Inspect and preprocess imagery data

Imagery is an important type of data that most remote sensing-based workflows use. Imagery can be any optical satellite or aerial image. You can use it as a backdrop for your other layers or analyze it to extract information beyond what the eye can see. In this section, you'll inspect the properties of an imagery dataset and optimize its appearance.

Note:

In real-life projects, the data preparation often takes more time than you may expect. This lesson will give you a sense of the varied tasks that go into doing this work. When working with imagery or other types of raster data, you start by inspecting every layer to understand its properties and detect any anomalies. You then correct these anomalies and make sure that all your layers are set up similarly so they can become part of the same analysis. You also choose the right rendering or symbology to optimize each layer's appearance and legibility. Then, you may want to generate new derived layers. Finally, you save the layers or package them to share them with other analysts involved in the project.

Download and set up the project package

First, you'll download a .zip compressed folder containing the ArcGIS Pro project and the data needed to complete this lesson.

  1. Download the HallstattImagery.zip and extract it a location of your choice, such as the Documents folder.
    Note:

    Depending on your web browser, you may be prompted to choose a file location before you begin the download. Most browsers download to your computer's Downloads folder by default.

  2. Locate and open the extracted HallstattImagery folder. Double-click HallstattImagery.aprx to open the project in ArcGIS Pro. If prompted, sign in to your ArcGIS account.

    Double-click HallstattImagery.aprx to open the project in

    Note:

    If you don't have ArcGIS Pro or an ArcGIS account, you can sign up for an ArcGIS free trial.

    The project appears in ArcGIS Pro.

    The project appears in

    The project's initial map has only one image displayed, Hallstatt_Image.tif, as well as the basemap layers. However, you downloaded many more layers, which are stored in the project folder on your local drive. You'll review the structure and content of that folder.

  3. On the ribbon, on the View map, in the Windows group, click Catalog Pane.

    Catalog Pane button

    The Catalog pane appears.

  4. In the Catalog pane, expand Folders, and expand HallstattImagery.

    Review the contents and folder organization and note how the source images and rasters are categorized and stored, especially in the DEM, DSM, Imagery, and ScannedMap subfolders. You'll process and explore these items in the lesson, and you'll also add new derived raster datasets to some of these folders.

    Folder organization in the Catalog pane

Note:

The data used in this lesson comes from the State of Upper Austria, which provides various regional vector and raster data layers under a Creative Commons Attribution 4.0 Austria license. If you have any questions about this data, use the following contact information:

Office of Upper Austria. State Government

Directorate Presidium, Department Presidium, Landhausplatz 1, 4021 Linz

Telephone: (+43 732) 77 20-111 61

Fax: (+43 732) 77 20-21 16 21

Email: praes.post@ooe.gv.at

Inspect the properties of the imagery

Hallstatt_Image.tif, the imagery layer that was already placed for you on the map, is a multispectral aerial image that contains four spectral bands (red, green, blue, and near infrared) and shows the Hallstatt area. You'll inspect that image.

  1. First, in the Contents pane, review the legend of the Hallstatt_Image.tif image.

    It lists three bands that are currently displayed: Red: Band_1, Green: Band_2, and Blue: Band_3. Band_4 (near infrared) is not currently displayed.

    Hallstatt_Image.tif legend showing the three bands currently displayed

    Note:

    Each band is represented by a raster: a grid of cells (or pixels) organized into rows and columns in which each cell contains a value. The bands are stacked up, and together, the bands form a composite image dataset that displays in color.

    To see the raster grid, you can zoom in to the image with the mouse wheel button until you can see the individual pixels. Then zoom back out to see the full extent of the image.

    You'll now inspect some of the raster dataset properties of this image.

  2. In the Contents pane, right-click Hallstatt_Image.tif, and click Properties.

    Properties menu option

    The Layer Properties window appears.

  3. In the Layer Properties window, click Source.

    The Source properties report various details for the layer source, such as the data location on disk and the number of rows and columns of pixels.

  4. In the Source pane, expand the Raster Information section and review the Columns and Rows properties.

    Columns and Rows properties

    This shows how many pixels are in the x direction and y direction, respectively. You can multiply the columns and rows to find how many pixels are in the entire image.

