IntroductionIRWIN ArcGIS Online GeoPlatform Services The Integrated Reporting of Wildland-Fire Information (IRWIN) Production data is replicated every 60 seconds to the ArcGIS Online GeoPlatform organization so that read-only views can be provided for consumers. This replicated view is called the hosted datastore. The “IRWIN Data” group is a set of Feature Layer views based on the replicated IRWIN layers. These feature layers provide a near real-time feed of all valid IRWIN data. All incidents that have been shared through the integration service since May 20, 2014 are available through this service. The incident data provides the location of existing fires, size, conditions and several other attributes that help classify fires. The IRWIN Data service allows users to create a web map, share it with their organization, or pull it into ArcMap or ArcGIS Pro for more in-depth analysis.InstructionsTo allow the emergency management GIS staff to join the IRWIN Data group, they will need to set up an ArcGIS Online account through our account manager. Please send the response to Samantha Gibbes (Samantha.C.Gibbes@saic.com) and Kayloni Ahtong (kayloni_ahtong@ios.doi.gov). Use the below template and fill in each part as best as possible, where the point of contact (POC) is the person responsible for the account.Reply Email Body: The (name of application) application requests the following user account and access to the IRWIN Data group.POC Name: First name Last name and titlePOC Email: Username: <>_irwin (choose a username, something short, followed by _irwin)Business Justification: Once you are set up with the account, I will coordinate a call to go over any questions.

This lesson steps you through sharing spatial data from ArcGIS Pro as a Web Feature Layer.

Learn state-of-the-art skills to build compelling, useful, and fun Web GIS apps easily, with no programming experience required.Building on the foundation of the previous three editions, Getting to Know Web GIS, fourth edition,features the latest advances in Esri’s entire Web GIS platform, from the cloud server side to the client side.Discover and apply what’s new in ArcGIS Online, ArcGIS Enterprise, Map Viewer, Esri StoryMaps, Web AppBuilder, ArcGIS Survey123, and more.Learn about recent Web GIS products such as ArcGIS Experience Builder, ArcGIS Indoors, and ArcGIS QuickCapture. Understand updates in mobile GIS such as ArcGIS Collector and AuGeo, and then build your own web apps.Further your knowledge and skills with detailed sections and chapters on ArcGIS Dashboards, ArcGIS Analytics for the Internet of Things, online spatial analysis, image services, 3D web scenes, ArcGIS API for JavaScript, and best practices in Web GIS.Each chapter is written for immediate productivity with a good balance of principles and hands-on exercises and includes:A conceptual discussion section to give you the big picture and principles,A detailed tutorial section with step-by-step instructions,A Q/A section to answer common questions,An assignment section to reinforce your comprehension, andA list of resources with more information.Ideal for classroom lab work and on-the-job training for GIS students, instructors, GIS analysts, managers, web developers, and other professionals, Getting to Know Web GIS, fourth edition, uses a holistic approach to systematically teach the breadth of the Esri Geospatial Cloud.AUDIENCEProfessional and scholarly. College/higher education. General/trade.AUTHOR BIOPinde Fu leads the ArcGIS Platform Engineering team at Esri Professional Services and teaches at universities including Harvard University Extension School. His specialties include web and mobile GIS technologies and applications in various industries. Several of his projects have won specialachievement awards. Fu is the lead author of Web GIS: Principles and Applications (Esri Press, 2010).Pub Date: Print: 7/21/2020 Digital: 6/16/2020 Format: Trade paperISBN: Print: 9781589485921 Digital: 9781589485938 Trim: 7.5 x 9 in.Price: Print: $94.99 USD Digital: $94.99 USD Pages: 490TABLE OF CONTENTSPrefaceForeword1 Get started with Web GIS2 Hosted feature layers and storytelling with GIS3 Web AppBuilder for ArcGIS and ArcGIS Experience Builder4 Mobile GIS5 Tile layers and on-premises Web GIS6 Spatial temporal data and real-time GIS7 3D web scenes8 Spatial analysis and geoprocessing9 Image service and online raster analysis10 Web GIS programming with ArcGIS API for JavaScriptPinde Fu | Interview with Esri Press | 2020-07-10 | 15:56 | Link.

