Set up the project

To get started, you'll set up the project. You'll download and explore the data, create an ArcGIS Pro project, set up the environment, and create a Reality mapping workspace.

Note:

To work with Reality for ArcGIS Pro, the following software must be installed and licensed in the following order:

  • ArcGIS Pro Standard or Advanced, version 3.3 or later
  • ArcGIS Reality Studio
  • ArcGIS Reality for ArcGIS Pro extension
  • ArcGIS Coordinate System Data

This tutorial assumes that these steps were already completed. For step-by-step instructions, see the Install ArcGIS Reality for ArcGIS Pro page.

Download and explore the data

You'll download the data you need for this tutorial and review it. You'll start with the satellite imagery.

  1. Go to the Maxar resource page.

    Maxar resource page

  2. Read the license information on the page. Click the View-Ready (Standard) OR2A | 30 cm | 4 band | San Diego, California link to initiate the imagery download.

    Link to download the Maxar imagery

    A file named ESRI-data-6-13-2024.zip is downloaded.

    Note:

    This file is 12.8 GB in size and will take some time to download.

    Most web browsers download files to your computer's Downloads folder by default.

  3. In Microsoft File Explorer, right-click the ESRI-data-6-13-2024.zip file and unzip it to the C:\Sample_Data\SanDiegoSat_Data location on your computer, using a utility tool like 7-Zip.

    Extract Here menu option

  4. Right-click the extracted ESRI-data-6-13-2024 folder and rename it to Imagery.
  5. Browse to C:\Sample_Data\SanDiegoSat_Data\Imagery\050221198010_01 and examine the contents.

    Content of 050221198010_01 folder

    This folder contains all the satellite imagery you'll use as input data. It contains 26 subfolders housing images acquired by Maxar's WorldView-3 and WorldView-2 sensors. The image folders are listed in pairs ending in _MUL and _PAN. Each _MUL folder contains four-band multispectral RGB imagery and each _PAN folder contains single-band panchromatic imagery. Each pair represents a satellite scene, captured on a specific date. Together the images cover the area of interest for this tutorial. The date range of the images is from 2016 to 2024.

    Note:

    It is recommended that you limit the date range of the acquired images to be within one to three years. Larger date ranges may result in anomalies in the generated products due to changes in topography and features. However, there may be cases in which some of the required images are not available in the targeted date range or are lower quality. In such cases, an older image may be used. Most of the scenes used in this tutorial were acquired between 2022 and 2024 except for two that were captured in 2016 and 2020.

  6. Open the 050221198010_01_P001_MUL folder.

    050221198010_01_P001_MUL folder content

    This folder contains an image in TIFF format (.tif) along with the metadata files (.rpb, .imd, and .til) required for processing. It also contains a thumbnail in the JPEG format (.jpg).

  7. In the folder, double-click the 24APR28184216-M2AS-050221198010_01_P001-BROWSE.JPG thumbnail image to open it in your default image viewing application.

    Thumbnail image

    Note:

    All the images used in this tutorial were provided by Maxar. They are high-resolution satellite imagery captured with their WorldView-3 and WorldView-2 sensors. Learn more about WorldView-3 and WorldView-2.

  8. Close the window displaying the thumbnail image.

    You need a few more data files to support the workflow. You'll download them now.

  9. Download the Support_Data.zip file and unzip it to the C:\Sample_Data\SanDiegoSat_Data location on your computer.

    Extract Here menu option

    The extracted Support_Data folder contains the following subfolders:

    • In the AOI folder, two feature classes provide the boundaries for the area of interest (AOI) and the water bodies in that same area.
    • In the DEM folder, a digital elevation model (DEM) raster provides elevation information for the AOI. This information will be used to support the alignment process.
    • The Output folder contains the resulting product outputs of this tutorial. Optionally, you can use them later in the workflow.

    Support_Data folder content

Create a project and connect to the data

Now that you've downloaded the data and explored it, you'll create an ArcGIS Pro project and connect it to the data.

  1. Start ArcGIS Pro. If prompted, sign in using your licensed ArcGIS organizational account.
    Note:

    If you don't have access to ArcGIS Pro or an ArcGIS organizational account, see options for software access.

