing the Auckland Regional Council and seven territorial authorities.The seaward boundary of any costal regional council is the twelve mile New Zealand territorial limit. Regional councils are defined at meshblock and area unit level.Regional Councils included in the 2013 digital pattern are:Regional Council CodeRegional Council Name01Northland Region02Auckland Region03Waikato Region04Bay of Plenty Region05Gisborne Region06Hawke's Bay Region07Taranaki Region08Manawatu-Wanganui Region09Wellington Region12West Coast Region13Canterbury Region14Otago Region15Southland Region16Tasman Region17Nelson Region18Marlborough Region99Area Outside RegionAs at 1stJuly 2007, Digital Boundary data became freely available.Deriving of Output FilesThe original vertices delineating the meshblock boundary pattern were digitised in 1991 from 1:5,000 scale urban maps and 1:50,000 scale rural maps. The magnitude of error of the original digital points would have been in the range of +/- 10 metres in urban areas and +/- 25 metres in rural areas. Where meshblock boundaries coincide with cadastral boundaries the magnitude of error will be within the range of 1–5 metres in urban areas and 5 - 20 metres in rural areas. This being the estimated magnitude of error of Landonline.The creation of high definition and generalised meshblock boundaries for the 2013 digital pattern and the dissolving of these meshblocks into other geographies/boundaries were completed within Statistics New Zealand using ESRI's ArcGIS desktop suite and the Data Interoperability extension with the following process: 1. Import data and all attribute fields into an ESRI File Geodatabase from LINZ as a shapefile2. Run geometry checks and repairs.3. Run Topology Checks on all data (Must Not Have Gaps, Must Not Overlap), detailed below.4. Generalise the meshblock layers to a 1m tolerance to create generalised dataset. 5. Clip the high definition and generalised meshblock layers to the coastline using land water codes.6. Dissolve all four meshblock datasets (clipped and unclipped, for both generalised and high definition versions) to higher geographies to create the following output data layers: Area Unit, Territorial Authorities, Regional Council, Urban Areas, Community Boards, Territorial Authority Subdivisions, Wards Constituencies and Maori Constituencies for the four datasets. 7. Complete a frequency analysis to determine that each code only has a single record.8. Re-run topology checks for overlaps and gaps.9. Export all created datasets into MapInfo and Shapefile format using the Data Interoperability extension to create 3 output formats for each file. 10. Quality Assurance and rechecking of delivery files.The High Definition version is similar to how the layer exists in Landonline with a couple of changes to fix topology errors identified in topology checking. The following quality checks and steps were applied to the meshblock pattern:Translation of ESRI Shapefiles to ESRI geodatabase datasetThe meshblock dataset was imported into the ESRI File Geodatabase format, required to run the ESRI topology checks. Topology rules were set for each of the layers. Topology ChecksA tolerance of 0.1 cm was applied to the data, which meant that the topology engine validating the data saw any vertex closer than this distance as the same location. A default topology rule of “Must Be Larger than Cluster Tolerance” is applied to all data – this would highlight where any features with a width less than 0.1cm exist. No errors were found for this rule.Three additional topology rules were applied specifically within each of the layers in the ESRI geodatabase – namely “Must Not Overlap”, “Must Not Have Gaps” and “"Area Boundary Must Be Covered By Boundary Of (Meshblock)”. These check that a layer forms a continuous coverage over a surface, that any given point on that surface is only assigned to a single category, and that the dissolved boundaries are identical to the parent meshblock boundaries.Topology Checks Results: There were no errors in either the gap or overlap checks.GeneralisingTo create the generalised Meshblock layer the “Simplify Polygon” geoprocessing tool was used in ArcGIS, with the following parameters:Simplification Algorithm: POINT_REMOVEMaximum Allowable Offset: 1 metreMinimum Area: 1 square metreHandling Topological Errors: RESOLVE_ERRORSClipping of Layers to CoastlineThe processed feature class was then clipped to the coastline. The coastline was defined as features within the supplied Land2013 with codes and descriptions as follows:11- Island – Included12- Mainland – Included21- Inland Water – Included22- Inlet – Excluded23- Oceanic –Excluded33- Other – Included.Features were clipped using the Data Interoperability extension, attribute filter tool. The attribute filter was used on both the generalised and high definition meshblock datasets creating four meshblock layers. Each meshblock dataset also contained all higher geographies and land-water data as attributes. Note: Meshblock 0017001 which is classified as island, was excluded from the clipped meshblock layers, as most of this meshblock is oceanic. Dissolve meshblocks to higher geographiesStatistics New Zealand then dissolved the ESRI meshblock feature classes to the higher geographies, for both the full and clipped dataset, generalised and high definition datasets. To dissolve the higher geographies, a model was built using the dissolver, aggregator and sorter tools, with each output set to include geography code and names within the Data Interoperability extension. Export to MapInfo Format and ShapfilesThe data was exported to MapInfo and Shapefile format using ESRI's Data Interoperability extension Translation tool. Quality Assurance and rechecking of delivery filesThe feature counts of all files were checked to ensure all layers had the correct number of features. This included checking that all multipart features had translated correctly in the new file.

Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice.Sentinel-2, 10 and 60m Multispectral 13-band imagery, rendered on-the-fly. Available for visualization and analytics, this Imagery Layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.This imagery layer can be used for multiple purposes including but not limited to bathymetric mapping applications, changing lands and marine environmental monitoring.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean SeaNote: Areas of interest going beyond the Mission baseline (as laid out in the Mission Requirements Document) will be assessed, and may be added to the baseline if sufficient resources are identified.Temporal CoverageThe revisit time for each point on Earth is every 5 days.This layer is updated daily with new imagery.This imagery layer is designed to include imagery collected within the past 14 months. Custom Image Services can be created for access to images older than 14 months.The number of images available will vary depending on location.Image Selection/FilteringThe most recent and cloud free image, for any location, is displayed by default.Any image available, within the past 14 months, can be displayed via custom filtering.Filtering can be done based on Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More…NOTE: Not using filters, and loading the entire archive, may affect performance.Analysis ReadyThis imagery layer is analysis ready with TOA correction applied.Visual RenderingDefault rendering is Bathymetric (bands 4,3,1) with Dynamic Range Adjustment (DRA). This DRA version enables visualization of the full dynamic range of the images. The non-DRA version of this layer can be viewed by switching to the pre-defined Bathymetric raster function.Bands red, green, coastal/aerosol with dynamic range adjustment applied. Useful in bathymetric mapping applications.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Color-Infrared with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn Ratio, NDVI Colormap.Multispectral BandsBandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request.Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS , or alternatively access Sentinel2Look Viewer, EarthExplorer or the Copernicus Open Access Hub to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice.Sentinel-2, 10m Multispectral 13-band imagery, rendered on-the-fly. Available for visualization and analytics, this Imagery Layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.This imagery layer can be used for multiple purposes including but not limited to vegetation, plant health, land cover and environmental monitoring.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean SeaNote: Areas of interest going beyond the Mission baseline (as laid out in the Mission Requirements Document) will be assessed, and may be added to the baseline if sufficient resources are identified.Temporal CoverageThe revisit time for each point on Earth is every 5 days.This layer is updated daily with new imagery.This imagery layer is designed to include imagery collected within the past 14 months. Custom Image Services can be created for access to images older than 14 months.The number of images available will vary depending on location.Image Selection/FilteringThe most recent and cloud free image, for any location, is displayed by default.Any image available, within the past 14 months, can be displayed via custom filtering.Filtering can be done based on Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More…NOTE: Not using filters, and loading the entire archive, may affect performance.Analysis ReadyThis imagery layer is analysis ready with TOA correction applied.Visual RenderingDefault rendering is Color-Infrared (bands 8,4,3) with Dynamic Range Adjustment (DRA).This DRA version enables visualization of the full dynamic range of the images. The non-DRA version of this layer can be viewed by switching to the pre-defined Color Infrared raster function.Bands near-infrared, red, green with dynamic range adjustment applied. Healthy vegetation is bright red while stressed vegetation is dull red.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Bathymetric with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn Ratio, NDVI Colormap.Multispectral BandsBandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request.Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS , or alternatively access Sentinel2Look Viewer, EarthExplorer or the Copernicus Open Access Hub to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

This dataset shows historical roads in Albemarle County, Virginia. Current road data from the OpenStreetMap database was used a starting point and compared to historical maps from 1864, 1867, 1875, and 1907 to identify historical roads. Features were also compared to historical aerial imagery from 1937 and 1955 provided by the University of Virginia to identify where the road bed has been adjusted in modern times. Roads that no longer exist, and thus were not present in the OSM database, were mapped using LiDAR data from the Virginia Geographic Information Network.Roads were divided into three category types:Road: Indicates the feature is still a current road in useRoad Trace / Road Path: In most cases these are road traces visible in the LiDAR data. In some limited cases the historical road bed is no longer present however the likely path of the road is obvious.Possible Road Path: These are features identified on a historical map but for which no trace is visible on LiDAR or current and historical imagery. These features represent a possible path based on the terrain. They can be thought of as "place holders" indicating that a road ran through a general area.Attributes are also included indicating if a feature is present on four historical maps:Campbell/Gilmer's 1864 mapHotchkiss' 1867 mapPeyton's 1875 mapMassie's 1907 mapDue to the inherent challenges in mapping features that no longer exist, all historical features in this dataset should be considered approximate and evaluated before use in other research projects.This data can be viewed with other historical data layers in the Historical Albemarle webmap: https://www.fadedcontours.com/map/