Renowned for its natural and man-made beauty, the historic city of Venice spans a series of islands in a shallow lagoon. Venice’s unique geography has a downside, however. Tidal patterns mix with low elevation to cause acqua alta (high water), a periodic flooding that, although not dangerous to human life, impedes transportation and endangers Venice’s priceless architecture.This layer package includes three layers. The Structures layer contains building footprint data. The Canals layer contains Venice's canals. The Landmarks layer contains famous landmarks throughout the city. The data was acquired from Comune di Venezia - Portale dei servizi in 2014.This layer package contains feature class data on Venice's landmarks, canals, and structures for the tutorial Map Venice in 2D. The data will be used to visualize the landscape of Venice.

The U.S. Fish & Wildlife Service manages commercial guiding and hunting activities within the National Wildlife Refuges in the State of Alaska. To aid in management, the Service has established Guide Use Areas (GUA). This feature layer depicts the GUAs within the Alaska national wildlife refuges.

Published to allow joining of spreadsheet data to county geometry in ESRI Maps for Office or Map Analysis Tools, contains Iowa DOM County Code (1-99) as a small integer, Census County FIPS as a both an string and integer. This data was originally created by the Iowa DNR and digitized from USGS 7.5' topographic maps.Click on the data tab above to see an example of expected data. OCIO has a tutorial on how to join your spreadsheet to this Feature layer to create a new feature layer with your county based information. Please contact patrick.wilke-brown@iowa.gov.

Feature layer generated from the Current Weather and Wind Station Data Living Atlas layer for the Learn ArcGIS lesson Predict weather with real-time data.

Feature layer generated from running the Overlay layers solution.

Feature layer for the tutorial Analyze volcano shelter access in Hawaii.This layer is a copy of the Volcano Lava Flow Hazard Zones by HawaiiStateGIS.The boundaries and classification of lava flow hazard zones on Hawaii Island were first mapped by the US Geological Survey in 1974. This classification scheme divides the island into 18 major zones that are ranked from 1 through 9 based on the probability of coverage by lava flows. The risk levels are based primarily on the location and frequency of historic eruptions (those for which there are written records or that are known from the oral traditions of the Hawaiians) and the geologic mapping and scientific dating of the old flows from prehistoric eruptions.Much of the USGS work was based on a paper called Geologic Map of the Island of Hawaii by Edward Wolfe and Jean Morris.

Feature layer generated from running the Enrich layer solution. Hexagons_within_VA were enriched

Gridded SSURGO (gSSURGO) is similar to the standard product from the United States Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Soil Survey Geographic (SSURGO) Database, but is in the Environmental Systems Research Institute, Inc. (ESRI®) file geodatabase format. A file geodatabase has the capacity to store significantly more data and thus greater spatial extents than the traditional SSURGO product. This allows for statewide or even Conterminous United States (CONUS) tiling of data. gSSURGO contains all of the original soil attribute tables in SSURGO. All spatial data are stored within the geodatabase instead of externally as separate shape files. Both SSURGO and gSSURGO are considered products of the National Cooperative Soil Survey (NCSS). An important addition to the new format is a 10-meter raster (MapunitRaster_10m) of the map unit soil polygons feature class, which provides statewide coverage in a single layer. The CONUS database includes a 30-meter raster because of size constraints. This new addition provides greater performance and important analysis capabilities to users of soils data. Statewide tiles consist of soil survey areas needed to provide full coverage for a given State. In order to create a true statewide soils layer, some clipping of excess soil survey area gSSURGO data may be required. The new format also includes a national Value Added Look Up (valu) Table that has several new “ready to map” attributes.Other Documents to Reference:gSSURGO FactsheetgSSURGO User Guide ArcMap version 2.4Soil Data Development Toolbox User Guide v5 for ArcMapgSSURGO Mapping Detailed GuidegSSURGO Valu1 table column descriptions