  2. On the ArcGIS Pro start screen, under New Project, click Map.

    Map button

  3. In the Create a New Project window, for Name, type SanDiegoSat_Reality.
  4. For Location, accept the default location or click the Browse button to choose a location, for instance, on drive C:.
    Note:
    Ensure that the location you choose has at least 130 gigabytes (GB) of available storage space.

    New Project window

  5. Click OK.

    The project opens and displays a map view.

    Initial project view

    Next, you'll connect the project to the data you downloaded.

  6. On the ribbon, click the View tab. In the Windows group, click Catalog Pane.

    Catalog Pane button

    The Catalog pane appears. This pane contains all the folders, files, and data associated with the project. You'll use this pane to establish a folder connection to the SanDiegoSat_Data folder.

  7. In the Catalog pane, click the arrow next to Folders to expand it.

    Folders expanded

    The default folder associated with the project is SanDiegoSat_Reality, a folder that was made when you created the project. For now, the folder contains some empty geodatabases and toolboxes, but no data.

  8. Right-click Folders and choose Add Folder Connection.

    Add Folder Connection menu option

  9. In the Add Folder Connection window, browse to Computer > This PC > C: > Sample_Data. Select the SanDiegoSat_Data folder and click OK.

    Add Folder Connection window

    In the Catalog pane, under Folders, the SanDiegoSat_Data folder is now listed.

    SanDiegoSat_Data folder

  10. Expand the SanDiegoSat_Data and Support_Data folders and confirm that the imagery and support data you saw earlier are present.

    Support_Data folder content

You can now access all of the data from within your ArcGIS Pro project.

Set up the environment

Next, you'll choose specific environment parameter values that the system will use when running imagery tools.

  1. On the ribbon, on the Analysis tab, in the Geoprocessing group, click Environments.

    Environments button

  2. Under Parallel Processing, for Parallel Processing Factor, type 90%.

    The parallel processing factor defines the percentage of your computer cores that will be used to support processing. For example, on a four-core machine, a setting of 50 percent means the operation will be spread over two processes (50% * 4 = 2).

    Parallel Processing Factor field

    Tip:

    Make sure to include the % sign in 90%.

  3. Scroll down to the Raster Storage section.
  4. Under Raster Statistics, for X skip factor and Y skip factor, type 10.

    Statistics must be computed on imagery to enable certain tasks, such as applying a contrast stretch. For efficiency, statistics can be generated for a sample of pixels instead of every pixel. The skip factor determines the sample size. A value of 10 in X and 10 in Y means that every eleventh pixel in the image row and column will be used to generate statistics.

  5. Under Tile Size, for Width and Height, type 512.

    For efficiency, imagery is often accessed in the form of small square fragments named tiles. This parameter defines the tile size, which you choose to be 512 by 512 pixels.

  6. For Resampling Method, choose Bilinear.

    Resampling is the process used to change a raster's cell size or orientation. Among different resampling methods available, bilinear is recommended when working with imagery data.

    Raster Storage section

  7. Accept all other defaults and click OK.

Create a workspace

Next, you'll create a Reality mapping workspace to gather and manage all your data.

  1. On the ribbon, on the Imagery tab, in the Reality Mapping group, click the New Workspace button.

    New Workspace button

    The New Reality Mapping Workspace wizard pane appears, showing the Workspace Configuration page.

    New Reality Mapping Workspace wizard pane

  2. Set the following parameters:
    • For Name, type SanDiegoSat_Workspace.
    • For Workspace Type, confirm that Reality Mapping is selected.
    • For Sensor Data Type, choose Satellite.

    Workspace Configuration parameters

  3. Accept all other defaults and click Next.

    The Image Collection page appears, where you'll enter parameters related to the sensors used to capture the images.

  4. In the Image Collection page, under Sensor 1, set the following parameters:
    • For Sensor Type, choose WorldView-3.
    • For Folder Containing Images, click the Browse button, browse to Folders > SanDiegoSat_Data > Imagery, select the 050221198010_01 folder, and click OK.

    Image Collection parameters

    Because two sensor types, WorldView-3 and WorldView-2, were used to capture the images to be processed, you must define a second sensor.

