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Blog Author: Emily Meriam     Originally Published: ArcGIS


Did you know that you can create custom Arcade expressions to define your symbol sizes at the varying ArcGIS Online map scales? The Arcade code demonstrated here on Esri’s “Recent Hurricane Live Feed will show you how to automatically resize your symbols as you zoom in and out of your map.



Within the Living Atlas is a “Recent Hurricane” layer that features tropical cyclone (hurricanes, typhoons, cyclones) tracks and positions from the past year for the Atlantic, Pacific, and Indian Basins. Esri hosts this data from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC).


For this example you will be copying these links:

1. Hurricane – Recent Observed Positions (point file) service is located:

2. Spinning Blue Hurricane (PNG symbol) is located:


Monitoring agencies worldwide use varying wind speed criteria and terminology for tropical cyclone classifications. The NHC and JTWC use the Saffir-Simpson Wind Scale to classify storms in the Western Hemisphere. This ranking system places storms with different wind speed thresholds (one-minute maximum sustained wind speed) into the following three classes:


Major (Devastating/Catastrophic)
Category 5 Hurricane: > 137 knots | >157 mph | >252 kmh
Category 4 Hurricane: 113-136 knots | 130-156 mph | 209-251 kmh
Category 3 Hurricane: 96-112 knots | 111-129 mph | 178-208 kmh


Very/Extremely Dangerous
Category 2 Hurricane: 83-95 knots | 96-110 mph | 154-177 kmh
Category 1 Hurricane: 64-82 knots | 74-95 mph | 119-153 kmh


Related Classifications
Tropical Depression: <33 knots| <38 mph | <62 kmh
Tropical Storm: 34-63 knots | 39-73 mph |63-118 kmh



There are standard symbols for hurricanes:



Standard symbols for Depression, Storm, and Hurricane.



Using the Saffir-Simpson Wind Scale classifications, Category 1-5 Hurricanes will be displayed with a hurricane symbol to differentiate them from Tropical Storms and Depressions.


As a cartographer I see some room for interpretation here. I decide to take the standard symbol and tweak it a bit, so it spins like a hurricane and add an eye. It needs life and vibrations like it is moving, but there also should be a nod to the original symbol.  This change makes a visual statement that could be immediately recognizable (abstractly it looks like a hurricane) to someone who is looking at the map and they may not need a legend to determine what the symbol is.


After (Filters in Photoshop)Before (Standard Symbol)


Classify the Hurricane Data in Arcade

1. Open a new web map and click on Add –> Add Layer from Web


Screen capture: Add Layer from Web



2. Paste in the link listed above for the Hurricane Recent – Observed Positions.


Screen Capture: Pasting in the link


3. By default, the service comes in with a basic symbol that all has the same classification.

This layer has an attribute called INTENSITY.   It measures wind speed in knots. Use this to classify the data in Arcade so it is symbolized uniformly with the Saffir-Simpson Wind Scale.  Click to “Change Style” on the point layer.


Screen Capture: Change Style of Symbol


4. Select “Choose an attribute to show” and select to create a “New Expression”.


Screen Capture: Adding a New Expression


5. Edit the “Name” (by default it says Custom) at the top to say: Assign Storm Type (Saffir) by Intensity

6. Place this code in the Arcade window:


When(INTENSITY>=137,”Category 5 Hurricane”,
INTENSITY<137&&INTENSITY>112, “Category 4 Hurricane”,
INTENSITY<=112&&INTENSITY>95, “Category 3 Hurricane”,
INTENSITY<=95&&INTENSITY>82,”Category 2 Hurricane”,
INTENSITY<=82&&INTENSITY>63, “Category 1 Hurricane”,
INTENSITY<=63&&INTENSITY>33, “Tropical Storm”,
INTENSITY<=33&&INTENSITY>=0, “Tropical Depression”, “NO DATA”)

7. It looks like:


Screen Capture: Arcade Code for Assign Storm Tyre (Saffir) by Intensity


8. What the code is saying: When the wind speed intensity is between this number and that number, identify it as this type of storm.

9. Click “OK”

10. Because of this Arcade expression, the data is now classified and is immediately prompting you to “Select a drawing style”. Select “Types (Unique Symbols)” and click on “Options”.


Screen Capture: Click on Options



I love that I can use my own custom made symbols (transparent PNG images) in ArcGIS Online!  It is so easy to create my own symbols, upload them to my account, share them publicly, and then use them on my maps!

1. First rearrange all your points into the proper order (Category 5-1, Tropical Storm, Tropical Depression) by dragging them up and down while hovering the mouse over the three dots on the left side.

2. Next click on the default symbol for Category 5 Hurricane and Select –> Shapes (drop-down menu) –> Custom Images.

3. Click on “Use an Image” and paste in the “Shared” text box the link listed above for the spinning blue hurricane.

Screen Capture: Pasting link copied for the custom symbol


4. Once this symbol has been uploaded as a custom symbol you will just need to “Select” it as it will already be in your symbol gallery. Continue individually for Category 1-4 Hurricanes.

5. Don’t worry about the size of the symbols, keep them at their default. Those will get adjusted in the Arcade expression below.

6. Because the hurricane symbol should only highlight Category 1-5 Hurricanes, for Tropical Storm and Tropical Depression categories select any “Basic” symbol and change the “FILL” and “OUTLINE” to No Color (small box with red slash on it).

7. It will look like:


Screen Capture: Map Symbols Window


8. Click “OK” and keep the Style Editor open.


Automatically Adjust the Symbol Size in Arcade

While ArcGIS Online doesn’t allow for setting a map reference scale (yet) as you can in Pro, there is a trick through using an Arcade expression.

Using the Saffir-Simpson Wind Scale classes you just set from above, it’s possible to define your map zoom scales (cs) in combination with wind speed classifications (INTENSITY) and set a symbol size at the end of each line.

1. In the Change Style –> Choose and attribute to show window –> Add attribute


Screen Capture: Add Attribute


2. Using the drop-down menu select “New Expression”.

3. Edit the “Name” at the top to say: Set the Symbol Size by Map Scale

4. Place this code in the Arcade window:

var cs=$view.scale

When (cs<=74000000&&cs>=37000000&&INTENSITY>=137,30,





5. What the code is saying: When the map zoom scale is between this scale and that scale, and the intensity is between this speed and that speed, make the size this number.

6. It looks like:

Screen Capture: Arcade Code for Set Symbol Size by Map Scale


5. Take note that the lowest symbol size is 10  and the highest is 80 (“0” for Tropical Storms and Depressions is omitted). You will need this information again later.

