This tutorial will teach you how to take time-series data from many field sites and create a shareable online map, where clicking on a field location brings you to a page with interactive graph(s).

The tutorial can be completed with a sample dataset (provided via a Google Drive link within the document) or with your own time-series data from multiple field sites.

Part 1 covers how to make interactive graphs in Google Data Studio and Part 2 covers how to link data pages to an interactive map with ArcGIS Online. The tutorial will take 1-2 hours to complete.

An example interactive map and data portal can be found at: https://temple.maps.arcgis.com/apps/View/index.html?appid=a259e4ec88c94ddfbf3528dc8a5d77e8

Total file size: about 367M in zip format and about 600M after extracted. (To download: click the Download button at the upper right area of this page)Alternatively, you can download the data by chapters:- Go to https://go.esri.com/gtkwebgis4- Under Group Categories on the left, click each chapter, you will see the data file to download for that chapter.

This tutorial focuses on some of the tools you can access in ArcGIS Online that cover proximity and hot spot analysis. This resource is part of the Career Path Series - GIS for Crime Analysis Lesson.Find other resources at k12.esri.ca/resourcefinder.

Learn how to add points, lines and polygons within a sketch layer in the ArcGIS Online Map Viewer.

This quick introductory tutorial allows you to discover some of the basic tasks in ArcGIS Online.Find more resources at k12.esri.ca/resourcefinder.

In this seminar, you will learn about the spatial analysis tools built directly into the ArcGIS.com map viewer. You will learn of the spatial analysis capabilities in ArcGIS Online for Organizations, whether for analyzing your own data, data that's publicly available on ArcGIS Online, or a combination of both. You will learn the overall features and benefits of ArcGIS Online Analysis, how to get started, and how to choose the right approach in order to solve a specific spatial problem.

In this tutorial, you will explore some of the analysis tools that are available in ArcGIS Online. You will analyze the patterns of earthquakes that have occurred in Canada in 2017 with a magnitude of 2.5 or more on the Richter scale, you will discover which major cities in Canada fall within 50 km of these earthquakes, you will find out which province these major cities belong to, and you will consider factors that contribute to the presence of earthquakes and the effect they can have on the human and physical environment.Find more Esri Canada Education resources at k12.esri.ca/resourcefinder.

This resource contains the test data for the GeoServer OGC Web Services tutorials for various GIS applications including ArcGIS Pro, ArcMap, ArcGIS Story Maps, and QGIS. The contents of the data include a polygon shapefile, a polyline shapefile, a point shapefile, and a raster dataset; all of which pertain to the state of Utah, USA. The polygon shapefile is of every county in the state of Utah. The polyline is of every trail in the state of Utah. The point shapefile is the current list of GNIS place names in the state of Utah. The raster dataset covers a region in the center of the state of Utah. All datasets are projected to NAD 1983 Zone 12N.

This seminar is an applied study of deep learning methods for extracting information from geospatial data, such as aerial imagery, multispectral imagery, digital terrain data, and other digital cartographic representations. We first provide an introduction and conceptualization of artificial neural networks (ANNs). Next, we explore appropriate loss and assessment metrics for different use cases followed by the tensor data model, which is central to applying deep learning methods. Convolutional neural networks (CNNs) are then conceptualized with scene classification use cases. Lastly, we explore semantic segmentation, object detection, and instance segmentation. The primary focus of this course is semantic segmenation for pixel-level classification. The associated GitHub repo provides a series of applied examples. We hope to continue to add examples as methods and technologies further develop. These examples make use of a vareity of datasets (e.g., SAT-6, topoDL, Inria, LandCover.ai, vfillDL, and wvlcDL). Please see the repo for links to the data and associated papers. All examples have associated videos that walk through the process, which are also linked to the repo. A variety of deep learning architectures are explored including UNet, UNet++, DeepLabv3+, and Mask R-CNN. Currenlty, two examples use ArcGIS Pro and require no coding. The remaining five examples require coding and make use of PyTorch, Python, and R within the RStudio IDE. It is assumed that you have prior knowledge of coding in the Python and R enviroinments. If you do not have experience coding, please take a look at our Open-Source GIScience and Open-Source Spatial Analytics (R) courses, which explore coding in Python and R, respectively. After completing this seminar you will be able to: explain how ANNs work including weights, bias, activation, and optimization. describe and explain different loss and assessment metrics and determine appropriate use cases. use the tensor data model to represent data as input for deep learning. explain how CNNs work including convolutional operations/layers, kernel size, stride, padding, max pooling, activation, and batch normalization. use PyTorch, Python, and R to prepare data, produce and assess scene classification models, and infer to new data. explain common semantic segmentation architectures and how these methods allow for pixel-level classification and how they are different from traditional CNNs. use PyTorch, Python, and R (or ArcGIS Pro) to prepare data, produce and assess semantic segmentation models, and infer to new data.