  5. Click Add Sensor.
  6. On the Image Collection page, under Sensor 2, set the following parameters:
    • For Sensor Type, choose WorldView-2.
    • For Folder Containing Images, click the Browse button, browse to Folders > SanDiegoSat_Data > Imagery, select the 050221198010_01 folder, and click OK.

    Add Sensor button

  7. For Workspace Spatial Reference, review the values that were populated based on the imagery's own horizontal (XY) and vertical (Z) coordinate systems.

    They are, respectively, WGC 1984 UTM Zone 11N and WGS 1984.

    Workspace Spatial Reference parameter

  8. Accept all other defaults and click Next.

    The Data Loader Options page appears. Here, you'll point to the DEM needed for the workflow.

  9. On the Data Loader Options page, set the following parameters:
    • Under Elevation Source, ensure DEM is selected.
    • Under DEM, click the Select DEM button, browse to Folders > SanDiegoSat_Data > Support_Data > DEM, select SRTM_gcs.tif, and click OK.
    • Ensure Geoid Correction is set to EGM96.
    • For Processing Template, choose Pansharpen.

    Data Loader Options parameters

    Note:

    Pansharpening is an image fusion process that combines a high-resolution panchromatic image with a lower resolution multispectral image to create a high-resolution multispectral image. This process takes advantage of the fact that the WorldView-3 and WorldView-2 images include both types of images.

  10. Expand the Advanced Options section and set the following parameters:
    • Ensure Estimate Statistics option is checked.
    • Expand Gamma. For Gamma Stretch, select User Defined. For Value, type 1.8.
    • Expand Pre-processing and ensure the box next to Calculate Statistics is checked.
    • For Number of Columns to Skip and Number of Rows to Skip, type 1.
    Note:

    The Gamma value was determined by reviewing the Gamma setting in the Symbology pane, when initially reviewing the image.

    Advanced Options section

  11. Accept all other defaults and click Finish.

    After a few minutes, the workspace is created. In the Logs: SanDiegoSat_Workspace window, the last line indicates that the process succeeded.

    Last line of the log indicates success.

    A new SanDiegoSat_Workspace map is also created.

    SanDiegoSat_Workspace map

    Various workspace components are now listed in the Contents pane. This includes Image Collection, a new mosaic dataset that contains 13 pairs of satellite images.

    Image Collection dataset

    The Image Collection dataset is represented primarily with a Footprint layer (green outlines) and an Image layer containing the images themselves. The two layers are displayed on the map.

    Image Collection dataset on the map

    Tip:

    If you can't see the images on the map, zoom in further. The visibility of the images is dependent on map scale.

    Moreover, a Reality Mapping tab has been added to the ribbon.

  12. On the ribbon, click the Reality Mapping tab.

    Reality Mapping tab

    The tab contains a series of tools that support imagery alignment and the production of Reality mapping products. Currently, the tools in the Product group are unavailable because your input images have not yet been adjusted.

  13. Review the content of the Catalog pane.

    Following the workspace creation, a Reality Mapping container was added to the project.

    Reality Mapping container

  14. Expand Reality Mapping, SanDiegoSat_Workspace, and its components.

    Components of the SanDiegoSat_Workspace

    This is where the workspace elements are stored. It includes an Imagery folder that houses a copy of the image collection layer and a Products folder with two empty subfolders—DEMs and Orthos—that will later be used to hold the outputs of the Reality mapping process.

    Note:

    A Meshes folder for storing mesh products will be added to this location after the mesh generation process later in the workflow.

  15. Collapse SanDiegoSat_Workspace.

    SanDiegoSat_Workspace collapsed

  16. On the Quick Access Toolbar, click the Save Project button to save your project.

    Save Project button

In this part of this workflow, you downloaded the input data, set up an ArcGIS Pro project, created a Reality mapping workspace, and populated it with input data. Next, you'll perform the image alignment and generate Reality mapping products.


Process the imagery

Now that your project, workspace, and imagery are set up, you'll start the image processing. First, you'll remove NoData areas in the imagery layer and improve the image alignment using tie points. Then, you'll generate the following products:

  • DSM—A digital surface model of the earth, including the elevation of objects on the ground surface such as trees and buildings. This is generated from a collection of overlapping images.
  • True Ortho—An orthorectified image without perspective distortion so that above-ground features do not lean and obscure other features.
  • DSM mesh—A textured model in which the adjusted images are draped on a triangulated irregular network (TIN) version of the DSM extracted from overlapping images.