  5. Review the Number of Bands property.

    As described earlier, there are four bands.

  6. Review Cell Size X and Cell Size Y.

    Cell Size X and Cell Size Y properties

    Cell size tells you the pixel size, or resolution, of the raster; in this case, the value is 0.2. Usually, pixel size is the same for x and y, meaning it is a square pixel. But what is the unit of the 0.2 value? You'll check the Linear Unit property under Spatial Reference to determine the unit.

  7. In the Source pane, expand Spatial Reference, and note the Linear Unit property.

    Linear Unit property

    The Linear Unit property for this raster is Meters (1.0). Therefore, each pixel represents a surface on the ground of 0.2 by 0.2 meters, or 20 by 20 centimeters.

  8. Collapse Spatial Reference.
  9. Next, under Raster Information, locate Pixel Type and Pixel Depth.

    Pixel Type and Pixel Depth properties

    The pixel type is unsigned char, which means that each band of the raster contains only positive pixel values. The pixel depth is 8 Bit, which means that a pixel can hold 256 different values. Since the type is unsigned, the values can range between 0 and 255.

  10. In the Source pane, collapse Raster Information and expand Statistics.

    Raster statistics

    Statistics are reported for each of the four bands in the raster dataset.

    Note:

    Raster statistics include the minimum and maximum pixel values, as well as the mean and standard deviation of the pixel values. Statistics are needed to properly symbolize and render raster data.

  11. In the Source pane, collapse Statistics. Expand Spatial Reference.

    Spatial Reference properties

    Note:

    To function in a GIS, every layer needs to be defined within a coordinate system.

    The Projected Coordinate System property is set to MGI Austria GK Central, a coordinate system commonly used for this region of Austria. As an analyst, for the Upper Austria government, you know that this is the preferred choice for the project, so you won't have to change it. Later in the lesson, you'll encounter other data layers that use a different coordinate system and that you'll need to reproject.

  12. Optionally, continue exploring additional properties. Click OK to close the Properties window.
    Note:

    It is important to become comfortable with inspecting the properties of the rasters you are using.

    Next, you'll explore your composite image further with the Image Information pane.

  13. In the Contents pane, ensure Hallstatt_Image.tif is selected. On the ribbon, on the Imagery tab, in the Tools group, click the Image Information button.

    Image Information button

    The Image Information pane displays contextual information about the raster layer.

  14. On the map, point anywhere on the Hallstatt_Image.tif imagery layer.
    • The Location section shows geographic information about the current location of your pointer.
    • The Spectral section shows the image's spectral information at the location of your pointer. This means that it shows the value of the current pixel for each band.
    • The Quick View section shows information about the sensor that captured the image, if that metadata is available.

    Image Information pane

  15. On the map, point to the lake (water) on Hallstatt_Image.tif.

    Water band details

    In the spectral information, the Band 1 (red) and Band 4 (near infrared) values are low, as is typical for water.

  16. Point to a dark green, forested area (dark green).

    Forest band details

    Notice that the near infrared band value is particularly high. This is because the cell structure of healthy vegetation strongly reflects near infrared light.

    Note:

    It is these variations in band values that will enable image analysis later on, such as identifying the different types of land cover appearing in the imagery (water, vegetation, bare soil, human-made buildings, and so on).

  17. Continue exploring, and when finished, close the Image Information pane.

Improve the symbology of the image

In this section, you'll learn how to change the appearance of the raster image. First, you'll zoom in on a specific area of the map.

  1. On the Map tab, in the Navigate group, click Bookmarks, and choose Hallstatt.

    Hallstatt bookmark

    The map zooms to the extent of the town and some of the surrounding forest and lake.

    Bookmark extent

    Next, you'll add to the map a duplicate of the Hallstatt_Image.tif image. This will allow you to compare various appearance updates you'll make to the original layer.

  2. In the Catalog pane, expand Folders and the Imagery folder. Right-click Hallstatt_Duplicate.tif and choose Add To Current Map.

    Add To Current Map menu option

  3. In the Contents pane, drag Hallstatt_Duplicate.tif below Hallstatt_Image.tif. Ensure that both layers are turned on. Click Hallstatt_Image.tif to select it.

