What's new in ArcGIS tutorials April 2026
Set up a flood simulation
In 2024, the United States experienced 27 weather- and climate-related events that resulted in damage of more than $1 billion each to affected communities and their infrastructure. Severe rainfall and flooding events make up a significant portion of these costs, with Hurricane Helene alone causing $79.6 billion in damage to the southeastern United States. Understanding and preparing for flooding caused by these extreme weather events has become a critical need for communities.
In this two-part tutorial series, you'll use ArcGIS Pro to perform a sophisticated flood simulation for a hypothetical high rainfall event in Houston, Texas. By analyzing the results alongside structure and road data, it's possible to predict how infrastructure might be impacted by such an event.
In this tutorial, the first in the series, you'll prepare the data necessary to perform the simulation. In particular, you'll use land cover and impervious surface data to create a water infiltration raster layer that shows how quickly water enters the soil, with areas of low infiltration being more susceptible to flooding. In the second tutorial, you'll use the data you prepared to simulate flooding and analyze potential impacts to infrastructure.
Simulate a flood
In this tutorial, the second in the series, you'll use the prepared data to perform the simulation. Then, you'll export the results as a flood depth raster, which you'll compare to buildings and roads data to determine how much infrastructure might be impacted by the flood event. You'll also configure flood depth charts to quickly view the impacts at different flood levels.
Calculate a field in Map Viewer
You've received sales data from a colleague for your company's store locations. You must identify any regional or spatial patterns in the data that might explain how stores are performing. After mapping the data, you notice that the dataset is missing a key metric—net operating income (NOI)—that you'll need to calculate. There are several options for calculating data in Map Viewer. In this tutorial, you'll decide on the best method for your goals and calculate a new field in Map Viewer to better understand regional performance patterns.
Clip raster data
You have a raster image of a historical paper map of Hallstatt, Austria, that you want to use as a background layer in ArcGIS Pro. However, the image is much larger than your area of interest. The unneeded parts of the image take up storage space and increase the image processing time. In this tutorial, you'll make a copy of the raster image that is clipped to the area of interest. Because you have other raster datasets you want to clip for the same reason, you'll perform batch processing to clip all of them at once. Lastly, you'll package the results as a project package so they can all be shared as one file.
Combine raster data into a mosaic
To properly visualize and analyze raster data, it's sometimes necessary to merge multiple raster datasets into one. A mosaic is a combination of two or more images. In this tutorial, you have two elevation datasets for the area of Hallstatt, Austria. You want to compare these datasets to another layer and use them for analysis. Rather than compare and analyze each dataset individually, you'll create a mosaic that combines them.
Create a 3D subsurface visualization of aquifers
Kent and Sussex counties in Delaware depend on groundwater for household consumption, agriculture, and industry. To effectively use and manage this critical natural resource, it is important to understand the geographic extent and thickness of the aquifers. Geologists used borehole records to identify the depth to, and thickness of, 12 confined aquifers throughout the counties.
In this tutorial, you'll create a public visualization of the aquifers. You'll create 3D models in ArcGIS Pro and publish them in ArcGIS Online to view in Scene Viewer.
Get started with ArcGIS Data Pipelines
The New York City Department of Parks and Recreation (DPR) maintains a database of capital improvement projects as a .csv table. However, other departments within the city would like to know additional information about each capital project, such as the age of each project from its initial design or which neighborhood contains each capital project.
In the past, adding more information to this list of park projects has been a time-consuming, manual process. Specifically, it entails the following:
- Querying projects that are in the construction phase
- Projecting data to an appropriate coordinate system for New York City
- Calculating the amount of time that has passed since the project was initially designed
- Determining which neighborhood tabulation area the project falls within
- Determining which community district each project falls within
- Removing numerous attributes that are not necessary for the stakeholders
- Renaming three attribute fields whose current names are vague and unintuitive
To automate this workflow and keep your data up to date, you'll use ArcGIS Data Pipelines to extract information from the New York City OpenData website, load it into ArcGIS Enterprise, and transform it by adding the requested attributes. Finally, you'll have this data pipeline run on a schedule to keep your list of capital projects current.
Inspect and visualize imagery
Imagery is an important type of data used in most remote sensing-based workflows. Imagery can be any optical satellite or aerial image. You can use it as a backdrop for other layers or analyze it to extract information beyond what the eye can see. In this introductory tutorial, you'll learn how to understand and display imagery in ArcGIS Pro. First, you'll inspect the properties of an imagery dataset to learn more about its cell size, pixel characteristics, and spectral bands. Then, you'll change the image's appearance to make it smoother and more vivid. Lastly, you'll change the band combination to better distinguish vegetation in the image. The skills you'll learn in this tutorial can be applied to nearly any imagery workflow in ArcGIS Pro.
Solve common projection issues
Projections are calculations that allow you to draw the round earth on a flat screen or piece of paper. To function in a GIS, every layer needs to be defined within a coordinate system, which allows it to be projected onto the map. Issues with the projection can cause data to not appear correctly or at all.
In this tutorial, you'll identify and fix the following three common projection issues:
- A layer with no defined projection, causing it to appear in the wrong place
- A layer with a projection that is different than the one used in the project
- A layer that is misaligned with the other map layers
You'll primarily work with raster data, although the issues and their solutions also apply to other types of data, such as feature classes. To learn how to resolve projection issues for a feature class, try the Fix data when it appears in the wrong place tutorial.