A DSM and a True Ortho are 2D rasters meant to be represented in a 2D map. A DSM mesh is considered a 2.5D product because it is meant to be represented in a 3D scene. However, each point in the DSM mesh has only a single z-value (height), in contrast to 3D products that have multiple heights for each point.

Back up the workspace

Before proceeding, you'll create a backup of the workspace in case there is a need to return to a previous state of the project.

  1. In the Catalog pane, if necessary, expand the Reality Mapping container.

    Reality Mapping container expanded

  2. Right-click SanDiegoSat_Workspace and choose Copy.

    Copy menu option

  3. Right-click the Reality Mapping folder and choose Paste.

    Paste menu option

    A new file, SanDiegoSat _Workspace-Copy, is added to the Reality Mapping container.

  4. Right-click SanDiegoSat _Workspace-Copy, choose Rename, and change the folder name to SanDiegoSat_Workspace_orig.

    SanDiegoSat_Workspace_orig renamed

    This name signifies that this copy of the workspace represents its original state.

Remove areas with no data

Areas around the edges of the imagery that are filled with black pixels that have no information and are called NoData. These NoData areas obscure features beneath them on overlapping images and must be removed using the Build Footprint geoprocessing tool.

  1. In the SanDiegoSat_Workspace window, zoom in on the southern extremities of the image footprint.

    Elongated NoData areas appear in black.

    NoData areas

  2. On the ribbon, on the Analysis tab, in the Geoprocessing group, click Tools.

    Tools button

    The Geoprocessing pane appears.

  3. In the search box, type Build Footprints. In the list of results, click the Build Footprints tool to open it.

    Build Footprints tool search

  4. In the Build Footprints tool, for Mosaic Dataset, choose Image Collection.

    Build Footprints tool parameters

  5. Accept all other defaults and click Run.

    Once the process is complete, the NoData areas are removed from the map.

    NoData areas removed from the map

Improve image alignment with tie points

To improve the relative accuracy of your input images, you'll use tie points, which are common objects or locations identified in the overlapping areas between adjacent images. The Adjust tool automatically extracts tie points using image matching techniques and uses them to better align the images relative to one another.

  1. On the ribbon, on the Reality Mapping tab, in the Adjust group, click Adjust.

    Adjust button

    You'll set some of the Adjust tool parameters that determine the quality and precision of the tie points and image alignment process.

  2. In the Adjust window, confirm that Transformation Type is set to RPC.

    Adjust window

    Note:

    Rational Polynomial Coefficients (RPC) is a mathematical model that describes the relation between the sensor and the ground. Imagery vendors provide an RPC file for compatible product types.

  3. Expand the Advanced Options section and Tie Point Matching.
  4. Under Tie Point Matching, set the following parameters:
    • For Image Location Accuracy, choose Low, which uses a larger search radius and the SIFT (scale invariant feature transformation) algorithm to generate a high number of tie points.
    • For Tie Point Similarity, choose High to have only points that are highly similar taken into account.
    • For Tie Point Density, choose High to create the highest number of points possible.
    • For Tie Point Distribution, confirm that Random is selected to ensure the generated tie points are well distributed over the images.

    Advanced Options section

  5. Accept all other default values and click Run.

    The process takes several minutes to run. You can follow the progress in the Logs window. The tool first reports to be Computing the tie points, then Computing block adjustment, and finally Applying block adjustment. For the purpose of the alignment process, the images are grouped into blocks of several images. The position of the blocks is then adjusted.

  6. In the Logs window, confirm that the process is complete by locating the Succeeded message displayed after Applying Block Adjustment.

    The Applying Block Adjustment process was successful.

  7. Under Computing Block Adjustment, locate the RMSE_TIE_IMAGE(xy) line.

    RMSE_TIE_IMAGE(xy) line

    This line indicates the accuracy of the adjustment in pixels, based on the computed tie points. A root mean square error (RMSE) of less than one pixel is acceptable.