This StoryMap describes the neighborhoods in Nashville and provides information on nearby apartments, restaurants, and points of interest.Nashville is one of the country's fastest growing cities. From music to healthcare, Nashville has seen an abundance of development in recent years. In 2023, 86 residents per day were moving to Nashville, and 18.6 million tourists visited the city [1].The first interactive feature will walk you through 11 neighborhoods found in Nashville. It was created using the “map tour” feature and walks you around a map of Nashville (created by me) while displaying the location and information. The information describes the ambience of each neighborhood as well as what they are known for and who typically lives in the area. All the information was provided by Nashville Guru [2]. Next, the story continues with rent for these locations. The values reflect the costs for studio/one-bedroom apartments. These costs were calculated using the Summary Statistics feature in ArcGIS Pro, which were then plotted in the chart seen in this StoryMap. After displaying the average values, there is a map of the individual apartments’ locations (created by me) with pop-ups showing the building name, starting rent, pool, and website link. This map and its pop-ups were created by me in ArcGIS Pro and then uploaded as a web map into ArcGIS Online. It utilizes an Experience Builder to allow you to filter through and focus on the apartments in each neighborhood. All of the information is available on apartments.com [3]. The next map dictates some restaurants in the area. The original feature layer was created by NNRobbins11 [4]. A spatial query was performed in ArcGIS pro by joining this restaurants layer to neighborhoods within a 1-mile distance. Like the apartments map, a filter is attached so that you may select a neighborhood. This allows you to select a neighborhood and then view the closest restaurants. There is also a pull-up arrow located at the bottom of this experience to allow users to view the pop-ups in table form.Finally, a sidecar is used to show the locations and information about local attractions. The map was created by me in ArcGIS Pro and shows 10 features with a name, description, and image. The description and image are shown in the left sidecar. All of this information is available in Nashville Guru [5]. The final video provides a live look of Nashville from a drone’s perspective [6]. Sources:[1] https://www.govloop.com/community/blog/the-enterprise-tech-driving-nashvilles-historic-growth/[2] https://nashvilleguru.com/neighborhoods[3] https://www.apartments.com/nashville-tn/?msockid=2dcf432ac6f36e722d9956e7c76a6fa7[4] https://services3.arcgis.com/58WV6GqBWodG9Kll/arcgis/rest/services/Nashville_Eateries/FeatureServer[5] https://nashvilleguru.com/[6] https://www.bing.com/videos/riverview/relatedvideo?&q=nashville+birds+eye+video&&mid=2489D5A39FFFCAE7A92B2489D5A39FFFCAE7A92B&&FORM=VRDGAR

The U.S. Fish & Wildlife Service manages commercial guiding and hunting activities within the National Wildlife Refuges in the State of Alaska. To aid in management, the Service has established Guide Use Areas (GUA). This feature layer depicts the GUAs within the Alaska national wildlife refuges.

