This tool takes the state of a web application (for example, included services, layer visibility settings, and client-side graphics) and returns a printable page layout or basic map of the specified area of interest., The input for Export Web Map is a piece of text in JavaScript object notation (JSON) format describing the layers, graphics, and other settings in the web map. The JSON must be structured according to the ExportWebMap specification in the ArcGIS Help., This tool is shipped with ArcGIS Server to support web services for printing, including the preconfigured service named PrintingTools. The ArcGIS web APIs for JavaScript, Flex and Silverlight use the PrintingTools service to generate images for simple map printing.

This file contains the digital vector boundaries for Nomenclature of Territorial Units for Statistics Level 1, in the United Kingdom, as at January 2018.

NUTS areas in England and Wales are unchanged but there are changes in Scotland (at NUTS2) and in Northern Ireland (NUTS3). In Scotland a fifth NUTS2 area has been created (Southern Scotland), while in Northen Ireland the new NUTS3 areas will now match the 11 local government districts.

• Full resolution - extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands);
  
• Full resolution - clipped to the coastline (Mean High Water mark);
  
• Generalised (20m) - clipped to the coastline (Mean High Water mark);
  
• Super generalised (200m) - clipped to the coastline (Mean High Water mark) and
  
• Ultra generalised (500m) - clipped to the coastline (Mean High Water mark).
  

Contains both Ordnance Survey and ONS Intellectual Property Rights.

Download File Sizes

• Full resolution - extent of the realm (30 MB)
• Full resolution - clipped to the coastline (34 MB)
• Generalised (20m) - clipped to the coastline (3 MB)
• Super generalised (200m) - clipped to the coastline (648 KB)
• Ultra generalised (500m) - clipped to the coastline (263 KB).

https://cdn.arcgis.com/cdn/20886/js/jsapi/dojo/resources/blank.gif" />

REST URL of ArcGIS for INSPIRE View Service – https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/NUTS_Level_1_January_2018_Boundaries/MapServer/exts/InspireView

REST URL of ArcGIS for INSPIRE Feature Download Service – https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/NUTS_Level_1_January_2018_Boundaries/MapServer/exts/InspireFeatureDownload

REST URL of Feature Service (use these URLs in maps, where you can view pop-up information and change the styling) - https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/NUTS_Level_1_January_2018_Boundaries/FeatureServer

This file contains the digital vector boundaries for Nomenclature of Territorial Units for Statistics Level 1, in the United Kingdom, as at January 2018.

NUTS areas in England and Wales are unchanged but there are changes in Scotland (at NUTS2) and in Northern Ireland (NUTS3). In Scotland a fifth NUTS2 area has been created (Southern Scotland), while in Northen Ireland the new NUTS3 areas will now match the 11 local government districts.

• Full resolution - extent of the realm (usually this is the Mean Low Water mark but in some cases boundaries extend beyond this to include off shore islands);
  
• Full resolution - clipped to the coastline (Mean High Water mark);
  
• Generalised (20m) - clipped to the coastline (Mean High Water mark);
  
• Super generalised (200m) - clipped to the coastline (Mean High Water mark) and
  
• Ultra generalised (500m) - clipped to the coastline (Mean High Water mark).
  

Contains both Ordnance Survey and ONS Intellectual Property Rights.

Download File Sizes

• Full resolution - extent of the realm (30 MB)
• Full resolution - clipped to the coastline (34 MB)
• Generalised (20m) - clipped to the coastline (3 MB)
• Super generalised (200m) - clipped to the coastline (648 KB)
• Ultra generalised (500m) - clipped to the coastline (263 KB).

https://cdn.arcgis.com/cdn/20886/js/jsapi/dojo/resources/blank.gif" />

REST URL of ArcGIS for INSPIRE View Service – https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/NUTS_Level_1_January_2018_Boundaries/MapServer/exts/InspireView

REST URL of ArcGIS for INSPIRE Feature Download Service – https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/NUTS_Level_1_January_2018_Boundaries/MapServer/exts/InspireFeatureDownload

REST URL of Feature Service (use these URLs in maps, where you can view pop-up information and change the styling) - https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/NUTS_Level_1_January_2018_Boundaries/FeatureServer

This dataset contains air quality data between the years 2000 and 2018 for 32000 ZIP codes. It was used by Harvard and Esri researchers in a study about air quality and its disparities across the United States. The research shows that air quality has generally improved across the US since 2000. But it has not improved equally for everyone - namely Black, Asian, Latinx, and low-income populations.Link: https://github.com/xiaodan-zhou/pm25_and_disparityPaper: https://www.esri.com/arcgis-blog/products/js-api-arcgis/mapping/air-quality-disparities-among-ethnic-groups-and-income-level/You can find the shapefile boundary in this our data hub: https://usc-geohealth-hub-uscssi.hub.arcgis.com/datasets/USCSSI::u-s-5-digit-zip-code-tabulation-areas-zcta5-boundary/explore

Lands Department of Hong Kong SAR has released Location Search API which is available in Hong Kong Geodata Store (https://geodata.gov.hk/gs/). This API is very useful to Esri Users in Hong Kong as it saves vast amount of time to carry out data conversion to support location searching. The API is HTTP-based for application developers to find any locations in Hong Kong by addresses, building names, place names or facility names.