    Note:

    The accuracy number you obtain might be slightly different from the one in the example image.

  8. In the Contents pane, check the Tie Points layer box to turn it on.

    Tie Points layer turned on

    On the map, the tie points generated by the Adjust tool appear.

    Tie points on the map

  9. In the Contents pane, uncheck the Tie Points box to turn the layer off.

    Tie Points turned off

You have optimized the relative accuracy of your images.

Note:

To improve the absolute accuracy, ground control points (GCPs) can be added. The addition of GCPs will not be covered in this tutorial. See Generate DSMs and True Orthos with ArcGIS Reality for ArcGIS Pro for an example of how to add GCPs to a project.

Generate Reality mapping products

Next, you'll generate the Reality mapping products. For brevity, you'll only generate these products for a small area. The SanDiego_AOI.shp layer provides the boundaries for that area. You'll add it to the map.

  1. In the Catalog pane, expand Folders, SanDiegoSat_Data, Support_Data, and AOI.

    Expanded AOI folder

  2. Right-click SanDiego_AOI.shp and choose Add To Current Map.

    Add To Current Map menu option

    On the map, the AOI polygon appears in a randomly assigned color (light blue in the example images).

    AOI polygon on the map

    The image coverage is larger than the AOI polygon. This ensures that all images that have any overlap with the AOI are included. All of these overlapping images must be used to generate high quality results.

    Since there is a large body of water within the project area, it is recommended that a layer representing the water body boundaries be used to hydro-constrain (or flatten) the areas covered by water. For that purpose, you'll use the feature class provided, Waterbody.shp.

  3. In the Catalog pane, in the AOI folder, right-click Waterbody.shp and choose Add To Current Map.

    Add To Current Map menu option

    On the map, the Waterbody polygon appears in a randomly assigned color (light yellow in the example images).

    Waterbody polygon on the map

  4. In the Contents pane, turn off the SanDiego_AOI and Waterbody layers, as you don't need to see them on the map for the rest of the workflow.

    SanDiego_AOI and Waterbody layers turned off

  5. On the ribbon, on the Reality Mapping tab, review the Product group.

    Product group

    Following the image adjustment process, the tools within the group are now available. Products can be generated individually using the product buttons (such as DSM, True Ortho or DSM Mesh), or all at once using the Multiple Products button. You'll use the latter option.

  6. On the Reality Mapping tab, click the Multiple Products button.

    Multiple Products button

    The Reality Mapping Products Wizard pane appears, displaying the Product Generation Settings page.

    Reality Mapping Products Wizard

  7. Confirm that all the 2D product boxes are checked (Digital Surface Model (DSM), True Ortho, and DSM Mesh). Click Shared Advanced Settings.

    2D products checked

    The Advanced Product Settings window appears. It allows you to set parameters that affect all the products to be generated.

  8. In the Advanced Product Settings window, for Quality, confirm that Ultra is selected.

    The Ultra value will result in the derived products having the highest image resolution. A Quality setting of High would result in products having resolutions two times the source image resolution.

  9. For Product Boundary, choose SanDiego_AOI.shp.

    The Reality products generated will be limited to the extent defined by this feature class.

  10. For Waterbody Features, choose Waterbody.
  11. For Processing Folder, click the Browse button. Browse to a folder on a disk drive that has a minimum available storage of 10 times the total size of the images being processed.
    Caution:

    The processing folder stores temporary files generated during Reality processing. It is recommended that the processing folder be located on a fast drive with large available storage space.

    In this workflow, there is about 13 GB of imagery, so you would need 130 GB of processing space.

    Advanced Product Settings window

  12. Accept all other defaults and click OK.
  13. In the Reality Mapping Products Wizard pane, on the Product Generation Settings page, click Next.
  14. On the DSM Settings page, set the following parameters:
    • For Output Type, choose Mosaic.
    • For Format, choose Cloud Raster Format.
    • For Compression, confirm that None is selected.
    • For Resampling, confirm that Bilinear is selected.

    DSM Settings parameters

  15. Click Next. On the True Ortho Settings page, set the following parameters:
    • For Output Type, choose Mosaic.
    • For Format, choose Cloud Raster Format.
    • For Compression, confirm that None is selected.
    • For Resampling, confirm that Bilinear is selected.