This layer includes Landsat GLS pansharpened imagery rendered on-the-fly as Natural Color with DRA for use in visualization and analysis. This layer is time enabled and includes a number of pansharpened renderings on demand. The layer includes 30m natural color Landsat 7 ETM+, Landsat 5 TM, and Landsat 4 imagery, enhanced with 15m panchromatic imagery.Geographic CoverageWorld-wide imagery coverage.Temporal CoverageThis imagery layer includes data from epochs 2010, 2005 and 2000. Analysis ReadyThis imagery layer is analysis ready with Top of Atmosphere (TOA) correction applied.The TOA reflectance values (ranging 0 – 1 by default) are scaled using a range of 0 – 10,000.The scale is equivalent to other TOA reflectance products, including those provided by the USGS.Image Selection/FilteringNewer images are displayed by default on top.The entire archive is accessible via custom filtering.A number of fields are available for filtering, including Acquisition Date, Estimated Cloud Cover, and Product ID.By setting the filter to Best is lesser than QQQQ one can control to see the best N scenes, where QQQQ=N*1million.NOTE: Turning off all filters, and loading the entire archive, may affect performance.Visual RenderingDefault layer is Pansharpened Enhanced with Dynamic Range Adjustment (DRA), which is a band combination (original bands 4,3,2) that displays natural colors.The DRA version of each layer enables visualization of the full dynamic range of the images.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions can be created.Other Layer Usage Notes...Overviews exist with a spatial resolution of 300m and are updated weekly based on the best and latest imagery available at that time.To work with individual source images at all scales, either use the ‘Lock Raster’ functionality or add a query filter to restrict the display to a specified image or group of images.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.Images can be exported up to a maximum of 2,000 columns x 2,000 rows per request.This ArcGIS Server dynamic Imagery Layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image Services API.WCS and WMS compatibility means this imagery can be consumed as WCS or WMS services.Landsat Web App via Unlock Earth's Secrets.Data SourceLandsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted by the Amazon Web Services as part of their Public Data Sets program. Users can access full scenes from Landsat on AWS, or alternatively access LandsatLook to review and download full scenes from the complete USGS archive.The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit GLS.

The Waterbodies dataset is comprised of area features: lakes, intermittent waterbodies, islands, and rivers wide enough to be represented as an area feature (e.g. St. Lawrence River, Mackenzie River). In a few exceptional cases, islands had to be represented by "holes" in the polygons in the Waterbodies dataset. Some area features have been subdivided and several types of virtual linear features serve to separate them. Features in this dataset are linked (by an attribute) to their corresponding flow line in the Drainage Network Skeleton. Therefore the Waterbodies dataset may be used in conjunction with the Drainage Network Skeleton for analytical applications. The Islands dataset is comprised of area and linear features: islands within inland waters and the waterbodies and single line rivers within these islands. Oceanic islands are not included as they are part of the coastline component of the Drainage Network Skeleton dataset. The Islands dataset exists to complete the cartographic representation of Canadian hydrology. The Islands dataset is not logically connected with the Drainage Network Skeleton, and can not be used for analytical applications. It should be noted that flow lines of the Drainage Network Skeleton do not take into account of the existence of islands and therefore do not necessarily flow around them. In a few exceptional cases, islands had to be represented by "holes" in the polygons in the Waterbodies dataset. Some islands themselves contain waterbodies and rivers, not significant for network analysis. However, in order to support a complete cartographic representation such waterbodies and rivers have been added to the Islands dataset. The National Scale Frameworks Hydrology data consists of area, linear and point geospatial and attribute data for Canada's hydrology at a national scale. It provides a representation of Canada's surface water features, and data completeness reflects the content of the source, the original Vector Map level 0 (VMAP0) revision 4 hydrographic layers, except where revision editing has been performed. Key value-added characteristics include river flow direction, connectivity and the tagging of geographical name keys to selected rivers, lakes and islands included in the Concise Gazetteer of Canada. The Atlas Frameworks are a set of integrated base map layers which form part of a larger National Scale Frameworks data collection. These data have been compiled at a scale of 1:1 000 000 with the primary goal being to indicate correct relative positioning with other framework layers rather than absolute positional accuracy.Distributed from GeoYukon by the Government of Yukon. Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: geomatics.help@gov.yk.ca