6. Did you notice that the code omits Tropical Storms and Depressions (last two lines of each section the symbol size to “0”)?  This is because the spinning blue hurricane symbol only needs to symbolize Category 1-5 Hurricanes and there is another layer (with a filter) in the map that symbolizes Tropical Storms and Depressions. Also take note that the spinning blue hurricane symbol is a PNG file and the Tropical Storms and Depressions are symbolized as basic circle point symbols.  The PNG files that you upload, and standard embedded point symbology in ArcGIS Online will have different behaviors and need to have separate Arcade expressions.  This is due to minimum and maximum sizing of symbols you will see next in Step 10.

7. Now that I have the two Arcade expressions in the layer and they are applied select “Options” from the drawing style.


Screen Capture: Apply style to 2nd Arcade Expression


8. Click on “Options” for Counts and Amounts (Size)


Screen Capture: Set Symbols by Counts and Amounts


9. Remember the lowest symbol size value is 10 and the highest is 80? Enter in the these high and low values in the following six places for this sizing expression to work (Please note that if you adjust anything in your Arcade code you will need to reenter these again.  Any change will override these values):


Screen Capture: Six places to enter in your high and low values


10. Click “Done”. Both Arcade expressions are embedded within the layer and everything should be now sizing appropriately!



Sequential hurricane symbols



This is the map at 1:74,000,000:


Screen Capture: Map at Main Scale



At 1:18,500,000 the hurricane symbol starts to appear:


Screen Capture: Map at 1:18,500,000



Here is 1:5,000,000 and they are sizing nicely!


Screen Capture: Map at 1:5,000,000



Creating custom Arcade expressions to define symbol sizes at the varying ArcGIS Online map scales will give you more control and your map symbols more presence.  The beauty of using these Arcade expressions is that you no longer must replicate layers to show the symbols at all the varying scales, you can now just have one layer in your map and the symbols will size appropriately.



Here is the web map and app discussed in this blog. Feel free to open them up and copy the Arcade codes for the varying hurricane point and line files.

1. The Recent Hurricanes, Cyclones, and Typhoons (Current Year) web app is here.

2. The Recent Hurricanes, Cyclones, and Typhoons (Current Year) web map is here.


Thank You!

One of the best things about working at Esri is the team and professional camaraderie.  My colleague Jennifer Bell deserves special thanks for her assistance with the Arcade expressions and her continuous support and encouragement of my work.



Do you have questions or comments about this blog? Post them in our GeoNet.

Blog Author: Diana Lavery     Originally Published:  ArcGIS


Many feature layers in the ArcGIS Living Atlas contain features for a larger region than many analysts need.  A growing number of content items are added to the Living Atlas every day that have data for all tracts, counties, schools, hospitals, or parks in the whole United States.  Most GIS analysts only need to work with features for their own immediate area.  By applying filters to these national layers, you can subset only the features that you need.



Blog Author: Robert Waterman  Originally Published: ArcGIS


Earth’s poles have historically been some of the most poorly mapped regions on the planet.  With heightened awareness, and an overall sense of urgency around global climate change, there is a need for high quality mapping data to facilitate a deeper understanding of the impact with regard to Earth’s polar regions.


Sparked by President Obama’s 2015 Executive Order, and thanks to the University of Minnesota’s Polar Geospatial Center (PGC), along with their partners and sponsors, we now have high resolution topographic models of the Arctic region and the entire continent of Antarctica.


From monitoring and modeling the impacts of climate change over time, to field logistics, scientists, government officials, and the broader user community can leverage these great elevation maps and layers via the ArcGIS Living Atlas of the World.


Arctic DEM

ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality Digital Surface Model (DSM) of the Arctic using optical stereo imagery from DigitalGlobe.


Esri has been providing this data to users since 2016.  However, we recently updated to ArcticDEM Release 7, which includes 2-meter resolution elevation data for the entire region.  All of our online Arctic DEM layers and maps can be accessed and used in ArcGIS Pro, ArcMap, and custom web apps.


Want to see ice field and glacier changes over time?  For a quick introduction to the different layers and functionality, check out the Exploring Arctic Elevation user guide.  This story map will provide a quick overview of the different renderings and functionality, and even demonstrate how to analyze and measure ice changes over time.  It is an eye opening experience, I encourage you to give it try.  Also, since the Arctic DEM layers themselves are time enabled, change over time, and much more, can also be accomplished using ArcGIS Pro.


Arctic DEM Explorer app showing Hillshade Grey and a profile from the Time Control. Click here begin exploring.


Antarctic DEM

New to the Living Atlas is an 8-meter resolution elevation model covering the continent of Antarctica.  The Reference Elevation Model of Antarctica (REMA) is the latest addition to Esri’s polar elevation services, adding a level of detail not previously available in a full coverage map of Antarctica.  According to Ian Howat, director of the Byrd Polar and Climate Research Center at The Ohio State University, “Up until now, we’ve had a better map of Mars than we’ve had of the Earth.”  I think it is safe to say that a gap has been filled.


Funded by the National Science Foundation’s Division of Polar Programs, REMA Release 1 is an 8-meter Digital Surface Model (DSM) constructed from sub-meter, stereoscopic satellite imagery collected by DigitalGlobe’s Worldview satellite constellation.  The DigitalGlobe satellite imagery is licensed by the National Geospatial-Intelligence Agency, and includes data acquired between 2009 and 2017, with most collected in 2015 and 2016.


This elevation data is ready to use in a number of different web map views and renderings.  Some layers are optimized for visualization and some for computation.  For more details, refer to this item description or click on the image below to begin exploring with the Antarctic REMA Explorer.  While our Antarctic layers are not currently time enabled, users can find and download individual strips from different points in time by going to the ‘REMA Strips’ section of the PGC website.


Arctic REMA Explorer app with the elevation rendered as a grey hillshade. Click here to begin exploring.


In case you missed it above, all of the Arctic and Antarctic DEM layers and maps can be found in the ArcGIS Living Atlas.


New to ArcGIS?  Sign-up for a free Online account to access additional online content, start making web maps, and start collaborating today.  For a full ArcGIS experience, sign-up for a free trial.

Blog Author: Lucy Guerra's Blog    Originally Published: ArcGIS 


It’s no surprise that today’s residential real estate has remained pricey. Rising interest rates aside, the value of most homes has gradually recovered since the last major price correction a decade ago. Gone are the days of unrestrained, unsound lending practices, and borrowers overextending themselves to the point of default or foreclosure. By and large, property values across the price spectrum have appreciated since the last recession. As this trend continues to be prevalent within markets containing premium-priced properties, we’re faced with a growing number of towns with million-dollar homes. But how many?