    Hallstatt_Image.tif and Hallstatt_Duplicate.tif in Contents pane

    For now, the two layers are identical.

    Next, you'll try out different types of image stretches.

    Note:

    Image stretches take the original value range of an image raster and spread it (or stretch it) to take advantage of all the possible values offered by the raster's bit depth. For instance, the values in a raster may originally vary from 34 to 148. When a stretch such as Minimum Maximum is applied, the values will be transformed to use the entire range from 0 to 255. This will make the image appear more vivid and contrasted.

    By default, both Hallstatt_ Image.tif and Hallstatt_Duplicate.tif are set to the Percent Clip stretch, which is a good default stretch for imagery. You'll compare that stretch to no stretch.

  4. In the Contents pane, verify that Hallstatt_ Image.tif is selected. On the ribbon, on the Appearance tab, in the Rendering group, click the Stretch Type drop-down menu and choose None.

    Choose None in the Stretch Type drop-down menu.

    You'll use the Swipe tool to compare the two images.

  5. On the ribbon, on the Appearance tab, in the Compare group, click the Swipe tool.

    Swipe tool

    You can use the Swipe tool to pull back the layer that is selected in the Contents pane to reveal what is below. In this case, the Swipe tool pulls back the Hallstatt_image.tif layer to reveal what the Hallstatt_Duplicate.tif layer looks like. This allows you to compare the two layers.

  6. On the map, place the pointer near the edge of the image. Slowly drag the pointer from top to bottom or left to right.

    Use the Swipe tool.

    You can see that the image with no stretch applied is less vivid and has less contrast.

  7. Select other stretch types in the Stretch Type menu, and use the Swipe tool to compare to the default. See which of the stretch types produces the best image for you. If you do not have a preference, choose Percent Clip.
    Note:

    As a general rule, applying some type of stretch gives a better rendition of imagery than no stretch at all. Percent Clip is a good default for imagery. Percent Clip cuts off a percentage of the highest and lowest pixel values to reduce the effect of outliers and applies a linear stretch to the remaining values.

    You can learn more about the different types of stretches in the Change the appearance of imagery documentation.

    You'll now turn your attention to the resampling type.

  8. At the bottom of the Map view, for the map scale, type 1:200 and press Enter.

    Zoom to pixel size.

    You can see individual pixels and where the village buildings are located.

  9. On the Appearance tab, click the Resampling Type drop-down menu, and choose Bilinear.

    Apply resampling.

    Use the Swipe tool to compare the Bilinear type and the default type (Nearest Neighbor).

    Review resampling with Swipe.

    You can see that the Bilinear resampling type has a smoother look, so you don't see the actual pixels. Instead there is a smooth transition between pixels. This is achieved by averaging the value of neighboring cells. In general, the Bilinear resampling method is most commonly used for imagery. You'll keep Bilinear as the resampling type.

    Note:

    This resampling option only governs the way the image is displayed. Later in the lesson, you'll encounter other types of resampling actions that change the actual image file permanently.

  10. On the ribbon, on the Map tab, click Bookmarks, and choose Hallstatt.

    Currently, the band combination displayed is Natural Color (red, green, and blue bands), which is closest to what is seen by the human eye. Next, you'll change the band combination to include the near infrared band, which is good to highlight vegetation.

  11. On the Appearance tab, click the Band Combination drop-down menu, and choose Color Infrared.

    Apply band combination.

    Since you have a near-infrared band, you can create a Color Infrared (or false color) composite, in which the near-infrared band is displayed as red, the red band is displayed as green, and the green band is displayed as blue. Notice how color Infrared highlights vegetation (in red) and water (in black).

    Review the Color Infrared band combination.

  12. Use the Swipe tool to compare the Color Infrared and the default Natural Color band combinations.

    For instance, in Natural Color, it was hard to distinguish whether there was any vegetation inside the village. With Color Infrared, the small vegetated areas between the buildings pop up clearly in bright red.

    Note:

    If your imagery had more than four bands, you could create even more band combinations. Different band combinations highlight different features in the imagery. See the Learn ArcGIS lessons Get started with imagery and Assess burn scars with satellite imagery for more examples.