    True Ortho Settings parameters

  16. Click Next. On the DSM Mesh Settings page, for Format, confirm that SLPK is selected.

    DSM Mesh Settings parameters.

    Note:

    Depending on your system resources, the product generation process may take approximately three hours. For reference, the processing time on a computer with an Intel i7-9850 processor, 32GB RAM, and an SSD hard drive took three hours and six minutes.

    If you prefer not to run this process to save time, you can use ready-made output datasets for the rest of the tutorial. In the Catalog pane, browse to Folders > SanDiegoSat_Data > Support_Data > Output. Right-click SanDiegoSat_DSM.crf and choose Add To Current Map. Do the same for SanDiegoSat_TrueOrtho.crf. You'll add SanDiegoSat_DSM_Mesh.slpk to a 3D scene later in the workflow.

    Provided output files

    If you decide to use the ready-made output dataset, proceed to the next section, Examine the results.

  17. If you decide to run the process, click Finish.

    Finish button

    During the process, status information is displayed in the Logs window. When the process is complete, the log indicates that the process succeeded. The last part of the process is generating mosaics from tiles.

    The Generating Mosaic from Tiles process was successful.

  18. Press Ctrl+S to save the project.

In this part of the workflow, you processed the imagery. First, you removed NoData areas in the imagery layer and improved the image alignment using tie points. Then, you generated the Reality mapping products.


Examine the results

You have generated three Reality mapping products (alternatively, you may have chosen to use the ready-made products): a True Ortho, a DSM, and a DSM mesh. Next, you'll examine them.

Examine the True Ortho output

After the product generation, both the DSM and True Ortho products were automatically added to the SanDiegoSat_Workspace map and the Contents pane. After reorganizing the view on the map, you'll examine the True Ortho.

  1. In the Contents pane, under Image Collection, turn off the Footprint and Image layers.

    Footprint and Image turned off

  2. Right-click the True Ortho layer and choose Zoom To Layer.

    Zoom To Layer menu option

    The True Ortho output layer displays over the basemap.

    True Ortho output layer displayed over the basemap

  3. Use the mouse wheel to zoom in and drag to pan. Observe the highly detailed features.

    Next, you'll compare the True Ortho image to the original satellite imagery.

  4. In the Contents pane, turn off the DSM layer.

    DSM turned off

  5. Under Image Collection, turn on the Image layer.

    Image layer turned on

    You'll use an imported bookmark to examine a specific location.

  6. On the ribbon, on the Map tab, in the Navigate group, click Bookmarks and choose Import Bookmarks.

    Import Bookmarks menu option

  7. In the Import window, browse to Folders > SanDiegoSat_Data > Support_Data > Output, click Location for comparison.bkmx, and click OK.

    Import window

  8. On the Map tab, click Bookmarks and choose Location for comparison.

    Location for comparison bookmark

    The map zooms to the area where you'll compare the two layers.

  9. In the Contents pane, click the True Ortho layer to select it.

    True Ortho layer selected

  10. On the ribbon, on the Raster Layer tab, in the Compare group, click Swipe.

    Swipe button

  11. On the map, drag the pointer from top to bottom to peel off the True Ortho layer and reveal the input Image mosaic layer underneath.

    Swiping the image

    In the original Image layer, the sides of the building are visible; it is displaced because of the sensor's off-nadir angle. In contrast, in the True Ortho layer, the same building is vertically oriented (you are viewing it from above). With the displacement errors removed from the True Ortho, above-ground structures are vertically aligned. If the measured accuracy falls within accepted tolerances, this True Ortho can be used to accurately extract features, such as building footprints.

    Note:

    The absolute accuracy of the True Ortho features is directly related to the accuracy of the ground control points used to support the alignment process. Since this True Ortho was created without the use of authoritative ground control points, its absolute accuracy is unknown. However, the relative accuracy can be determined from the RMSE of the tie points, which for this project is RMSE X 0.271, Y 0.284 (pixels).

  12. On the ribbon, on the Map tab, in the Navigate group, click the Explore button to exit the swipe mode.

    Explore button

Examine the DSM output

Next, you'll review the generated DSM.