Show me the numbers

With over 78 million owner-occupied homes in the US:


  • More than 2.1 million homes are valued between $1 million and $2 million.
  • Nearly 600,000 homes are valued at $2 million or more!
  • New York City tops the list with more than 68,000 homes valued at $2 million or more!


These numbers sound impressive, but million dollar plus homes represent a relatively small segment of the US housing stock. However — an interesting data discovery here is that the percentage of million-dollar properties has more than doubled since 2010.

Across the US, you can see that majority of these million-dollar plus cities are concentrated along the east and west coast regions of the US.


2018 High Median Home Values

Where does the data come from?

Esri provides demographic data for 137 countries covering 90% of the world’s population. Esri’s in-house US Data Development team, which consists of demographers, economists, analysts, and programmers, develop independent demographic and socioeconomic updates and forecasts for the United States.

In addition to processing US Census and ACS data, the US Demographic Data Development team produces unique and innovative databases such as Tapestry Segmentation, Consumer Spending, and Market Potential which have become industry benchmarks for understanding communities. To learn more about Esri’s data accuracy, view

Why track the multi-million dollar housing market?

In most cases across the country, housing affordability continues to be a major concern. As a result, Esri’s US demographics team recognized the importance of adding more detail to the home value distribution.

“In many markets home values have surpassed their pre-recession highs. As more homes breach the million-dollar valuation mark, our home value distribution has been expanded to reflect current prices,” says Esri Chief Demographer, Kyle R. Cassal.

Show me the data

Taking a step back, if analysts wanted to identify areas with extreme affluence, the highest home value range used to be capped at $1 million or more. Capturing today’s growing multi-million-dollar housing market meant redefining and expanding Esri’s 2018 and 2023 home value ranges to offer more detailed data of owner occupied housing units with home values that would exceed $1 million. The result…

… a home value database that includes 3 new multi-million-dollar ranges:




A picture is worth… well, one or two million bucks!

One of the best ways to show you the impact of these new data ranges is with a map. Esri’s US demographics team created the 2017-2018 Home Value Comparison web map for the Manhattan, New York area using ArcGIS ’s smart mapping technique called Predominance Mapping.

The panel on the left displays the predominant home value range from Esri’s 2017 home value distribution by Census tract. The top end of this distribution of owner occupied housing units is capped at $1 million or more and symbolized by the deepest purple bubbles.

The panel on the right displays Esri’s newest 2018 distribution utilizing the three new top end home value ranges. The deep red bubbles symbolize the new higher top-coded home value range.



Using the predominant mapping technique, you immediately see the impact of the new intervals. Look at how the finer resolution ranges distinguish the smaller pockets of the highest valued homes at $2 million and beyond.

So, what does your town look like?

Access Esri Home Value data from these products and find out!

For more information about US demographics click here.

Blog Author: Shane Matthews      Originally Published: ArcGIS


Through the Community Maps Program organizations contribute their local geographic content which is published and freely-hosted by Esri. Everything from basemap layers such as address data, parks and trees, to imagery and stream gauge data can be contributed.

New Communities

Our users have just provided new and updated basemap layers and high-resolution imagery for 37 communities in Canada, Japan, Switzerland, and the United States. The Community Maps Team has published over 200 projects this year alone, and we’re not done! More and more communities are discovering that the ArcGIS platform is the best place to freely host their organization’s basemap content.

This latest release includes building footprints, facility sites, local parks, sidewalks, trees and other great content supporting campuses, cities, and counties across the globe. Detailed large-scale basemap layers and high-resolution imagery shared to the ArcGIS Living Atlas of the World are what set basemaps in ArcGIS apart from other mapping APIs.

Do these contributions make a difference? Just have a look at these examples by selecting the images below.

City of Vernon, British Columbia, Canada (Neighborhoods, Points of Interest, Waterbody, Road Centerline, Owner Parcels, Building Footprints, Airports, Local Parks, State Forests/Parks, Trails, Landscape Area & Street Pavement).

City of Vernon, British Columbia, Canada

Merced County Association of Governments (Owner Parcels, Road Centerlines, Railway Lines, Waterlines, Municipal Boundary, Building Footprints, Waterbody, Local Parks, National Forests/Parks, State Forests/Parks, Education, Administrative Line)

Merced County Association of Governments

This release also includes high resolution imagery for an impressive 270 campus-areas throughout the state of Hawaii, shared by Resource Mapping Hawai’i, one of our latest Community Maps contributors, and the leading provider of aerial mapping, remote sensing and GIS solutions in Hawai’i and the Pacific region. The sub-meter resolution (0.03m) is remarkable.

Click on the Story Map below to view interactive maps of our new communities.

New to Community Maps

How do I contribute?

It’s easy! The Community Maps Program works with authoritative GIS data contributors to build the ArcGIS Living Atlas of the World consisting of reference and thematic maps covering a wide variety of topics. Community Maps Program contributors participate by sharing data to one or more of these communities.

You can begin contributing by registering here!



Shane is a Cartographic Specialist for Esri's ArcGIS Content Team. He curates and recruits content for the ArcGIS Living Atlas of the World through Esri's Community Maps Program, and explores and implements new and innovative delivery methods of providing geospatial information.

Blog Author: Andrew Green         Originally Published: ArcGIS Blog


With our latest release late last week, Esri Vector Basemaps updated map styles and added features, increased the number of localized maps, and published a new creative style. We added new HERE data to improve the maps. Our Community Maps Program also provided new data. See these blogs by Shane Matthews for specific contributions.

Style Improvements

Display of features improved across several basemaps. Street Map, Streets with Relief, and the Hybrid Reference Overlay changes increased city font size, added beach sprite, and made JSON layer names more user friendly. New pavement markings enhance larger scales, especially at the campus level. The updated Topographic vector map displays arrows and handicapped parking symbols. This Reference Document provides information on recent changes and structure of our basemaps. Bookmark this group or search the Living Atlas of the World (Basemaps category and Vector Tiles sub-category). Similarly, Esri vector maps are accessible in the map viewer and ArcGIS Pro in the same Living Atlas Basemaps category and Vector Tiles sub-category search.