  13. To exit the Swipe mode, on the ribbon, on the Map tab, in the Navigate group, click the Explore tool.

    Explore tool

  14. On the Appearance tab, in the Rendering group, click the Symbology button to display the Symbology pane.

    Symbology button

    Notice that most of the tasks you have performed to change image appearance, such as setting the Stretch type, are also accessible from the Symbology pane.

    Symbology pane

    Note:

    Any changes to the appearance of a layer are only for visual display purposes and do not actually change the source data. Changes do not persist unless you save the project or save a layer file. Saving the project saves the state of the layer as you have edited it, but only within this project. Saving a layer file saves the layer appearance and allows that same appearance to be reused in multiple projects.

    Next, you'll create a layer file to persist the stretch, resampling, and band combinations you have applied to the layer.

  15. In the Contents pane, right-click Hallstatt_Image.tif, point to Sharing, and choose Save As Layer File.

    Create a layer file.

    A window appears that allows you to choose where to save your layer. The saved layer file has a .lyrx extension.

  16. In the Save Layer File window, browse to your Imagery folder. For Name, type Hallstatt_ColorInfrared, and click Save.

    Save Layer(s) As LYRX File window

  17. In the Catalog pane, browse and right-click the Hallstatt_ColorInfrared layer file and choose Add To Current Map.

    Add To Current Map for Hallstatt_ColorInfrared.lyrx in the Imagery folder on the Catalog pane

    The layer is added to the map. You can see that the layer file saved all the appearance and symbology parameters that you had set.

  18. In the Contents pane, right-click the top Hallstatt_Image.tif layer you just added, and click Remove, as you no longer need it. Similarly, remove Hallstatt_Duplicate.tif.

    Only the Hallstatt_Image.tif and the basemap layers remain.

  19. On the Quick Access Toolbar, click Save to save your project.

    Save button

In this module, you inspected the properties of an imagery raster dataset. You also changed the appearance of the imagery and saved those choices to a layer file. Your image is now ready for further exploration and analysis by the Upper Austria region's planners. In the next module, you'll work with elevation data.


Inspect and preprocess elevation data

In this module, you'll work with raster elevation data. Elevation data provides you with valuable information and can also be used to derive other types of raster layers. A digital elevation model (DEM) is a raster that shows the elevation of the ground or terrain. A digital surface model (DSM) is another type of elevation raster that shows the height of the surface, such as the top of the buildings or the top of the tree canopy. You'll prepare a DEM and a DSM for analysis, and also derive a slope layer.

Note:

Elevation rasters come from remote sensed data, such as a lidar point cloud. If you want to learn more about deriving elevation rasters and other types of information from a lidar point cloud, see the Learn ArcGIS lesson Extract 3D buildings from lidar data.

Inspect the DEMs

In this section, you'll start working with the data in the DEM folder. The area of Hallstatt is covered by two side-by-side DEMs. You'll inspect the two DEM files to determine how you need to prepare them to make them ready for analysis.

  1. In the Catalog pane, expand Folders, HallstattImagery, and the DEM folder.

    There are two DEMs in the folder: EastDEM40.tif and WestDEM50.tif.

    Source DEMs

  2. Right-click EastDEM40.tif and choose Add To Current Map. Do the same with WestDEM50.tif.
    Note:

    If a Calculate statistics window appears asking you whether you want to calculate statistics for one of these rasters, click Yes.

    As you saw earlier, statistics are needed to properly symbolize and render raster data, and they do not always come built in with the raw data.

    The two rasters appear on the map, side by side.

    DEMs side by side

    Unlike multispectral imagery, they are not composed of several bands, and each one contains a single raster. The darker areas represent low elevation and the lighter areas represent high elevation. The symbology seems to change abruptly from one DEM to the other. That's because for now, each raster has its own default stretch applied to it.

    You'll now review the properties of the two rasters.

  3. In the Catalog pane, right-click EastDEM40.tif and click Properties.

    The Raster Dataset Properties window appears.

  4. In the Raster Dataset Properties window, under the Raster Information section and note the Cell Size X and Cell Size Y values of 0.4.