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

Mapping Our World Using GIS is a 1:1 set of instructional materials for teaching basic concepts found in middle school world geography. Each module consists of multiple files.

The Mapping Our World collection is at: http://esriurl.com/MOW.

All Esri GeoInquiries can be found at: http://www.esri.com/geoinquiries

        This computer activity will show you how to start the ArcGIS Online program. You will be guided

through the basics of using ArcGIS Online map viewer to explore maps. After you do this activity, you will be prepared to complete other GIS activities.

In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.

This story map explains how to use two attributes to make a map using both color and size using the smart mapping capability within ArcGIS Online and ArcGIS Enterprise. You can easily select two attributes, and one will be shown in your map using color, while the other will be used to represent size. This mapping technique can help to show relationships you might not have known existed. This method can also help turn multiple maps into a single map to share with others. This story map walks you through multiple examples, which can help get you started with smart mapping color and size.

Public Information is a configuration of Web AppBuilder for ArcGIS that can be used by the public to review authoritative emergency information and understand the status of an incident or event.

Tutorial Audience: GIS / Technology SpecialistsEnd User Audience: Emergency Management Planning and Operations Staff

Problem: The Public needs situational awareness as much as emergency managers and first responders. They want answers to questions like – Do I need to evacuate? Where can I go for more information or protection? How do I get there / are there any road closures?Solution: Public Information Web Mapping ApplicationRequirements: You will need a license for ArcGIS Online to complete this tutorial.Note: This tutorial works with the Operations Response Tutorial.

PurposeThis job aid will lead the GIS analyst through the process of manually creating an incident map journal and how to create additional pages for the journal. This process should be used at the beginning of an incident and then the journal should be maintained to assure it remains viable. The incident map journal serves as a curated center to place maps, apps, and dashboards relevant to the incident.

This job aid assumes a working knowledge of how to create maps, apps, and dashboards on ArcGIS Online. For a tutorial, go to the Create apps from maps - ArcGIS Tutorial.Example workflow for the Geo-Enabled Plans Session at InSPIRE. Job Aid developed by FEMA GIS to enable GIS analysts to rapidly spin-up a standardized incident journal.