New beach sprite pattern and larger city names in World Street Map


New pavement markings (arrows and handicapped parking) in Topographic


Basemaps Localization

We added three new languages to our collection of localized basemaps. Our current total is nine different languages. Each one is available in nine different basemap styles. New are Italian, Polish, and Brazilian Portuguese. These join previously released Modern Chinese, French, German, Japanese, Russian, and Spanish. To make localized maps the default basemap, change the organization’s Region and Language in the General settings. Also, change the Map setting to display Esri vector basemaps for the Gallery. Each language above is linked to a group of web maps. Localized labels display primarily at small scales; however, we are expanding translations across more feature classes and at more scales. Additional languages will be deployed in subsequent releases.



Italian (Navigation), Portuguese (Brazilian) (Dark Gray Canvas), Polish (Streets)

Style Editor

Esri Vector Tile Style Editor (Beta) - Quick Edit change to World Navigation Map

Style Editor

The Esri Tile Layer Style Editor (Beta) provides an easy way to customize vector basemaps. Experiment (& save!) different cartographic styles with this app. Start from an Esri vector basemap or one of your own vector tile layers. Two styling paths exist:

Quick Edit is only configured for Esri vector basemaps. This quick path sorts map features into six high-level categories. Apply random colors for cartographic inspiration, or apply a pre-defined color palette to each category.

Edit Layer Styles works with Esri vector maps and your own styles. It offers more control over each map feature’s spec. Countless options are available to customize your new vector map. Save your new style as a tile layer in your account and use the new style in your web maps and apps. This blog and space on GeoNet offers information about the Style Editor. This recent Esri Webinar showcased the Style Editor. Follow-up questions and answers are at this Living Atlas GeoNet page.


Pop Art Basemaps

San Francisco waterfront at ~1:4,000 scale in the new creative Pop Art vector map style

And now, something completely new!

Pop Art is Esri cartographer Andrew Skinner’s new custom style. This 1960’s-inspired map is busy, brash, and bright! This map, along with other Esri Creative Maps, pushes the limits of map design. The maps have drastically different looks, but still use the same vector map content. He also published a series of blogs on working with and customizing Esri Vector Basemaps. Check them out!



Have you ever seen a problem with Esri Vector Basemap data that needs to be fixed? Report issues directly on this Feedback Map. Our team reviews your comments and considers the update for one of our frequent releases.




Andy is the Project Manager for the Basemaps in the ArcGIS Living Atlas of the World. Creating and updating the basemaps is a collaboration of the Community Maps, Data, Authoring, QA, Release, and Development teams.

Ready to take your maps to the next level? Vector tiles enable dynamic cartography and provide the flexibility to create your own basemap style. The new ArcGIS Vector Tile Style Editor makes it easy to test different styles until you find one that works well with your brand and design. It even provides suggestions to help you discover combinations you never considered. We will show you how to use the tool and provide some creative examples.

The ArcGIS Living Atlas of the World team continually enhances and expands its set of vector basemaps. During the webinar we’ll share our localization plans that are already underway—vector basemaps were just released in six languages across eight basemap styles. We will also walk you through a gallery of creative map styles. These unique map styles were developed by our cartographers and incorporate new map features and labels. These are ready to use and available in ArcGIS Living Atlas of the World.

Register to join this webinar.

by Bern Szukalski


The Thomas Fire


The Thomas Fire was a devastating wildfire of historic proportions that burned through parts of California’s Ventura and Santa Barbara Counties. The fire started on December 4, 2017, north of Santa Paula and near the Thomas Aquinas College, the fire’s namesake. Driven by strong Santa Ana winds that persisted for nearly two weeks, and a large amount of available fuel, the fire grew rapidly. By it’s official end on January 12, 2018, the fire had become the largest in California history (since superceded by the Mendocino Complex Fire).


The fire destroyed over a thousand structures, with hundreds more damaged. It generated over $2.18 billion in damages, injuring one firefighter and claiming the life of another, along with one resident who died in an auto accident while fleeing the area. The destruction didn’t stop with the fire, as post-fire rains created massive mud flows that claimed 21 lives, destroyed 129 residences, and damaged over 300 more. See the Thomas Fire on Wikipediafor more information.


The Thomas Fire map


In this tutorial you will learn more about the fire using ArcGIS  analysis tools and content available from the ArcGIS Living Atlas of the World to author a map showing the  fire perimeter, learn more about the population and demographics of the impacted area, and view satellite imagery before, during, and after the fire.


You will use the following steps:


  1. Find the fire location
  2. Add and save the fire perimeter
  3. Geoenrich the perimeter, adding population and other demographic information
  4. Add Sentinel-2 imagery for dates prior to the fire, during the fire, and after the fire was fully contained.
  5. Adjust the imagery to reveal specific details


Find the fire location


Step 1 – Use Search to find the location.


The first step in making the map is to navigate to the fire location. Open a new web map, use search and enter Santa Paula, California. You can also use Thomas Aquinas College, Santa Barbara County, or Ventura County as the search string.



Add the Thomas Fire perimeter


The USA Wildfire Activity layer from the Living Atlas displays current and inactive fire locations and perimeters. From your web map, Browse the Living Atlas to find the USA Wildfire Activity layer, then add it to your map.


Step 1 – Click Add, then Browse Living Atlas Layers.


Step 2 – Search for “wildfire” to locate USA Wildfire Activity, then click + to add the layer to your map.


Step 3 – Display the Thomas Fire perimeter.


By default, the  USA Wildfire Activity layer has the active fires locations and perimeters toggled on. Since the Thomas Fire is no longer active, you will turn the default active fire sublayers off, and turn the inactive perimeters on. Click the layer title to reveal the sublayers, and toggle the layers as shown below.


Zooming out, you can view the extent of the Thomas Fire.



Create a copy of the perimeter


Inactive fire locations and perimeters are eventually phased out from the service, so you will create a copy of the perimeter to ensure it will always be available in your map. You will use the Analysis tools to create a new feature layer from the existing Thomas Fire perimeter.


Step 1a – Open the Analysis tools.


Step 1b – Open the Find Locations group.


Step 1c – Click Find Existing Locations.


Step 2 – Complete the tool steps (numbered in blue) as follows.


In tool step 1, choose the USA Wildfire Activity-Inactive Perimeter sublayer.


Step 3 – In tool step 2, construct the attribute query expression to find the Thomas Fire perimeter. The expression looks like this:


Step 4 – Complete the tool inputs for Find Existing Locations by entering a Result layer name in tool step 3, then click Run Analysis.



Enrich the fire perimeter polygon


How may people lived in the burn area? How many households were impacted? What is the population like? These questions can be answered by using geoenrichment tools that tap into Living Atlas data to add attributes describing these characteristics. These data are added based upon the area of the polygon using apportionment, the full details of the implementation and methodology can be viewed in the Data Apportionment documentation.