    EastDEM40.tif cell size properties

  5. Click OK to close the Raster Dataset Properties window.
  6. Repeat the process for WestDEM50.tif and note the Cell Size X and Cell Size Y values of 0.5.

    WestDEM50.tif cell size properties

    EastDEM40.tif has a pixel size of 0.4 meters (or 40 centimeters) and WestDEM50.tif has a pixel size of 0.5 meters (or 50 centimeters).

    For these DEMs to be part of the same analysis, they need to have the same resolution. The best practice is to resample the smaller pixel size (here, 0.4 meters) to the larger pixel size (here, 0.5 meters). In the next section, you'll use the Resample tool to resample EastDEM40.tif to 0.5 meters.

    But first, you'll finish the inspection of the DEM properties by checking the spatial reference.

  7. In the Catalog pane, open the EastDEM40.tif Raster Dataset Properties window again and review its Spatial Reference properties. Do the same for WestDEM50.tif.

    DEM Projected Coordinate System property

    Both images use the same coordinate system, GK_M31; however, this does not match the coordinate system used for Hallstatt_Image.tif, which is MGI_Austria_GK_Central and the ideal coordinate system for the project. So, you'll need to reproject the DEM data to MGI_Austria_GK_Central.

    After inspecting the two DEM files, you determine that you'll need to do three things:

    • Resample EastDEM40.tif to 0.5 meters, so that both DEMs are at the same resolution.
    • Mosaic (assemble) the two DEMs together, so you only have a single larger DEM raster to work with.
    • Reproject the DEMs so that their spatial reference (coordinate system) matches the one from Hallstatt_Image.tif. You can do that in the step when you mosaic the two DEMs.
  8. Close the Raster Dataset Properties window.

Resample and mosaic the DEMs

Now that you determined the issues with your DEM raster files, you'll resample, mosaic, and reproject them as needed. First, you'll resample EastDEM40.tif to 0.5 meters.

  1. On the ribbon, on the Analysis tab, in the Geoprocessing group, click Tools to display the Geoprocessing pane.

    Tools button

    The Geoprocessing pane appears.

  2. In the Geoprocessing pane, on the search bar, type Resample.
  3. In the search results, click Resample (Data Management Tools).

    Search for the Resample tool and open it.

  4. In the Resample tool pane, enter the following parameters:
    • For Input Raster, choose EastDEM40.tif in the drop-down list.
    • For Output Raster Dataset, click the Browse button. Browse to and open the DEM folder, and for Name, type EastDEM50.tif. Click Save.
    • For Output Cell Size, choose WestDEM50.tif in the drop-down list. The X and Y fields update to 0.5.
    • For Resampling Technique, choose Bilinear.

    For elevation data, the Bilinear resampling technique is preferred.

    Resample parameters

  5. Click the Environments tab.
  6. Under Raster Analysis, for Snap Raster, choose WestDEM50.tif

    Resample Environments pane

    Snap Raster ensures that the new output raster and WestDEM50.tif will align perfectly.

  7. Click Run.

    The new layer EastDEM50.tif is added to the Contents pane. It is similar to EastDEM40.tif, but the cell size has been resampled from 0.4 to 0.5 meters. Next, you'll combine the rasters to create a mosaic using the Mosaic to New Raster tool. In that step, you'll also reproject the mosaic to the desired spatial reference.

  8. In the Geoprocessing pane, click the Back button twice.

    Geoprocessing Back button

  9. In the Geoprocessing pane, search for and open Mosaic To New Raster.
  10. In the Mosaic To New Raster tool pane, enter the following parameters:
    • For Input Rasters, choose EastDEM50.tif and WestDEM50.tif.
    • For Output Location, browse to and choose the DEM folder. Click OK.
    • For Raster Dataset Name with Extension, type Hallstatt_DEM.tif.
    • For Spatial Reference for Raster, choose Hallstatt_Image.tif (MGI_Austria_GK_Central).
    • For Pixel Type, choose 32 bit float, because your elevation has decimal precision.
    • For Number of Bands, type 1, since there is only one band in the elevation datasets.

