There's a lot going on in marine aquaculture in the United States! NOAA, with its partners, plays a major role in developing environmentally and economically sustainable marine aquaculture practices, technologies and industry in the U.S. Marine aquaculture creates jobs, supports working waterfronts and coastal communities, provides new international trade opportunities, and provides a domestic source of sustainable seafood to complement our wild fisheries. Use this map to check out just some of the recent developments in the domestic marine aquaculture industry in your region, and how NOAA is involved. Click on the individual images to get project details, materials and links.

The Story Map Basic application is a simple map viewer with a minimalist user interface. Apart from the title bar, an optional legend, and a configurable search box the map fills the screen. Use this app to let your map speak for itself. Your users can click features on the map to get more information in pop-ups. The Story Map Basic application puts all the emphasis on your map, so it works best when your map has great cartography and tells a clear story.You can create a Basic story map by sharing a web map as an application from the map viewer. You can also click the 'Create a Web App' button on this page to create a story map with this application. Optionally, the application source code can be downloaded for further customization and hosted on your own web server.For more information about the Story Map Basic application, a step-by-step tutorial, and a gallery of examples, please see this page on the Esri Story Maps website.

The Story Maps, developed by the Joint Research Centre, the Commission's science and knowledge service, inform in an easily accessible way about several initiatives across Europe linked to cultural heritage. These include actions like the European Heritage Days, the EU Prize for Cultural Heritage or the European Heritage Label, funded by Creative Europe, the EU programme that supports the cultural and creative sectors. The website also contains links to the digital collections of Europeana – the EU digital platform for cultural heritage. This platform allows users to explore more than 50 million artworks, artefacts, books, videos and sounds from more than 3500 museums, galleries, libraries and archives across Europe. These maps will be updated and developed, for example taking into account tips from young people exploring Europe's cultural heritage through the new DiscoverEU initiative.

Presentation to the mid-term conference of the Canadian Historical GIS Partnership, June 20th 2016, discussing geovisualization techniques available in ArcGIS Online and Portal for ArcGIS and how they can be used for historical research. Topics included:Interactive map viewerSmart Mapping (demo)Time-enabled Web mapsConfigurable Web apps (including Time Aware)Story Map templates: Journal, Swipe, Tour, and Cascade (with hyperlinked examples)Combining configurable apps and Story Maps

This is an Expansion and Subset of the Internal Knowledge Map dataset that focuses on Story Writing and Role Playing. I was curious to see if I could adapt my IKM structure and approach to improve Story Telling, Role Playing/Character/Discourse in an LLM. Here are 2,071 highly-detailed and unique examples that allow an LLM to exhibit more depth, diverse perspectives and novel interactions. Side benefit is the LLM also writes in well-formed, aesthetically pleasing formatting and is an… See the full description on the dataset page: https://huggingface.co/datasets/Severian/Internal-Knowledge-Map-StoryWriter-RolePlaying.

The District of Columbia shares story maps that combine impacting narratives and multimedia with data and analytics. These examples support agency programs and help educate how DC is using its data.

General Accessibility Creative Commons All data products available from the data hub are provided on an 'as is' basis. The City of Sydney (City) makes no warranty, representation or guarantee of any type as to any errors and omissions, or as to the content, accuracy, timeliness, completeness or fitness for any particular purpose or use of any data product available from the data hub. If you find any information that you believe may be inaccurate, please email the City. In addition, please note that the data products available from the data hub are not intended to constitute advice and must not be used as a substitute for professional advice. The City may modify the data products available from the data hub and/or discontinue providing any or all of data products at any time and for any reason, without notice. Accordingly, the City recommends that you regularly check the data hub to ensure that the latest version of data products is used. The City recommends that when accessing data sets, you use APIs. We are committed to making our website as accessible and user-friendly as possible. Web Content Accessibility Guidelines (WCAG) cover a wide set of recommendations to make websites accessible. For more information on WCAG please visit https://www.w3.org/TR/WCAG21/ . This site is built using Esri's ArcGIS Hubs template, and their Accessibility status report is available online at https://hub.arcgis.com/pages/a11y. We create the maps and stories on this site using ArcGIS templates, each template having accessibility features. Examples include Instant Apps, Story maps, and Webapp builder. If you would like to request alternative formats for data products on this site please email the City. We encourage developers using our data to deliver maps and applications with consideration to accessibility for all. Design elements can include colour, contrast, symbol size and style, font size and style, basemap style, alternate text for images, and captions for video and audio. Alternative content such as static maps may sometimes be required. Unless otherwise stated, data products available from the data hub are published under Creative Commons licences. Creative Commons licences include terms and conditions about how licensed data products may be used, shared and/or adapted. Depending on the applicable licence, licensed data products may or may not be used for commercial purposes. The applicable Creative Commons licence for specific data is specified in the "Licence" section of the data description. By accessing, sharing and/or adapting licensed data products, you are deemed to have accepted the terms and conditions of the applicable Creative Common licence. For more information about Creative Commons licences, please visit https://creativecommons.org.au/ and https://creativecommons.org/faq/ If you believe that the applicable Creative Commons licence for the data product that you wish to use is overly restrictive for how you would like to use the data product, please email the City. Contact If you have a question, comments, or requests for interactive maps and data, we would love to hear from you. Council business For information on rates, development applications, strategies, reports and other council business, see the City of Sydney's main website.