When talking about creating a better future, it is inevitable to bring up the topic of climate change, and more specifically, global warming. One of the most pressing issues facing society, global warming may put an end to our future, if we don't act soon.ProcessBuilding on my work on biodiversity last year, I delve deeper into a new issue, Global Warming. This year I focused on the projected impacts of global warming on Missouri. The StoryMap analyzes the projected temperatures, projected precipitation levels, farm sales, corn production, and calculations necessary to suggest possible differences between now and the future.To start, I needed to complete some tutorials teaching me how to use the multidimensional analysis filter on ArcGIS to provide raster projection data. I also needed to complete a tutorial teaching how to make a swipe map as an instant application. After completing these two things, I began putting my new skills to work building maps. After creating the basic outline for my StoryMap, I began creating the maps I would need to illustrate the difference between the 2030 projections and the 2090 projections. To do this, I first filtered down a nationwide layer depicting all the county boundaries to just Missouri. I then took a Bioclimate Projection raster layer, and aggregated the Missouri data by county, summarizing it utilizing a zonal statistics table. I then input the data into Microsoft Excel, and created a pivot table, which gave me a table with county names as the rows, and 12 columns for each of the 4 time zones associated with each of the 3 variables. I exported this file as a CSV into my maps on ArcGIS, and joined the filtered down county feature with this CSV, joining the two by county name. This created a layer of Missouri counties in which I could represent each of the 12 different scenarios by changing which one I wanted to display. As a final added layer of analysis, I created a calculated column showing the change from 2030-2090 across the worst case scenario. This method of analysis was used for both temperature and precipitation projections.The other non-temperature-based maps were created using LivingAtlas filters on ArcGIS online. These maps were the farming sales map, the national corn production map, and the Missouri specific corn production map. Finally, express maps were created to point out movement of crops and pinpoint locations that I would talk about later. There are two of these within this project.Content SourcesAll map layers were derived from ArcGIS Online and the other community layers on ArcGIS.com.Base layers were provided by ArcGIS Online.All other sources of content have been hyperlinked to the text in which they apply to.Content AnalysisTo analyze my content, I created a web map or story map including all the relevant layers, maps, and information about global warming in order to display the projected disastrous effects it could have on the people of Missouri and Missouri's economy. A major player in content analysis was the swipe map, which easily allows the reader to view the differences between two different time period, one in the near future and one in the far future. Using the same color ramp that has the same minimum and maximum values for temperature or precipitation within these swipe maps adds another layer of analysis.Original DataTo complete my original data requirements for this project, I used the multidimensional filter to understand projections for the data. I also aggregated the Bioclimate Projection data to Missouri Counties, using zonal statistics tables. By joining a nationwide county boundary layer I filtered down to Missouri only, and a CSV created by making a pivot table out of the aggregated Bioclimate Projection data, I created another piece of original data. My final piece of original data was the line graph used to analyze the 3 different scenarios for temperature projections.CreditsThanks to Paul Hoelscher, AP World teacher at Clayton High School for serving as the school coordinator for this project. Also thanks to Dr. Bob Coulter for serving as my GeoMentor for this project and providing technical support with ArcGIS Online. Finally, thanks to my parents for coordinating project meetings, and supporting my work on this project.