    Mosaic To New Raster parameters

  11. Click Run.
    Note:

    The Mosaic To New Raster tool merges two or more rasters into a single larger raster. This is a fine approach when you only need to mosaic a few adjacent rasters together. However, for larger amounts of data, in which many rasters are involved, a more scalable mosaic dataset is the recommended data management structure.

    The new Hallstatt_DEM.tif layer appears. It is a single seamless elevation raster and has been reprojected to the correct spatial reference.

    Single DEM

    You need to make a small improvement to the raster, so you'll remove it from the map for now.

  12. In the Contents pane, right-click Hallstatt_DEM.tif and choose Remove.

    Remove menu option

  13. In the Catalog pane, locate Hallstatt_DEM.tif in the DEM folder.
    Note:

    You may need to refresh the DEM folder before the new file appears (right-click DEM and choose Refresh).

  14. Right-click Hallstatt_DEM.tif and choose Properties. In the Raster Dataset Properties window that appears and verify the following properties:
    • Under Raster Information, the Cell Size X and Cell Size Y values are 0.5 (meters).
    • Under Spatial Reference, the Projected Coordinate System value is MGI_Austria_GK_Central.
  15. Under Raster Information, for Source Type, choose Elevation. Click OK to accept the changes.

    Set data source type.

    Choosing the appropriate source type ensures that the raster will be rendered properly by default when displayed. When Source Type is set to Elevation, the default stretch type is Minimum Maximum and the default resampling type is Bilinear, which are the best defaults for elevation data.

  16. In the Catalog pane, right-click Hallstatt_DEM.tif and choose Add To Current Map.

    Add To Current Map menu option

    Your elevation raster is now ready and can be used for analysis.

  17. Right-click EastDEM50.tif and choose Remove. Similarly, remove WestDEM50.tif and EastDEM40.tif, as you don't need them any longer.
  18. Press Ctrl+S to save your project.

In this section, you resampled a DEM to a common pixel resolution, mosaicked two DEMs together, and reprojected them to match the other layers in the project. Next, you'll improve the appearance of the DEM.

Improve the appearance of the DEM

In this section, you'll view the default appearance of the DEM and change it to better show the elevation.

  1. In the Contents pane, ensure Hallstatt_DEM.tif is turned on and selected. Turn off Hallstatt_Image.tif.

    Ensure Hallstatt_DEM.tif is turned on and selected.

  2. On the ribbon, on the Appearance tab, in the Rendering group, click the Stretch Type drop-down list. Verify it is set to Minimum Maximum.

    Verify DEM stretch type.

  3. Click the Resampling Type drop-down list and verify it is set to Bilinear.

    Because you declared the raster type as Elevation, these defaults are set up optimally for that raster type. You'll now look at a smaller area of the DEM.

  4. On the ribbon, on the Map tab, in the Navigate group, click Bookmarks, and choose Dark Shoreline.

    Dark Shoreline bookmark

    Your display is mainly dark gray, which is not very informative.

  5. On the ribbon, on the Appearance tab, in the Rendering group, click DRA.

    DRA button

    DRA stands for dynamic range adjustment. It adapts the stretch display by only taking into account the pixel values within the display extent. When you turn on DRA, you can see more shades of gray each time you zoom in on any areas of your raster.

    More shades of gray appear with DRA turned on.

    This is an improvement; however, it would be even better to display the elevation with a more appropriate set of colors.

  6. On the Contents tab, right-click the Hallstatt_DEM.tif layer, and choose Zoom To Layer.

    Zoom To Layer menu option

  7. Under Hallstatt_DEM.tif, click the layer's symbol to open the Symbology pane.

    Hallstatt_DEM.tif symbol

    You'll choose a more appropriate color scheme.

  8. In the Symbology pane, for Color scheme, click the drop-down list and check Show names. Choose Elevation #5.

    Elevation color ramp

    Now you have some green colors for low elevations, and yellow and brown colors for the higher elevations.

    Symbology for the Hallstatt_DEM.tif layer updates to Elevation #5 color ramp.

    This symbology gives a good account of the area's elevation. However, since the lake and the nearby coastal land are almost at the same level of elevation, a good supplement to this data can be to display the water bodies as a vector layer on top of the DEM.