Important Note: This item is in mature support as of February 2023 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. This layer displays change in pixels of the Sentinel-2 10m Land Use/Land Cover product developed by Esri, Impact Observatory, and Microsoft. Available years to compare with 2021 are 2018, 2019 and 2020. By default, the layer shows all comparisons together, in effect showing what changed 2018-2021. But the layer may be changed to show one of three specific pairs of years, 2018-2021, 2019-2021, or 2020-2021.Showing just one pair of years in ArcGIS Online Map ViewerTo show just one pair of years in ArcGIS Online Map viewer, create a filter. 1. Click the filter button. 2. Next, click add expression. 3. In the expression dialogue, specify a pair of years with the ProductName attribute. Use the following example in your expression dialogue to show only places that changed between 2020 and 2021:ProductNameis2020-2021By default, places that do not change appear as a transparent symbol in ArcGIS Pro. But in ArcGIS Online Map Viewer, a transparent symbol may need to be set for these places after a filter is chosen. To do this:4. Click the styles button. 5. Under unique values click style options. 6. Click the symbol next to No Change at the bottom of the legend. 7. Click the slider next to "enable fill" to turn the symbol off.Showing just one pair of years in ArcGIS ProTo show just one pair of years in ArcGIS Pro, choose one of the layer's processing templates to single out a particular pair of years. The processing template applies a definition query that works in ArcGIS Pro. 1. To choose a processing template, right click the layer in the table of contents for ArcGIS Pro and choose properties. 2. In the dialogue that comes up, choose the tab that says processing templates. 3. On the right where it says processing template, choose the pair of years you would like to display. The processing template will stay applied for any analysis you may want to perform as well.How the change layer was created, combining LULC classes from two yearsImpact Observatory, Esri, and Microsoft used artificial intelligence to classify the world in 10 Land Use/Land Cover (LULC) classes for the years 2017-2021. Mosaics serve the following sets of change rasters in a single global layer: Change between 2018 and 2021Change between 2019 and 2021Change between 2020 and 2021To make this change layer, Esri used an arithmetic operation combining the cells from a source year and 2021 to make a change index value. ((from year * 16) + to year) In the example of the change between 2020 and 2021, the from year (2020) was multiplied by 16, then added to the to year (2021). Then the combined number is served as an index in an 8 bit unsigned mosaic with an attribute table which describes what changed or did not change in that timeframe. Variable mapped: Change in land cover between 2018, 2019, or 2020 and 2021 Data Projection: Universal Transverse Mercator (UTM)Mosaic Projection: WGS84Extent: GlobalSource imagery: Sentinel-2Cell Size: 10m (0.00008983152098239751 degrees)Type: ThematicSource: Esri Inc.Publication date: January 2022What can you do with this layer?Global LULC maps provide information on conservation planning, food security, and hydrologic modeling, among other things. This dataset can be used to visualize land cover anywhere on Earth. This layer can also be used in analyses that require land cover input. For example, the Zonal Statistics tools allow a user to understand the composition of a specified area by reporting the total estimates for each of the classes. Land Cover processingThis map was produced by a deep learning model trained using over 5 billion hand-labeled Sentinel-2 pixels, sampled from over 20,000 sites distributed across all major biomes of the world. The underlying deep learning model uses 6 bands of Sentinel-2 surface reflectance data: visible blue, green, red, near infrared, and two shortwave infrared bands. To create the final map, the model is run on multiple dates of imagery throughout the year, and the outputs are composited into a final representative map. Processing platformSentinel-2 L2A/B data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch.Class definitions1. WaterAreas where water was predominantly present throughout the year; may not cover areas with sporadic or ephemeral water; contains little to no sparse vegetation, no rock outcrop nor built up features like docks; examples: rivers, ponds, lakes, oceans, flooded salt plains.2. TreesAny significant clustering of tall (~15-m or higher) dense vegetation, typically with a closed or dense canopy; examples: wooded vegetation,
clusters of dense tall vegetation within savannas, plantations, swamp or mangroves (dense/tall vegetation with ephemeral water or canopy too thick to detect water underneath).4. Flooded vegetationAreas of any type of vegetation with obvious intermixing of water throughout a majority of the year; seasonally flooded area that is a mix of grass/shrub/trees/bare ground; examples: flooded mangroves, emergent vegetation, rice paddies and other heavily irrigated and inundated agriculture.5. CropsHuman planted/plotted cereals, grasses, and crops not at tree height; examples: corn, wheat, soy, fallow plots of structured land.7. Built AreaHuman made structures; major road and rail networks; large homogenous impervious surfaces including parking structures, office buildings and residential housing; examples: houses, dense villages / towns / cities, paved roads, asphalt.8. Bare groundAreas of rock or soil with very sparse to no vegetation for the entire year; large areas of sand and deserts with no to little vegetation; examples: exposed rock or soil, desert and sand dunes, dry salt flats/pans, dried lake beds, mines.9. Snow/IceLarge homogenous areas of permanent snow or ice, typically only in mountain areas or highest latitudes; examples: glaciers, permanent snowpack, snow fields. 10. CloudsNo land cover information due to persistent cloud cover.11. Rangeland Open areas covered in homogenous grasses with little to no taller vegetation; wild cereals and grasses with no obvious human plotting (i.e., not a plotted field); examples: natural meadows and fields with sparse to no tree cover, open savanna with few to no trees, parks/golf courses/lawns, pastures. Mix of small clusters of plants or single plants dispersed on a landscape that shows exposed soil or rock; scrub-filled clearings within dense forests that are clearly not taller than trees; examples: moderate to sparse cover of bushes, shrubs and tufts of grass, savannas with very sparse grasses, trees or other plants.CitationKarra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021.AcknowledgementsTraining data for this project makes use of the National Geographic Society Dynamic World training dataset, produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.For questions please email environment@esri.com

Crowdsourcing is a way to obtain information from the public by enlisting the services of the general public or volunteers via the Internet. This can be a valuable source of information during a disaster if it is done in a way that answers important questions, for instance:

• Where are roads obstructed by standing water?

• What homes have individuals that need assistance evacuating?

• Where are debris that needs to be removed?

Tutorial Audience: GIS / Technology SpecialistsEnd User Audience: Emergency Management Planning and Operations Staff

Problem: The emergency management agency has requested that you prepare a crowdsourcing solution in advance of the next disaster. The data collected must be structured in a way so that it is informative and actionable for decision makers. Your crowdsourcing app should be:

• Fast and easy to use for the Public.