About this itemStory Maps are a powerful platform that integrate spatial thinking with storytelling to present information in a compelling, interactive and easy to understand format. The University of Minnesota StoryMaps team provides support and resources for faculty looking to incorporate spatial tools such as StoryMaps, Survey 123 and other web-based GIS applications into their classrooms. The UMN StoryMaps site has examples of student projects, samples of project ideas/assignments/rubrics and user guides for students. This team’s work has received national recognition for promoting the role of spatial thinking and StoryMaps in higher education, K12 and informal learning spaces.Author/ContributorU-SpatialOrganizationUniversity of MinnesotaOrg Websitesystem.umn.edu

These interactive energy equity indicators are designed to help identify opportunities to improve access to clean energy technologies for low-income customers and disadvantaged communities; increase clean energy investment in those communities; and improve community resilience to grid outages and extreme events. A summary report of these indicators will be updated each year to track progress on implementation of the recommendations put forth by the Energy Commission’s December 2016 Low-Income Barriers Study mandated by Senate Bill 350 (de León, Chapter547, Statutes of 2015), and monitor performance of state-administered clean energy programs in low-income and disadvantaged communities across the state.Selected energy equity indicators are highlighted on the following California map. The base map highlights areas with median household income of $37,000 or less (60 percent of statewide median income for 2011-2015) and disadvantaged communities eligible for greenhouse gas reduction fund programs. The map also identifies tribal areas. Click to view data for low-income areas with low energy efficiency investments, low solar capacity per capita, or low clean vehicle rebate incentive investments. Additional data layers include high-density low-income areas and low-income areas that have many older buildings, as well as counties with high levels of asthma-related emergency room visit. This information can help identify opportunities for improving clean energy access, investment, and resilience in low-income and disadvantaged communities in California. Additional indicators are available by clicking on the Story Map or Tracking Progress Report links provided above.

This layer shows workers' place of residence by commute length. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of commuters whose commute is 90 minutes or more. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B08303Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Open the Data Resource: https://gis.chesapeakebay.net/viz/coastal/ This story map explains how 3-D landscape basecamps can be built, using an example that assesses the impacts of sea level rise on Norfolk, Virginia, within the context of global sea level rise.

This resources contains PDF files and Python notebook files that demonstrate how to create geospatial resources in HydroShare and how to use these resources through web services provided by the built-in HydroShare GeoServer instance. Geospatial resources can be consumed directly into ArcMap, ArcGIS, Story Maps, Quantum GIS (QGIS), Leaflet, and many other mapping environments. This provides HydroShare users with the ability to store data and retrieve it via services without needing to set up new data services. All tutorials cover how to add WMS and WFS connections. WCS connections are available for QGIS and are covered in the QGIS tutorial. The tutorials and examples provided here are intended to get the novice user up-to-speed with WMS and GeoServer, though we encourage users to read further on these topic using internet searches and other resources. Also included in this resource is a tutorial designed to that walk users through the process of creating a GeoServer connected resource.

The current list of available tutorials: - Creating a Resource - ArcGIS Pro - ArcMap - ArcGIS Story Maps - QGIS - IpyLeaflet - Folium

To create this app:Make a map of the AfDB projects CSV file in the Training Materials group.Download the CSV file, click Map (at the top of the page), and drag and drop the file onto your mapFrom the layer menu on your Projects layer choose Change Symbols and show the projects using Unique Symbols and the Status of field.Make a second map of the AfDB projects shown using Unique Symbols and the Sector field.HINT: Create a copy of your first map using Save As... and modify the copy.Assemble your story map on the Esri Story Maps websiteGo to storymaps.arcgis.comAt the top of the site, click AppsFind the Story Map Tabbed app and click Build a Tabbed Story MapFollow the instructions in the app builder. Add the maps you made in previous steps and copy the text from this sample app to your app. Explore and experiment with the app configuration settings.=============OPTIONAL - Make a third map of the AFDB projects summarized by country and add it to your story map.Add the World Countries layer to your map (Add > Search for Layers)From the layer menu on your Projects layer choose Perform Analysis > Summarize Data > Aggregate Points and run the tool to summarize the projects in each country.HINT: UNCHECK "Keep areas with no points"Experiment with changing the symbols and settings on your new layer and remove other unnecessary layers.Save AS... a new map.At the top of the site, click My Content.Find your story map application item, open its Details page, and click Configure App.Use the builder to add your third map and a description to the app and save it.

