Sentinel-2 multispectral and multitemporal atmospherically corrected imagery with on-the-fly visual renderings and indices for visualization and analysis. This includes thirteen multispectral bands at spatial resolutions of 10, 20, and 60-meters. This Imagery Layer is sourced from the Planetary Computer Sentinel-2 Level-2A data catalog on Azure, which is updated daily with the latest available imagery.Geographic CoverageGlobal landmassesTemporal Coverage2015 to presentThe revisit time for each point on Earth is every 5 daysThis layer is updated daily with new imageryProduct LevelLevel-2A atmospherically corrected, surface reflectanceProcessed with Sen2Cor and PlanetDEM elevation dataImage Selection/FilteringA number of fields are available for filtering, including Acquisition Date, Estimated Cloud Cover, and Product ID.To isolate and work with specific images, either use the ‘Image Filter’ to create custom layers or add a ‘Query Filter’ to restrict the default layer display to a specified image or group of images.Visual RenderingThe default 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 - 0.9556011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Additional Usage NotesImage exports are limited to 4,000 columns x 4,000 rows per request.This dynamic imagery layer can be used in Web Maps and ArcGIS Pro as well as web and mobile applications using the ArcGIS REST APIs.Data SourceSentinel-2 imagery is the result of close collaboration between the European Space Agency (ESA), the European Commission and the USGS. The source data for this service is processed by Esri and hosted in Azure as as part of the Planetary Computer Data Catalog.For information on Sentinel-2 imagery, see Sentinel-2.

The data set contains the road data created as part of the project with extended attributes in order to examine the tasks described in the project. Further information can be found in the final report of the project. The download leads to a ZIP folder made available on ArcGIS Online. Contains: As a file geodatabase: - Adjusted road data with attributes that are necessary for routing - Point data that serve as connecting points to transfer the adjusted road data into an existing routing system. As HTML/JavaScript: - Web application that was created as part of the project with ArcGIS Enterprise and Web App Builder. This can be hosted on a standalone web server. This requires executable data on ArcGIS Online or ArcGIS Enterprise (not included).

Deep learning AI analysis of cardinal photosphere images for Anaheim unincorporated area in Orange County California (2018-337p1). The image locations (8 cardinal photospheres per location) containing results of image recognition by Azure cognitive vision model implementation.

Important Note: This item is in mature support as of June 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The GEOGloWS ECMWF Streamflow System represents a daily 51-member ensemble streamflow forecast for over 1 million reaches across the globe. Gridded surface runoff, provided by the European Centre for Medium-range Weather Forecasting (ECMWF), is downscaled and routed to the streams using the Routing Application for Parallel computation of Discharge (RAPID). This animation layer shows the first 6-days of a 15-day forecast at 3-hr intervals. Additionally, a 40-yr historical simulation was produced based on ECMWF’s ERA5 dataset. From this historical simulation , return periods for each reach are calculated and used to color the stream segments when/where events exceed these thresholds. Credits: This forecast model was produced as part of the GEOGloWS Partnership with collaboration from BYU, ECMWF, esri, NOAA, NASA, SERVIR, USAID, ICIMOD, JRC, Copernicus, World Bank, and Microsoft Azure.What can you do with this layer?This map service is designed for fast data visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the forecast data sequentially using the time slider, which is set to three hour intervals by default by Enabling Time Animation. This layer type is not recommended for use in analysis.Revisions:Dec 15, 2020: Updated 'flowstyle' field values from color names: 'blue', 'yellow', 'purple', ... to Return Period values. This now reports '0', '2', '5', '10', '25', '50', and '100' indicating the forecasted return period. The symbology has also been extended to better depict the relevant state of each reach using these periods.

The feature class represents a sheet of the Regional Technical Paper 1:5000. The data was received from the Molise Region in shapefile format.

This dataverse consists of three datasets for the ArcGIS Storymaps article: "Elverhøy - frå fiksjon til realitet": https://storymaps.arcgis.com/stories/3d9e1d5893ad4e65b43c32a5617e63f1: The datasets originate from the: 1.: 1886 Norwegian Cadastre (file M1886_Elverhoy.txt) 2.: 1950 Norwegian Cadastral Draft (file MU1950_Elverhoy.txt) 3.: 2010 Norwegian Cadastre (GAB-Register) (file M2010_Elverhoy.txt) Dataset 1 originate from Registeringssentral for historiske data, University of Tromsø. Dataset 2 derive from the Språksamlingane (The Norwegian Language Collections), University of Bergen.Dataset 3 is sourced from Statens kartverk (The Norwegian Mapping Authority).All datasets have been augmented under the auspices of the Språksamlingane (The Norwegian Language Collections).

This feature layer displays completed project locations as tracked by engineering staff at Leon County Public Works. This feature layer is a subset (view) of a parent hosted feature layer that is updated twice daily from a cloud (Azure) hosted SQL database that is administered by Leon County Applications team and maintained by engineering staff at Leon County Public Works.