Step 1 – Open the Analysis tools, and choose Enrich Layer.


Step 2 – Complete the tool steps in the Enrich Layer tool. First, select the layer you created in Step 8 in tool step 1.


Step 3 – In tool step 2, click Select Variables to open the Data Browser.


Step 3 – Choose the following attributes to enrich the fire perimeter:


  • 2018 Total Population (Esri)
  • 2018 Total Households (Esri)
  • 2018 Median Household Income (Esri)
  • 2018 Dominant Tapestry Segment Name (Esri)


Begin by selecting a category:


Then choose the attributes.


To go back to the categories, click the category box in the upper left:


Step 4 – After selecting the attributes, complete the tool steps as shown below, then click Run Analysis.



Add Sentinel-2 imagery


Sentinel-2 is multispectral, multitemporal global imagery obtained via two satellites placed in the same orbit by the European Space Agency, and phased 180 degrees from each other. Every location on the planet is revisited every 5 days. This Living Atlas imagery layer pulls content directly from the source Sentinel-2 archive on Amazon Web Services (AWS), and is updated daily. The layer can be easily added to web maps (and scenes), and rendered in different ways to highlight specific characteristics. In addition, the imagery can be filtered by date.


Step 1 – Add the Sentinel-2 imagery layer from the Living Atlas.


This is similar to what you did in Step 3, but search for Sentinel-2 instead.


Step 2 – Remove the default filter on Sentinel-2.


The default filter on the Sentinel-2 layer will display the most recent and clearest imagery available. You will want to search for all imagery around the dates of the fire, even smoke-filled imagery, so remove the filter so all imagery will be available. After adding the layer, click the Filter icon to display the current filter, and remove it.


Step 3 – Click More Options (…) and choose the Image Filter.


You will use this filter to search for available imagery around the dates of the fire.


Step 4 –  Select the imagery at the desired dates.


Adjust the time slider around the dates of the fire. The available imagery will be listed. Hover over each to display the coverage footprint in yellow on the map. Identify the date, then select the images that cover the fire perimeter. Repeat the process to create layers for before, during, and afterwards. Note that to cover the entire fire perimeter you will have to select two images, then click Add To Map combining both into one layer.


When moving on to the next date, remember to uncheck the previously selected layers.


The fire started December 4, 2017, and officially ended January 12, 2018. Using the image filter to add Sentinel-2 imagery for the following dates:


  • October 23, 2017 (before the fire began)
  • December 7, 2017 (during the fire)
  • January 16, 2018 (after the fire)



Adjust the imagery display


To glean more information from multispectral imagery like Sentinel-2, you can choose a renderer that highlights specific characteristics of the imagery. For example, you can choose renderers that highlight healthy vegetation, geology, moist areas, and more.


The default renderer is Natural Color with DRA (Dynamic Range Adjustment). In this section you will apply the following renderers to the imagery layers you have added to your map:


  • October 23, 2017 (before the fire began) – use the default Natural Color with DRA.
  • December 7, 2017 (during the fire) – use Short-wave Infrared to highlight actively burning areas and hotspots.
  • January 16, 2018 (after the fire) – use Normalized Burn Ratio to highlight the burned areas.


Step 1 – From the layer options, choose Image Display.


Step 2 – From the list of renderers, choose the one that you want, then click Apply.


Repeat the steps for the other layer, and save your map when finished.


Summary and results


Using content from the ArcGIS Living Atlas of the World and ArcGIS  capabilities, you have authored a map that delivers enhanced information about the Thomas Fire.  Demographic attributes have been added to the fire perimeter delivering information about the impacted households and enabling us to learn more about those that lived there.  Sentinel-2 layers of different vintages have been added, and specific spectral characteristics of the imagery have been rendered to highlight active burn areas, and post-fire impacts. These are reviewed below.

Geoenriched fire perimeter


After configuring the layer pop-up, clicking the perimeter provides more information about the population. The total number of acres was in the original perimeter, but geoenrichment has added the population, number of households, median age, median household income, and dominant Tapestry segment (Exurbanites). The dominant segment is a link that opens detailed documentation about Exurbanites, helping us learn more about the characteristics of the impacted residents.


Pre-fire Sentinal-2 imagery December 23, 2017


Using the default Natural Color DRA renderer, this image show the normal conditions and appearance for the burn area.


During-fire Sentinel-2 imagery December 7, 2017


Captured a few days after the fire started, and using the Short-wave Infrared renderer, this layer allows us to peer through the smoke and clearly see the active burn areas.


Post-fire Sentinal-2 imagery January 16, 2018


This layer uses the Normalized Burn Area renderer to highlight the burned areas in black.


View the map


Click the image below to view the map authored via this tutorial. Since the map contains subscription content, you will be prompted to sign in when the map is opened.



More information


For more information, see the following:


by Andy Skinner


This is an update of a blog and a sequence of story maps written in 2017 looking at the mechanics of customizing our vector basemaps. It includes updated links, and details on working with the new Vector Style Editor released in early 2018.


If you prefer to go straight to the Story maps, this link takes you to the first of them: Pt 1: The Basics




Personalize your maps with vector basemaps


Ready to take your maps to the next level? Vector tiles enable dynamic cartography and provide the flexibility to create your own basemap style. In our September 6, 2018 webinar, we will show you how to use the new ArcGIS Vector Tile Style Editor to personalize your maps. We’ll also walk you through an inspiring gallery of creative map styles that incorporate new map features and labels.


Register for the webinar here!



Vector Tile Layers can be used to create multi-scale maps that are efficient, high-resolution and customizable, and this includes Vector Basemaps. Esri’s Living Atlas Content Team has created vector tile versions of most of our traditional basemaps (plus some new ones), and these work well in themselves …



But have you ever had that moment where you thought ‘This basemap would work really well, if only …’?


What are Vector Basemaps?


Our vector basemaps originate as a Vector Tile Package, built in and generated by ArcGIS Pro, then published with a generic style. It establishes the maximum level of content available and a defined scale range for each layer of information. Separate style documents are created in JSON Code for each of our basemaps, although they do not necessarily use all of this content, or the available scale range.


The Vector Tile Package


A vector tile package contains the vector tiles, and various formatting documents. Of interest to us is the Resources Folder, which includes:


Fonts – Any font that is used in the ArcGIS Pro map.


Sprites – PNG Raster images created for special effects, such as textured patterns and point symbols. In most circumstances, once these have been exported from Pro, they are not editable. However, we have created alternatives for our different core maps.