This code sample contains sample HTML and JavaScript files. Users can follow This Guidelines to use the Location Search API with ArcGIS API for JavaScript to build web mapping applications with ArcGIS API for JavaScript.

This map provides a preview and information about the National Agriculture Imagery Program (NAIP) image service available on the USDA Farm Production and Conservation Business Center Geospatial Enterprise Office public image server. Under the NAIP folder you will find a cached layer of the Contiguous United States which provides fast rendering and is scaled up to Level 17. NAIP image dates vector services showing when imagery was acquired are available on the NAIP Image Dates Data Hub. Click on the map tack pin to bring up a thumbnail view of the imagery for that area. Click the more info link to view the REST services directory for that image. This directory provides information about the image service and provides links to view the image in the ArcGIS Online map viewer, ArcMap, ArcGIS Javascript, or Google Earth. If you have feedback about NAIP imagery you can provide it by accessing the NAIP Imagery Feedback map.To view the status of the 2024 NAIP inspection view the NAIP Inspection Status Dashboard.For ordering information and other questions please contact our Customer Service Section at geo.sales@usda.gov.For questions and comments about this map please contact Joan Biediger at joan.biediger@usda.gov.

View In: ArcGIS JavaScript ArcGIS Online map viewer Google Earth ArcMapSatellite imagery review of a storm track revealed a tornado damage path through forested areas that occurred on September 5, 2018 around 7:45 pm local time. High-resolution aerial imagery was collected in July 2019. Damage assessed as EF1, with an estimated maximum wind speed of 145 km/h, track length of 7.0 km and maximum path width of 330 m. Tornado motion from the WSW.

Summary: These data represent the DWR edited version of statistically based polygons derived from GPS collared data on animals migrating in Utah from 2016 - 2021. The GPS data were analyzed using the Brownian Bridge Movement Model (BBMM), which produced polygons based on an animal’s movement path from data recorded at brief intervals. This model understands that location points are connected to each other in time. Every animal has its own footprint of its migration. Each animal’s averaged footprint is combined into one layer. Corridor level of use types are combined and clipped into one dataset and the level of use is classified:Low use: 0 - 25% of the populationMedium use: 25 - 75% of the populationHigh Use: > 75% of the population (after Sawyer and others, 2009)Stopovers are extracted from the combined footprints and defined as the top 10% of the values. Stopover sites show where the animals spend most of their time during migration, and are likely used as foraging and resting areas. References:Sawyer, H., Kauffman, M. J., Nielson, R. M., & Horne, J. S. (2009). Identifying and prioritizing ungulate migration routes for landscape‐level conservation. Ecological Applications, 19(8), 2016-2025.

This wolverine prdicted habitat layer is a composite of two predictions of wolverine habitat (citations 1 & 2). Only the "primary" or resident adult habitat was included from citation 1 (Inman et al. 2013). The 2 predicted habitat layers were combined and any area predicted as wolverine habitat by either source was included. This combined layer was used in the first survey in 2016 as written up in citation 3 (Lukacs et al. 2020). 1. Inman, R. M., B.L. Brock, K.H. Inman, S.S. Sartorius, B.C. Aber, B. Giddings, S.L. Cain, M.L. Orme, J.A. Fredrick, B.J. Oakleaf, K.L. Alt, E. Odell, and G. Chapron. 2013. Developing Priorities for Metapopulation Conservation at the Landscape Scale: Wolverines in the Western United States. Biological Conservation 166:276–286. 2. Copeland, J.P., K.S. McKelvey, K.B. Aubry, A. Landa, J. Persson, R.M. Inman, J. Krebs, E. Lofroth, H. Golden, J.R. Squires, A. Magoun, M.K. Schwartz, J. Wilmot, C.L. Copeland, R.E. Yates, I. Kojola, R. May. 2010. The bioclimatic envelope of the wolverine (Gulo gulo spp.): do climatic constraints limit its geographic distribution? Canadian Journal of Zoology 88(3): 233–246. 3. Lukacs, P.M., D.E. Mack, R. Inman, J.S. Gude, J.A, Ivan, R.P. Lnaks, J.C. Lewis, R.A. Long, R. Sallabanks, Z. Walker, S. Courville, S. Jackson, R. Kahn, M.K. Schwartz, S.C. Torbit, J.S. Waller, and K. Carroll. 2020. Wolverine occupancy, spatial distribution, and monitoring design. Journal of Wildlife Management 84(5):841-851. 10.1002/jwmg.21856.