Uniform Coding UnitsPrior to 1982, Alaska Department of Fish and Game - Division of Wildlife Conservation (ADFG-DWC) had a variety of coding schemes (18) relating harvest and management information to geographical areas. This made it difficult when comparing statewide wildlife information gathered across the state. In 1982, a new standardized statewide, geographically-based, hierarchy system of coding was created called the Uniform Coding Unit or UCU system. Game management units (GMUs), Subunits, and uniform coding units (UCUs) are the underlying geographic foundation of the wildlife and habitat management and regulations for ADFG-DWC. The GMU/UCU system consists of five Regions which are divided into twenty-six (26) Game Management Units (GMUs). Many of the GMUs are divided into Subunits (e.g. GMU 15 has three (3) Subunits, 15A, 15B, and 15C). GMUs that are not divided into subunits have a "Z" designation for the subunit. GMUs and Subunits are further divided into Major Drainages, Minor Drainages and Specific Areas. The smallest of these areas (down to the "specific area") is referred to as a Uniform Coding Unit (UCU) and has a unique 10 character code associated with it. (NOTE: UCU layer is for internal and official use only, not for public use or distribution). The UCU code is used for geographically classifying harvest and management information. Data that cannot be tied to a specific code can be generalized to the next higher level of the hierarchy. For example:a location description that is within multiple "specific areas" within a "minor drainage" can be coded to the minor code with a "00" for the specific area. Unknown "minor drainages" can be coded to the "major drainage" level, etc. If the subunit is unknown or the area covers multiple subunits within a unit, the subunit can be specified as a "Z" code (e.g. an area within subunits 15A and 15B could be recorded as 15Z). If a geographic location covers multiple units or the unit is unknown, the most general code (statewide code) is recorded as 27Z-Z00. The original hardcopy master maps were drawn to portray the UCUs fairly accurately geographically, but were not necessarily precisely drawn (i.e. left vs. right bank of a river, or exact ridge line). Each UCU was represented by drawing boundaries on USGS 1:250,000 scale quadrangle maps with a thick magic marker. A list (database) of place-names and their corresponding UCU codes was created and is still used today to assign permit, harvest, and sealing information to one of these geographic areas. In 1988, the UCU boundaries were digitized (traced) from the original maps into a computerized Geographic Information System (ArcInfo). Minor changes were made in 1989. Phase I2006-2008 - initial clean-up of boundaries for GMU 6, 9, 10, 12, 16, 19, 20, 25. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Jan 2009 - Priority has shifted to getting the bulk of the updates into the master. Verification and modifications based on the UCU list and the AB corrections will come at a later date. This shift is to attempt to get the master into a permanent SDE GDB, set it up with the GDB topology, make additional clean-up/edits using the GDB tools, set up versioning, make it easier to replicate to area offices, and to take advantage of the tools/features available thru ArcGIS Server with versioned GDBs. June 2009 - initial clean-up of boundaries for Southeast (GMU 1-5), GMU 17, and GMU 18. These have NOT been verified against the UCU master list or by area biologists. -ras July 1 2009 - initial clean-up of boundaries for GMU 7 and 8. Also some adjustments for 25D based on the NHD 2008 version and ArcHydro Tools "raindrop" feature. These have NOT been verified against the UCU master list or by area biologists. -ras Sept 17, 2009 - initial clean-up of boundaries for GMU 13. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Oct 21, 2009 - initial clean-up of boundaries for GMU 14 These modification have NOT been verified against the UCU master list or by area biologists. -rasNov 19, 2009 - initial clean-up of boundaries for GMU 15. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Dec 7, 2009 - initial clean-up of boundaries for GMU 22. These modification have NOT been verified against the UCU master list or by area biologists. -ras March 3, 2010 - initial clean-up of boundaries for GMU 23. These modification have NOT been verified against the UCU master list or by area biologists. -rasApril 10, 2010 - initial clean-up of boundaries for GMU 26. These modification have NOT been verified against the UCU master list or by area biologists. -ras May 2010 - This completes Phase I of refining the UCUs - bulk heads-up re-digitizing of all arcs. Phase II - Converting and establishing procedures for maintaining the master in an Enterprise GDB is underway. Complete.Phase III- Continued maintenance as needed or as modified via the Board of Game process:Game Management changes:Effective July 1, 2006 - GMU 24 is now divided up into four subunit 24A, 24B, 24C, 24D. - GMU 21A and 21B - - boundary has been modifiedEffective July 1, 2010, Region II was split into Region 2 (GMU's 6, 7, 8, 14C, 15) and Region 4 (GMU's 9, 10, 11, 13, 14AB, 16, 17. This version was updated to reflect the change. An archive of the previous version (with Regions I, II, III, and V) is available on request as GMUMaster_063010. 2012 - minor updates continue as needed and time allows, and as newer base maps are used2014 - minor updates continue as needed, including updates to domain listings (not affecting GIS geometry)Effective July 1, 2014- revision to GMU 18/19/21 boundary to clarify/correct previous insufficient boundary description. Passed during Spring 2014 Board of Game.Effective July 1, 2016- revision to GMU 15 (Region II) and GMU 16 (Region IV). Kalgin Island (and surrounding waters) has been recoded from 16B-O00-1901 to 15B-O00-1901 This change will modify the area caluculations for Regions II and IV, Units 15 and 16, Subunits 16B and 15B, etc. GIS domains have been updated.Historical harvest information may not reflect these (or any) GMU modifications.