Marine Reserve's are the government's most comprehensive tool in the provision of area-based biodiversity protection in the marine environment. Marine reserves are specified areas of the sea and foreshore that are managed to preserve themin their natural state as the habitat of marine life for scientific study.Marine reserves may be established in areas that contain underwater scenery, natural features, or marine life of such distinctive quality, or so typical, beautiful or unique that their continued preservation is in the national interest. Under the Marine Reserves Act 1971, the Department of Conservation is responsible for caring for and managing marine reserves. Management functions include marking marine reserve boundaries, law enforcement, issuing scientific permits and monitoring environmental changes.Further information about any particular Marine Reserve with associated map and bounding co-ordinates can be found at: https://www.doc.govt.nz/nature/habitats/marine/marine-reserves-a-z/*****LICENCE*****This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/ or send a letter to Creative Commons, 444 Castro Street, Suite 900, MountainView, California, 94041, USA. *****DISCLAIMER*****1. DOC makes no express or implied warranties as to the accuracy or completeness of the data or information, nor its suitability for any purpose. Errors are inevitably part of any database, and can arise by a number of means, from errors during field data collection, to errors during data entry. 2. DOC makes no warranties or representations as to possible infringement upon copyrights or other intellectual property rights of others in the data or information. 3. DOC will not accept liability for any direct, indirect, special or consequential damages, losses or expenses howsoever arising and relating to use, or lack of use, of the data or information supplied. *****GUIDELINES FOR THE USE OF THE INFORMATION***** 4. Care should be taken in deriving conclusions from any data or information supplied. 5. Any use of the data or information supplied should state when the data or information was acquired and that it may now be out-of-date. *****COPYRIGHT OBLIGATIONS***** 6. All proprietary rights to the intellectual property in the data or information remain with the Crown as its sole property. 7. Modification of the data and information or the addition of the information does not confer copyright or any other form of property of the original material to a user. 8. All maps or reports that are derived from the data or information must acknowledge the Crown copyright, in the following way: Crown Copyright: Department of Conservation Te Papa Atawhai [year]. 9. This information resource may be passed onto another party, in either hard copy or electronic form. If a user does this, then it is recommended that they also supply this metadata record with the information resource.

This dataset is a selected subset of historical road traces in Albemarle County, Virginia completed by Faded Contours (full dataset available in the Reference subgroup). Additional naming information for historic road traces within Morven comes from research completed by Rivanna Archaeological Services (RAS). Current road data from the OpenStreetMap database was used a starting point and compared to historical maps from 1864, 1867, 1875, and 1907 to identify historical roads. Features were also compared to historical aerial imagery from 1937 and 1955 provided by the University of Virginia to identify where the road bed has been adjusted in modern times. Roads that no longer exist, and thus were not present in the OSM database, were mapped using LiDAR data from the Virginia Geographic Information Network.Roads were divided into three category types:Road: Indicates the feature is still a current road in useRoad Trace / Road Path: In most cases these are road traces visible in the LiDAR data. In some limited cases the historical road bed is no longer present however the likely path of the road is obvious.Possible Road Path: These are features identified on a historical map but for which no trace is visible on LiDAR or current and historical imagery. These features represent a possible path based on the terrain. They can be thought of as "place holders" indicating that a road ran through a general area.Attributes are also included indicating if a feature is present on four historical maps:Campbell/Gilmer's 1864 mapHotchkiss' 1867 mapPeyton's 1875 mapMassie's 1907 mapDue to the inherent challenges in mapping features that no longer exist, all historical features in this dataset should be considered approximate and evaluated before use in other research projects.This data can be viewed with other historical data layers in the Historical Albemarle

More MetadataThis GIS layer contains the geographical boundaries of the 2010 census block groups for Loudoun County, Virginia. The 2010 Census block group boundaries are used for Census Bureau statistical data tabulation purposes, including the 2010 Decennial Census and American Community Surveys.

Census block groups are part of the sub-county census geography hierarchy of tracts, block groups, and blocks. The three census geographies nest to each other, forming a hierarchy of census tract, followed by block groups, and then blocks, with blocks being the smallest. A census block group is a cluster of census blocks within the same census tract that have the same first digit of their four-digit census block numbers within a census tract.

Loudoun County's block groups were delineated by Loudoun County Government during the Census Bureau's Participant Statistical Areas Program for the 2010 Census. The 2010 Census block layer has been modified from the Census Bureau's Tiger line file. Users should be aware that the Census's Tiger line data is devised from a mix of national and local GIS data sets. When the Tiger line data is overlaid with Loudoun County Government's detailed GIS layers it can be determined that the Census Bureau's Tiger line boundaries in some cases are slightly off from the actual location of the physical features, natural features, and governmental units such as town boundaries that they are designated to follow. The 2010 Loudoun census block group layer was generated by Loudoun County so that the block group boundaries would overlay with the features in Loudoun County's GIS data sets that the boundary are designated to follow.