Styles – A root.json file that establishes the symbolization of the map detail. This is editable, and it is the key to the discussion here. We can make changes to this code to affect color, line weight, label size/font, and scale range … either directly, or through an editing app.


How do I work with them?


The Vector Basemaps Reference Document, is a downloadable PDF describing how our maps are structured. As the maps themselves have become more versatile (and we are trying to improve them all the time), our layer structure has become more complex. This document will help you to find your way through. It may be a little confusing at first, but the more you work with it, the more it will make sense. Don’t feel you have to learn it before you start work though (It’s a ‘reference’ document!).


We provide two editing apps to help you on your way (Note that both are in beta, so details could change without warning). Both require you to sign-in to an organization.


The first is new as of 2018.


The ArcGIS Vector Tile Style Editor is an intuitive app that leads you through most of the simpler changes you can make to the map style. For most tasks this will make life much easier for you.



The JSON Code Editor has been available for a while. It pairs the JSON style with a preview map as an easy way for you to work directly with the code and see the results. If you are confident in your ability to work with code, the JSON style file gives you access to some more sophisticated options. It is a requirement if you want to add data layers to the style.



For more information, these links take you to the sequence of story maps. Use these to get a better understanding of how our basemaps are structured, and how to exploit them using these two apps:


Pt 1: The Basics


Pt 2: Colors


Pt 3: Lines


Pt 4: Labels

by Shane Matthews


The ArcGIS World Geocoding Service helps you find and display global addresses on a map with a high degree of accuracy. Its global address dataset includes data from commercial sources, all levels of government, and many reputable mapping organizations. Esri works with its global distributors to include local data suited for each region for an unrivaled user experience. International reference data ensures that ArcGIS World Geocoding Service offers consistent and authoritative geocoding results.


Community Addresses


Our Community Maps contributors have been asking how they can help improve Esri’s World Geocoding Service. Many of our contributors are managing progressive communities, where new residential and commercial areas have been constructed. Some are enhancing their city or county 911 system that uses ArcGIS  mapping as an essential component.


The Community Maps Program uses best available address datasets to support ArcGIS World Geocoding Service. Included addresses represent comprehensive and accurate locations for many countries, and are available to search against and provide the most accurate geocoding results. You can now contribute point and polygon address data to enhance the geocoding experience of your users.


Community Addresses


Accepted content


Comprehensive and Accurate Point and Polygon Addressing Data located at


  • Primary entrance points to a building or unit (preferred)
  • Rooftop points – central location on rooftop of a building (2)
  • Offset from the street at a location where a vehicle would arrive at the address (3)
  • Offset from the street at a location in front of the building or parcel (4)
  • Parcel centroids (5)


Should include complete address attributes:


  • House number
  • Apartment or Unit Information (if available)
  • Building Name (if available)
  • Complete Street Name
  • Administrative addressing information such as City or State
  • Postal Information (recommended)


How do I share my Community Addresses?


Easy! Click on the image below to download the latest version of the Community Maps Data Prep Tools, we have included a new tool that prepares address data! There are instructions to help you along the way. Just email the Community Maps Team ( if you have questions.


Community Maps Data Prep Tools


If you are a registered Community Maps Program contributor just log into your account, select ‘My Account’ and select Addresses under the ‘Change Registered Layers’ section.


Not registered with the Community Maps Program? Get it done here!


Related Blogs:


It’s back to school with a Community Maps Data Prep Tools Update!

What’s New in Community Maps (August 2018)

by Shane Matthews


Well, it’s back to school season and with that comes hoarding supplies, buying books, and collecting tools to help get through it all. We wanted to make sure our contributors had the tools they needed by providing a Version 3.0 Release of the Community Maps Data Prep Tools. These easy-to-use tools assist contributors with preparing basemap layers for submission, standardize content, speed up data integration – what’s not to like about that? So, you can retire the former CM DataPrepTools Version 2.0!


Let’s breakdown the update…


Changes in Version 3.0 Release

  • The tools work in both ArcMap (10.4.1 and higher) and ArcGIS Pro (2.2.1).
  • Tool parameters (i.e., the query statements) are automatically saved to a parameters file, and the tools remember your previous settings. This means you can easily re-run a tool without needing to enter the query statements each time. You can also save the parameters and re-use them when you re-run the tools for your next data contribution.
  • The Road Centerline Tool has been simplified and combined into a single tool (no more Part1 and Part2).
  • There is a new tool to support contributors who want to provide Address points or polygons. The output layer is used by the Esri Geocoding Team to improve accuracy in the ArcGIS World Geocoding Service – as opposed to these being features added to the Esri basemaps.


Community Maps Data Preparation Tools – Part 1


This video provides an introduction to the Community Maps Data Prep Tools. It demonstrates how to download the tools, explores the resources that are included in the download, shows you how to begin by running the Setup Tool, and gives an example of running the Building Footprint Tool. Click the image below to view the video.


Community Maps Data Prep Tools Part 1 - Introducing the Tools in ArcMap


Community Maps Data Preparation Tools – Part 2


When you run a tool in Version 3.x of the Community Maps Data Prep Tools, your queries and other settings are saved in a Parameters file. Storing this information makes it incredibly easy to re-run the tool without re-entering all of these queries. This video provides an explanation of how to Save and re-use your query parameters in the Community Maps Data Prep Tools. It demonstrates where the parameters are saved, how they are used, and how to save and retrieve them for your next data contribution. Click the image below to view the video.


Community Maps Data Prep Tools Part 2 - Saving and Using Tool Parameters


Contributor App Updates


This video highlights new capabilities of the Community Maps Contributor App. Among other things, the big news here is that this latest release includes the ability to provide Road Centerline data in the form of a Service, which was requested the most from our contributors. Click the image below to view the video.


What's New in the Community Maps Contributor App


Community Maps Data Prep Tools


OK, you’ve been patient, so here they are. Click the image below to download the new tools now and get started on that basemap layer submission! If you have not yet registered with Esri’s Community Maps Program, you can get that done here. Have questions? Email the Community Maps Team (


Community Maps Data Prep Tools


Related blog: What’s New in Community Maps (August 2018)

by Dan Pisut


It’s rare for hurricanes to threaten the Hawaiian Islands. And it’s even more rare for one to threaten Honolulu, which is nestled in the middle of the chain on Oahu. Hurricane Lane, however, is tracking along the coast and is generating hurricane conditions for many of the islands.


Hurricane Lane Forecast Map

Forecast #31a for Hurricane Lane on August 22, 2018. Note: this is a static dataset used for display purposes and is not the Live Feed. The forecast will change but this map will not.