• The database behind it should contain structured information that answers specific questions for emergency managers (e.g. Where are the hazards? How severe is it? Where should we focus our resources?).

• Allows for submitting attachments such as photos.

Solution: Survey123 Web FormRequirements: You will need a license for ArcGIS Online to complete this tutorial.Note: This tutorial works with the Public Information Application Tutorial.

Pop-ups allow you to highlight attribute information in a web map. In this tutorial, you will learn how to create a web map and configure pop-ups in ArcGIS Online.

On January 25, 2018 FEMA replaced this map with a new NFHL map with additional functionality which allows users to print official flood maps. On April 1, 2018 this map and NFHL link will no longer function. Please update your bookmark to https://hazards-fema.maps.arcgis.com/apps/webappviewer/index.html?id=8b0adb51996444d4879338b5529aa9cd. For more information on NFHL data availability, please visit the NFHL GIS Services page at https://hazards.fema.gov/femaportal/wps/portal/NFHLWMSAs of August 1, 2017 all FEMA systems will require the use of the “https” protocol, and “http” links will no longer function. This may impact NFHL web services. The FEMA GeoPlatform (including this map) will not be affected by this change. For more information on how NFHL GIS services will be impacted, please visit the NFHL GIS Services page at https://hazards.fema.gov/femaportal/wps/portal/NFHLWMS.An NFHL FIRMette print service is now available HERE. (For a video tutorial, click here.)OverviewThe National Flood Hazard Layer (NFHL) dataset represents the current effective flood data for the country, where maps have been modernized. It is a compilation of effective Flood Insurance Rate Map (FIRM) databases and Letters of Map Change (LOMCs). The NFHL is updated as studies go effective. For more information, visit FEMA's Map Service Center (MSC). Base Map ConsiderationsThe default base map is from a USGS service and conforms to FEMA's specification for horizontal accuracy. This base map from The National Map (TNM) consists of National Agriculture Imagery Program (NAIP) and high resolution orthoimagery (HRO) that combine the visual attributes of an aerial photograph with the spatial accuracy and reliability of a map. This map should be considered the best online resource to use for official National Flood Insurance Program (NFIP) purposes when determining locations in relation to regulatory flood hazard information. If a different base map is used with the NFHL, the accuracy specification may not be met and the resulting map should be used for general reference only, and not official NFIP purposes. Users can download a simplified base map from the USGS service via: https://viewer.nationalmap.gov/services/ For the specifics of FEMA’s policy on the use of digital flood hazard data for NFIP purposes see: http://www.fema.gov/library/viewRecord.do?id=3235Letter of Map Amendment (LOMA) pointsLOMA point locations are approximate. The location of the LOMA is referenced in the legal description of the letter itself. Click the LOMA point for a link to the letter (use the arrows at the top of the popup window to bring up the LOMA info, if needed).This LOMA database may include LOMAs that are no longer effective. To be certain a particular LOMA is currently valid, please check relevant documentation at https://msc.fema.gov/ . Relevant documents can be found for a particular community by choosing to "Search All Products", and finding the community by State and County. Documents include LOMAs found in the "Effective Products" and "LOMC" folders, as well as Revalidations (those LOMAs which are still considered to be effective after a map is revised).Updates3/27/2017 - Updated all references to https to prevent issues with mixed content.5/11/2016 - Added link to NFHL FIRMette Print Service. Updated LOMA and CBRS popup notes.2/20/2014 - Created a General Reference map for use when the USGS base map service is down. Renamed this map to "Official".Further InformationSpecific questions about FEMA flood maps can be directed to FEMAMapSpecialist@riskmapcds.comFor more flood map data, tool, and viewing options, visit the FEMA NFHL page. Information about connecting to web map services (REST, WMS, WFS) can be found here.Several fact sheets are available to help you learn more about FEMA’s NFHL utility: National Flood Hazard Layer (NFHL) GIS Services Users GuideNational Flood Hazard Layer (NFHL): New Products and Services for FEMA's Flood Hazard Map DataMoving to Digital Flood Hazard Information Standards for Flood Risk Analysis and MappingNFHL GIS Data: Perform Spatial Analyses and Make Custom Maps and Reports

Version françaiseIn this tutorial, you will learn tips and tricks for getting started with ArcGIS Online by completing six activities. Each activity takes approximately six minutes to complete.