  9. In the Catalog pane, expand Databases and HallstattImagery.gdb. Right-click Hallstatt_Lake and choose Add To Current Map.

    Hallstatt_Lake in the Catalog pane

    The Hallstatt_Lake layer is added to your map and Contents pane.

  10. In the Contents pane, for the Hallstatt_Lake layer, right-click the symbol and choose the color Sodalite Blue.
    Tip:

    To see the name of a color, point to the color.

    Change the lake color.

    The Hallstatt_Lake polygon appears in light blue, clearly distinguishing water from land.

    DEM and lake polygon

    You'll save the symbolized DEM layer to a layer file.

  11. In the Contents pane, right-click Hallstatt_DEM.tif, point to Sharing, and click Save as Layer File.
  12. In the Save Layer File window, Name the layer DEM_layer.nlryx, and save it to the DEM folder.

    Save Layer(s) As LYRX File window

    You now have the symbolized DEM layer saved so that it can easily be shared. You can also use it to apply the symbology to another layer.

  13. Save your project.

In this section, you changed the appearance of your DEM layer to better show elevation heights. Then you saved it to a layer file that you'll use in the next section to apply the same symbology to another raster.

Inspect and change the appearance of a DSM

A DSM shows you the elevation of all surfaces, including tree canopy and buildings. You'll inspect the DSM raster for the Hallstatt area and apply to it the same symbology as the DEM layer.

  1. In the Catalog pane, expand the DSM folder.
  2. Right-click Hallstatt_DSM.tif and choose Properties. In the Raster Dataset Properties window that appears, under Raster Information, locate Number of Bands.

    The Hallstatt_DSM.tif raster has a single band, as is expected for elevation rasters.

  3. For Cell Size X and Cell Size Y, note that the pixel size is 0.5 meters, which is the same as for the Hallstatt_DEM.tif raster.

    DSM cell size properties

  4. Verify Source Type is set to Elevation.

    Source Type is set to Elevation.

    This ensures that the default stretch type is Minimum Maximum, and the default resampling type is Bilinear.

  5. Review the Spatial Reference settings.

    Projected Coordinate System is set to MGI_Austria_GK_Central.

    The Projected Coordinate System is set to MGI_Austria_GK_Central, which is the preferred coordinate system chosen for the project.

  6. Click OK to close the Raster Dataset Properties window.

    The Hallstatt_DSM.tif raster seems to be well set up and does not need any transformations. You'll now enhance its appearance.

  7. In the Catalog pane, right-click Hallstatt_DSM.tif and choose Add To Current Map.

    The DSM layer is added to the map, with the lake layer still showing on top.

    DSM and lake layers

    You'll use the layer file saved for the DEM and apply its symbology to the DSM.

  8. In the Contents pane, right-click Hallstatt_DSM.tif, and choose Symbology.

    The Symbology pane appears.

  9. In the Symbology pane, click the Menu button and select Import from layer file.

    Import from layer file option

  10. In the Import symbology window, browse to the DEM folder, choose DEM_layer.lyrx, and click OK.

    Select the layer file.

    The symbology you defined for the DEM is now applied to the DSM.

  11. On the ribbon, on the Map tab, click Bookmarks and choose Hallstatt.
  12. On the Contents pane, make sure that Hallstatt_DEM.tif and Hallstatt_DSM.tif are both turned on, and that Hallstatt_DSM.tif is selected.
  13. On the ribbon, on the Appearance tab, in the Compare group, click the Swipe tool. Use the Swipe tool to compare the DSM and the DEM.

    Swipe to compare the DSM and the DEM.

    You'll notice that the DSM is similar to the DEM overall, but its elevations are slightly higher than the ones from the DEM. Also, its surface does not appear as smooth. You'll zoom in to see more details.

  14. To exit the swipe mode, on the ribbon, on the Map tab, in the Navigate group, click the Explore tool.
  15. With the mouse wheel button, zoom in to the Hallstatt village.

    Due to the DRA setting, the stretch of the DSM is recomputed to show you more details. You can clearly see the height of the buildings. You can even recognize an occasional tree.

    The DSM shows the village buildings.

    For reference, the image below shows how the village looks from the ground.