Turns out that the Active Hurricanes layer in the Living Atlas of the World was missing a wind field found in other products from the National Hurricane Center.




Well…it has to do with how different components of the National Hurricane Center are responsible for different portions of the Atlantic and Pacific Basins, and they have different websites, data servers, and notification mechanisms. And when there are no storms (typically) to check if the data is there, you don’t know its missing. Kind of like the age-old question, “If a tree falls in a forest and no one is around to hear it, does it make a sound?” Only here, the tree is a major hurricane near the Hawaiian Islands.


The good news is that Central Pacific storms now have the forecast wind probability fields. This layer shows the chance that winds of a certain speed will impact an area. The 64 knot layer is probably the most useful, as that shows hurricane force winds. The layer does not display by default, so you’ll need to expand the options and check the appropriate boxes.


layers in active hurricane live feeds

Happy Probabilistic Wind Forecasting!


For comments or questions about this blog, please visit our GeoNet.

by Shane Matthews


Through the Community Maps Program organizations contribute their local geographic content which is published and freely-hosted by Esri. Everything from basemap layers such as parks and trees, to imagery and stream gauge data can be contributed.


Detailed large-scale basemap layers and high-resolution imagery shared to the ArcGIS Living Atlas of the World are what set Basemaps in ArcGIS apart from other mapping APIs.


When I speak with local governments, regional council of governments, universities and other like organizations that provide their local authoritative content through the Community Maps Program, I tell them to let the basemaps on ArcGIS  truly reflect their communities. I encourage them to empower themselves and contribute to a trusted foundation that helps them accomplish their work, helps them create better web maps and applications, and deliver better resources to their citizens. Below are a few examples of how these maps can be transformed when ‘local-knowledge geography’ is added.


The left panel in the images that follow illustrate content supplied through the Community Maps Program. Click on the images for the best view.


Bardstown, KY

Bardstown, KY


Bothell, WA


Gillette-Campbell County, WY


Pasco, WA


Dover, DE


Rutherford County, TN


Umatilla, OR


Latest Release


This month 48 communities have shared new and updated map layers in support of Esri’s expanding suite of high-performance basemaps and imagery services. Map layers include aerial photography, boundaries, buildings, owner parcels, parks, points of interest, trees, and similar large-scale features that enhance our foundational information sets for the world to use.


Tour our newest communities by clicking the Story Map below.


What's New in Community Maps (August 2018)


How does my organization contribute?


It’s easy! The Community Maps Program works with authoritative GIS data contributions to build the ArcGIS Living Atlas of the World consisting of reference and thematic maps covering a wide variety of topics. Community Maps Program contributors participate by sharing data to one or more of the following categories.


You can begin contributing by registering here!


Upcoming Webinar



Personalize your maps with vector basemaps


Ready to take your maps to the next level? Vector tiles enable dynamic cartography and provide the flexibility to create your own basemap style. In our September 6, 2018 webinar, we will show you how to use the new ArcGIS Vector Tile Style Editor to personalize your maps. We’ll also walk you through an inspiring gallery of creative map styles that incorporate new map features and labels.


Register for the webinar here!

by Diana Lavery


Did you know that Census’ American Community Survey data come with margins of error? Did you also know that you can easily incorporate these values into your web maps to help display the accuracy of the data?


What are Margins of Error?


If you’ve worked with some of our feature layers in the ArcGIS Living Atlas contain data from the U.S. Census Bureau’s American Community Survey (ACS), you have probably seen fields called “margin of error.” Ever wonder what those are?


First and foremost, remember that the ACS is based on a sample, just like any other survey. When I think of “samples,” I first think of ice cream. A sample of ice cream at the ice cream shop gives us an estimate of the characteristics of the whole tub of ice cream. Do all samples have the exact same amount of chocolate chips? Of course not. Does a sample from the top of a tub of ice cream taste the same as a sample from the bottom of the tub? Maybe, maybe not. Which sample is a better approximation of the taste of the entire tub?


Photo source: Yelp’s page for The Hop in Reno, NV.


Similarly, a survey’s sample gives us estimates of the characteristics of the whole population. We can measure how good those estimates are. Margins of error are an indicator of the reliability of the estimate, an upper- and lower-bound of a range that Census has given us. The estimate is simply the midpoint of the range, or “confidence interval.”


For example, this feature layer of disability status by sex by age gives us an estimate for Florida Tract 120990064.02 of women age 75+ with a disability of 361, and a Margin of Error (MOE) of 158. This tells us that the Census Bureau is 90% confident that the true count of women age 75+ with a disability in that tract is between 203 (361-158) and 519 (361+158). 361 is the midpoint of that range.


In general, the confidence interval gets larger as your population gets smaller. Your population could get smaller geographically (the range for the estimate of Los Angeles county’s population will be much smaller than the range for the estimate of a tract’s population), or demographically (the range for the estimate of same-sex married couples will be larger than the range for the estimate of opposite-sex married couples).


Why bother using the Margin of Error at all?


By incorporating the margins of error into our maps, data analysts and GIS analysts who inform decision makers can show the full picture of the data in their information products and reports. The Census Bureau has given its data users a gift: a measurement of how accurate each and every estimate is that they produce. Other large-scale surveys publish confidence intervals as well, such as many political polls.


This blog post presents some options for incorporating the margins of error into your web maps when mapping ACS data. Like with all map making, the option you choose depends on your audience! Option 1 is easiest to communicate to lay audiences who just want the high-level information. Option 2 is best for those who like to see all available data. Option 3 is for ACS power-users who are familiar with margins of error.


Option 1: Suppress Unreliable Estimates

Suppress Using the Reliability Flags from Geoenrichment


It’s often helpful to consider the ratio of the range to the estimate. If the confidence interval or range for a given estimate is very small in relation to the estimate, the estimate is more precise, but if the range is large, the estimate can be imprecise or unreliable.


Some analysts have a strict requirement of a 10 percent cutoff threshold, meaning if an estimate has a confidence interval that is 10 percent or more of the estimate’s value, then they consider it somewhat unreliable. Others have a more lax requirement of 15 percent. Those in the middle might use 12 percent. Esri’s demographics team created reliability flags for demographic estimates available through GeoEnrichment, and a 12-percent cutoff point is used to identify estimates with high reliability.