This feature layer displays historical project locations as tracked by engineering staff at Leon County Public Works. This feature layer is a subset (view) of a parent hosted feature layer that is updated twice daily from a cloud (Azure) hosted SQL database that is administered by Leon County Applications team and maintained by engineering staff at Leon County Public Works.

Données de la station Quai des Célestins pour l'année 2022

Deep learning AI analysis of cardinal photosphere images for North Tustin unincorporated area in Orange County California. The image locations (front left driving direction) containing results of image recognition by Azure cognitive vision model implementation.

The MM_Tmin_Marzo feature class is a polygonal feature class that represents the areas with homogeneous minimum temperatures measured in the month of March. Of the minimum temperatures are considered the minimum, the average and the maximum monthly. Each area was calculated by interpolation starting from the data collected by the individual measuring stations.

The digital model of the terrain is represented by a DTM with a grid structure with a sampling pitch of 20 metres, which can be used both to analyze the orographic trend of the Lombardy territory and to carry out various types of studies, being integrated with the other vector databases of the regional territorial information system. The coverage includes the hilly and mountainous areas of the Lombardy Region. The GRID is a raster file developed by Esri, which has two formats: A proprietary binary format, also known as ARC / INFO GRID, ARC GRID and many other variants, and an ASCII format non-proprietary, also known as GRID ASCII ARC / INFO. The binary format is widely used in Esri programs, such as ArcGIS, while the ASCII format is used as an exchange, or export format, due to its simple and portable structure. The GRID represents geographic space as a matrix of equal-sized square grid points composed of rows and columns. Each grid point stores a numerical value that represents a geographic attribute (such as surface elevation or slope). Each cell of the grid is georeferenced.

The feature class represents a sheet of the Regional Technical Paper 1:5000. The data was received from the Molise Region in shapefile format.

The MO_PDF133G_Molise_vinc feature class represents some areas of the municipal territory affected by specific restrictions that limit building rights. The elements were acquired from the Table: Zoning, of the Manufacturing Program on a scale of 1:1000. The feature class contains the information relating to the Istat Code of the municipality, and the type of restriction falling within the Municipality.

The MO_PDF231G_Tavenna feature class represents the urban zoning of the Municipality of Tavenna, the elements were acquired from Tables 4: Zoning (at a scale of 1:1000), 6: Identification of Variants (at a scale of 1:1000), of the Manufacturing Program. feature class contains the information relating to the Istat Code of the municipality, the subdivision into homogeneous areas regulated by the technical standards of the specific plan of the aforementioned Municipality and the information relating to the homogeneous areas regulated by a univocal subdivision for the entire Molise Region.

The MO_PRG280G_Riccia_vinc feature class represents some areas of the municipal territory affected by specific constraints that limit building rights. The elements were acquired from Tables 5: Zoning plan of the capital (on a scale of 1:1,000), 7: Zoning plan of the areas outside the capital "zone D" (on a scale of 1:2,000), 8: Zoning plan of the external areas to the capital "zone G" (scale 1:2.000), 9: Zoning plan of areas outside the capital "zone C3" (scale 1:2.000), of the General Town Plan. The feature class contains information relating to the Istat Code of the municipality, and the type of bond falling within the municipality.

The MM_Tmax_April feature class is a polygonal feature class that represents the areas with homogeneous maximum temperatures measured in the month of April. Of the Maximum Temperatures are considered the maximum, the average and the minimum monthly. Each area was calculated by interpolation starting from the data collected by the individual measuring stations.

the MO_DBP321G_Intersections_Roads feature class represents road intersections from the DBPrior 10k GDF 1 (Geographic data Files) . Data delivered by the Molise Region

The MO_alteraz_degrado_poly_2 feature class represents the elements of alteration and degradation, area elements acquired from the map of the alterations and degradation of the territory on a scale of 1:25 000. The PTPAAV maps (Piano Territoriale Landscape Enviromental di Vasta Area) are a series of thematic maps drawn up from 1989 and finished and approved at the end of November 1991, are divided into territorial areas for a total of 8 areas identified on the regional territory. The work was carried out by various groups of technicians, a coordination group which established through circulars the standards to be used for the drafting of the plans which ranged from the thickness of the tip of the graph to the type of screen and the shades to be used, and 8 groups one for each area, who created the maps trying to standardize the territorial information as much as possible. The hard copy of this work was delivered to us in 2008 by the Environmental Heritage Office of the Molise Region. The latter already had scans of some thematic maps relating to some areas, the missing ones and in the case of scans that were not suitable for georeferencing, they were scanned. The cartographic basis used by the working groups for the creation of the PTPAAV maps was the IGM in 1:25,000 scale.

Données de la station Boulevard Haussmann pour l'année 2022