  1. In the Contents pane, under Data Products, turn off the True Ortho layer and turn on the DSM layer.

    DSM layer turned on

  2. In the Contents pane, under Image Collection, turn off the Image layer to better see the DSM.

    DSM on the map

    Observe how the elevation of buildings, water, and other features is represented. You'll review the layer's properties.

  3. In the Contents pane, right-click the DSM layer and choose Properties.

    Properties menu option

  4. In the Layer Properties window, click the Source tab, expand the Raster Information section, and locate the Cell Size X and Cell Size Y fields.

    Layer Properties window

    The cell size of the DSM raster is 0.3 meters, or 30 centimeters. With the Pansharpen option you selected earlier, ArcGIS Reality for ArcGIS Pro generated a DSM that matches the highest resolution of the input imagery (in this case, the panchromatic imagery).

  5. Click OK to close the Layer Properties window.

    To view the DSM from another perspective, you'll create a hillshade layer, in which shading creates a three-dimensional appearance and gives a sense of the relief.

  6. On the ribbon, on the Imagery tab, in the Analysis group, click the Raster Functions button.

    Raster Functions button

  7. In the Raster Functions pane, type Hillshade in the search box. Click the Hillshade raster function to open it.

    Hillshade raster function search

  8. In the Hillshade Properties pane, for Raster, choose DSM.

    Hillshade Properties pane

  9. Accept all other defaults and click Create new layer.

    The hillshade layer appears on the map.

    Hillshade layer on the map

  10. Zoom in and pan to observe the relief and the details of the features’ volume.

Examine the DSM mesh output

Next, you'll review the generated DSM mesh displayed in a 3D scene.

  1. In the Catalog pane, under Reality Mapping, expand SanDiegoSat_Workspace > Products > Meshes.

    Meshes folder expanded

  2. Right-click DSM_Mesh.slpk, point to Add To New, and choose Local Scene.

    Local Scene menu option

    Note:

    If you are using the ready-made 3D products, go to Folders > SanDiegoSat_Data > Support_Data > Output and add SanDiegoSat_DSM_Mesh.slpk to a local scene.

    The DSM mesh appears in a new 3D scene.

    DSM mesh in a new 3D scene

    To better explore the mesh layer, you'll zoom, tilt, and rotate the scene with the Navigator wheel.

  3. Zoom in with the mouse wheel until you see the larger buildings clearly.
  4. In the scene, locate the Navigator wheel at the bottom left of the scene. Click the Show full control button to access the 3D navigation functionality.

    Show full control button

    The Navigator wheel changes to a 3D sphere and an additional wheel appears for 3D navigation.

  5. In the expanded Navigator wheel, use the middle wheel to tilt and rotate the scene. Use the mouse scroll wheel to zoom in and out.

    Navigator middle wheel

    Tip:

    Alternatively, you can also navigate the scene with the keyboard, pressing the following keys: V to tilt, B to rotate, C to pan, and Z to zoom, used in combination with the Up, Down, Left, and Right arrow keys.

  6. Explore the Mesh layer, looking at it from various angles.

    Mesh layer in the 3D scene

    The layer exposes buildings, vegetation, and ground features in photorealistic details.

  7. When you finish exploring, in the Contents pane, right-click the Mesh layer and choose Zoom To Layer.
  8. Press Ctrl+S to save the project.

To expand access to these Reality mapping output datasets, you can publish them to your organization's ArcGIS Online account. You saw an example of a DSM mesh displaying in an online 3D scene at the beginning of the tutorial. Learn more on the Publishing hosted scene layers page. The output datasets can also be integrated in various projects and combined with other GIS layers.

In this tutorial, you generated Reality mapping products using high-resolution, overlapping satellite imagery covering a section of San Diego. You downloaded input data and created a workspace in an ArcGIS Pro project to manage it. You then removed NoData areas and improved the image alignment using automatically generated tie points. You used the Reality Mapping Products Wizard to generate a high-resolution DSM, a True Ortho, and an integrated DSM mesh from the aligned images. Finally, you examined the output products.

You can find more Reality mapping tutorials in the tutorial gallery.