For example, I added a layer of census tracts from the Living Atlas to my map, and I filtered to only show tracts in Arizona. Then I enriched this layer to add the number of households with any retirement income. GeoEnrichment added three fields to my layer’s tabular data: one with the prefix “ACS” which is the estimate, one with the prefix “MOE” which is the margin of error, and one with the prefix “REL” which is Esri’s reliability flag. The reliability flag field take values of 1, 2, or 3: high reliability, medium reliability, or low reliability. I want to filter out census tracts whose estimate of households with any retirement income is highly questionable, so I’ll only map features with a value of 1 or 2. In other words, I want to suppress any features with a reliability flag of 3.


First apply a filter such as the one below:


Be sure the dropdown menu at the top is set to “any” of the following expressions” rather than “all of the following expressions” since we want the records whose reliability flag is either 1 or 2.



I notice that not all tracts have the default orange symbol given. Using the original fields, I can verify that – sure enough – the ones that don’t have a symbol are the ones that had a reliability flag of 3.


Now I can change the style of my features, and configure the pop-ups as I want. As long as the filter is applied, only the records with high or medium reliability will display.


Suppress Using Your Own Threshold for the MOE


If you did not obtain your ACS data using geoenrichment and do not have the reliability flags, you can construct your own by using your own cutoff for the MOE. For example, the disability by age by race layer mentioned earlier only has fields for the estimates and the MOEs. Depending on how strict you want to be in deeming an estimate “unreliable,” choose a cutoff point of somewhere around 8 to 15 percent for the range-to-estimate ratio. A cutoff of 8 percent would be very strict, a cutoff of 10-12 percent would be fairly strict, and a cutoff of 15 percent would be less strict, only removing the most unreliable estimates. Create an Arcade Expression when styling the map and configuring the pop-up and you can customize your suppression logic.


Option 2: Map all the data and display the range in the pop-ups


When configuring your pop-up, use Attribute Expressions to create an upper bound and a lower bound on the fly with Arcade.  For example, my upper bound expression is simply the estimate (count field) plus the margin of error (MOE field):



Then insert these expressions into a custom attribute display:


You will then get the pop-up displayed below:



Remember, estimates of zero still have an MOE!  Write this into your Arcade Expression for the lower bound:


This way you will not get any negative numbers displaying as your lower bound.  For example, the following pop-up displays a range of 0 to 13, not -13 to 13.


Other examples of items in the Living Atlas that display these ranges in the pop-ups are an app of various occupations vulnerable to extreme heat and a web map of detailed Asian American ethnicities.


Need to combine a few fields for your web map and are curious how to compute the margins of error for calculated fields?  The Census Bureau has many resources on this very problem. I used their guidance on approximating the MOEs of combined estimates in the maps of occupations vulnerable to extreme heat, in which I had to add the male and female counts for each occupation.


Option 3: Use Transparency to Show the Estimate’s Reliability


I want to show how reliable those estimates are of elderly women with a disability by tract in a way that doesn’t require the person viewing this map click on every single pop-up.  One effective way to do this is by using transparency to visually indicate reliability.  In the Change Style options, we can vary the transparency based on an attribute’s values.


We can select the attribute we’d like to use, or in our case, we’ll add a new expression.


The expression dialogue box appears for us to name and type in our expression. We want to create an expression that shows the range as a percent of the estimate. Also, we can subtract it from 1 so that the smallest MOE percentages will appear darker (less transparent) :


Then back to setting the transparency based on attribute values:


I’d like to use a cutoff of 10% (.1), so I’ll have to click “Zoom in” to see that section of the histogram better:


Now those tracts with poor estimates are more transparent than those with more reliable estimates.  The transparency appears in the legend underneath the proportional symbols.  Configure your pop-up as discussed above, and you get the following map:


Many Living Atlas Layers Contain Margins of Error


If you’re working with American Community Survey data in ArcGIS , always check the Living Atlas first, to see if the variables you want have already been published as part of feature layer.  An ever-increasing number of layers in the ArcGIS Living Atlas contain data from the American Community Survey, and include the margins of error as fields.  Some example topics are household income, educational attainment, ancestry and ethnicity, veteran characteristics, health insurance, language spoken at home, transportation to work, housing unit characteristics, and poverty, just to name a few!


Now that you know some options for displaying the margins of error, I look forward to seeing how you choose to incorporate the MOEs in your own web maps!


For more information about the American Community Survey, see the Esri White Paper or the Census Bureau’s ACS Handbook for Data Users.

by Dan Pisut and Keith VanGraafeiland


Ever dip your foot into the ocean and think, “This water is perfect…I bet it’s about 82 degrees.” Well, there’s one way to be sure for any place around the world: satellite sea surface temperature data.  


Besides hunting for prime beach spots, SST is a key climate and weather measurement used for weather prediction, ocean forecasts, tropical cyclone forecasts, and in coastal applications such as fisheries, pollution monitoring and tourism. El Niño and La Niña are two examples of climate events, which are forecasted and monitored using sea surface temperature maps.   


A daily updated SST analysis is available in the Living Atlas (with an archive going back to 2008). By default, time animation is enabled. But if you disable time in the Properties, you can take advantage of the layer’s multidimensional settings using definition queries on the time to return just that particular layer. This selection works in ArcGIS Desktop or .


properties option

In addition to time analysis, this layer can be used for visualization  in web maps and in ArcGIS Desktop.  Two server-side processing template options can be used to help in these visualizations: cartographic vs analytic renderer, and convert Celsius to Fahrenheit. Convert C to F is pretty self-explanatory. The cartographic render presents the map as RGB values stretched from 0-255, which displays efficiently for fast visualization. The analytic renderer provides the map as its range of temperature values (-2 to 34.5). Using the analytic renderer means you can change the display of the data (e.g., range, color, etc).


In ArcGIS Pro, access these options from the Processing Templates in the layer Properties.


processing templates in ArcGIS Pro

Or in ArcGIS , you’ll click on Image Display to access the processing templates.


processing templates in ArcGIS

Since I’m iridisophobic, I use this render option to quickly change the color palette…maybe to something like my favorite “hurricane formation zone” color palette with a break at 26oC, or a luminance-controlled palette from dark purple to bright yellow.


GIF of two SST color palettes

Additionally, many other analyses can be performed using this layer, including:


  • Apply contours using Raster Functions
  • Chain together several operations using the Raster Function Editor and Model Builder.
  • Generate summary statistics
  • Plot a graph of temperatures


SST histogram graph

In other words, use the archive of SST as if it were local on your desktop. Combine it with other layers from the Living Atlas or your local data to explore the Earth-system or author beautiful maps. You can also quickly browse SST data in the Daily Sea Surface Temperaturetime aware application. 


Have questions or comments about this blog? Post them in our GeoNet.