Story maps combine intelligent Web maps with Web applications and templates that incorporate text, multimedia, and interactive functions. Story maps inform, educate, entertain, and inspire people about a wide variety of topics.This web web map is used in the Austin Shortlist Sample story map application. You can view the blog post on how this map was used, and how you can author your own Shortlist story map.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the physical soil variable percent clay (clay).Within the subset of soil that is smaller than 2mm in size, also known as the fine earth portion, clay is defined as particles that are smaller than 0.002mm, making them only visible in an electron microscope. Clay soils contain low amounts of air, and water drains through them very slowly.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for percent clay are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Proportion of clay particles (< 0.002 mm) in the fine earth fraction in g/100g (%)Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for clay were used to create this layer. You may access the percent clay in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map: In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "world soils soilgrids" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "world soils soilgrids" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

Geoscience Australia’s Historical Aerial Photography Program currently involves scanning and georeferencing old flight diagrams to enable the digitising and positioning of historical aerial photographs for easy discovery and download. Accurate digital mapping of GA’s aerial photography collection will make catalogue searches easier and the collection more accessible to the public. This story map presents an interactive history of aerial photography, a background of aerial photography in Australia, historical aerial photography use cases and scenarios, and a background on Geoscience Australia's program to digitise flight diagrams and create a catalogue of aerial photographs.

This is number 1 of 3 data sets that accompany Open Data Maps Data Story on VA's Open Data Site.

Specifically this is a crosswalk data set that identifies VA facilities and their locations via postal address with zip codes and Latitude and Longitude information for facility geo plotting postal addresses. Facility location information as of 2018.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Purpose: This is an ArcGIS Pro template that GIS Specialists can use to identify vulnerable populations and special needs infrastructure most at risk to flooding events.How does it work?Determine and understand the Place Vulnerability (based on Cutter et al. 1997) and the Special Needs Infrastructure for an area of interest based on Special Flood Hazard Zones, Social Vulnerability Index, and the distribution of its Population and Housing units. The final product will be charts of the data distribution and a Hosted Feature Layer. See this Story Map example for a more detailed explanation.This uses the FEMA National Flood Hazard Layer as an input (although you can substitute your own flood hazard data), check availability for your County before beginning the Task: FEMA NFHL ViewerThe solution consists of several tasks that allow you to:Select an area of interest for your Place Vulnerability Analysis. Select a Hazard that may occur within your area of interest.Select the Social Vulnerability Index (SVI) features contained within your area of interest using the CDC’s Social Vulnerability Index (SVI) – 2016 overall SVI layer at the census tract level in the map.Determine and understand the Social Vulnerability Index for the hazard zones identified within you area of interest.Identify the Special Needs Infrastructure features located within the hazard zones identified within you area of interest.Share your data to ArcGIS Online as a Hosted Feature Layer.FIRST STEPS:Create a folder C:\GIS\ if you do not already have this folder created. (This is a suggested step as the ArcGIS Pro Tasks does not appear to keep relative paths)Download the ZIP file.Extract the ZIP file and save it to the C:\GIS\ location on your computer. Open the PlaceVulnerabilityAnalysis.aprx file.Once the Project file (.aprx) opens, we suggest the following setup to easily view the Tasks instructions, the Map and its Contents, and the Databases (.gdb) from the Catalog pane.The following public web map is included as a Template in the ArcGIS Pro solution file: Place Vulnerability Template Web MapNote 1:As this is a beta version, please take note of some pain points:Data input and output locations may need to be manually populated from the related workspaces (.gdb) or the tools may fail to run. Make sure to unzip/extract the file to the C:\GIS\ location on your computer to avoid issues.Switching from one step to the next may not be totally seamless yet.If you are experiencing any issues with the Flood Hazard Zones service provided, or if the data is not available for your area of interest, you can also download your Flood Hazard Zones data from the FEMA Flood Map Service Center. In the search, use the FEMA ID. Once downloaded, save the data in your project folder and use it as an input.Note 2:In this task, the default hazard being used are the National Flood Hazard Zones. If you would like to use a different hazard, you will need to add the new hazard layer to the map and update all query expressions accordingly.For questions, bug reports, or new requirements contact pdoherty@publicsafetygis.org

This activity is designed for small groups to work together in class to create a concept map based upon an ecological news story. Any short news story can be selected. One is provided here, along with a student concept map example.