    Hallstatt shoreline
    Photo credit: KyOnChen on Flickr.

  16. Zoom out, pan toward the mountains, and zoom back in.

    You can clearly see some forests on steep slopes.

    The DSM shows a forested area.

  17. In the Contents pane, right-click Hallstatt_DSM.tif and choose Zoom To Layer.
  18. Save your project.

In this section, you learned about a DSM. You imported the symbology from a layer file so that you could duplicate the symbology from an existing layer. Both the DEM and the DSM are useful elevation data. Your choice of one or the other depends on your specific analysis needs.

Derive slope

You can use elevation layers to create other layers that can be helpful in an analysis workflow. You'll derive a slope layer out of the DEM using the Slope raster function.

Note:

Raster functions are a quick way to generate on-the-fly data. They are similar to geoprocessing tools, in that they both can analyze and process data.

Geoprocessing tools create persisted dataset outputs that have had each pixel processed. In contrast, raster functions perform analysis on the fly on the pixels within the display extent, and do not generate a new dataset on your machine. You are only working with small datasets in this lesson, but when you have much larger data, or if you want to create a prototype to show what your output should look like, raster functions can be effective.

  1. In the Contents pane, turn off Hallstatt_Lake. Ensure that Hallstatt_DEM.tif is on and selected.
  2. On the Imagery tab, in the Analysis group, click the Raster Functions button.

    Raster Functions button

    The Raster Functions pane appears.

  3. In the Raster Functions pane, expand the Surface group.

    Surface raster functions

    The Surface group contains many functions that work with elevation data.

  4. In the Surface group, click Slope.
    Note:

    The Slope function calculates the rate of change in the elevation (Z).

  5. In the Slope Properties pane, for DEM, choose Hallstatt_DEM.tif. For Scaling, verify the value is Degree.

    Slope raster function Degree

  6. Click Create new layer.

    The new Slope_Hallstatt_DEM.tif layer representing slope in degrees is added to the map.

    Slope in degrees

    The lighter areas correspond to the steepest slopes. The darker areas correspond to the flatter sites. As you can see in the Contents pane, the cell values vary from 0 to 90 degrees. You'll now add a second slope layer, this time in percent rise.

  7. In the Raster Functions pane, in the Surface group, click Slope. In the Slope Properties pane, for DEM, choose Hallstatt_DEM.tif. For Scaling, choose PercentRise.

    Slope raster function PercentRise

  8. Click Create new layer.

    The new Slope_Hallstatt_DEM.tif_1 layer representing slope in PercentRise is added to the map. Slope PercentRise

    In Contents pane, the legend for the Slope_Hallstatt_DEM_1.tif raster is visible, showing that the cell values vary from 0 to 2804.54 percent.

    The legend for Slope_Hallstatt_DEM_1.tif on the Contents pane

  9. Use the Swipe tool to compare and contrast the differences between the slope generated in degrees versus the slope generated in percent rise.

    Compare Degree to PercentRise.

    Raster functions allow you to create quick, on-the-fly results. This allows you to create a prototype of how you want the result to look. When you are satisfied with the result, you can export the raster to persist the dataset on disk. You'll save the slope generated in degrees.

  10. In the Contents pane, right-click Slope_Hallstatt_DEM.tif, point to Data, and click Export.

    The Export Raster pane appears.

  11. In the Export Raster pane, for Output Raster Dataset, browse and select the DEM folder, and for Name, type DEM_Slope.tif. Click Save. For Pixel Type, select 8 Bit Unsigned.

    Export slope raster.

  12. Click Export.

    The new DEM_Slope.tif layer appears. Unlike the preview raster function slope layers, it is a permanent layer that exists on disk.

    Note:

    Optionally, experiment with other surface functions, such as Hillshade, Shaded Relief, or Curvature, to examine how your DEM can be used to create other useful layers. Also consider running Slope or other tools on the DSM and comparing the results to the results of the DEM.

  13. In the Contents pane, remove Slope_Hallstatt_DEM.tif_1 and Slop_Hallstatt_DEM_Slope.tif.
  14. Save your project.

In this module, you worked with elevation data—both DEM and DSM. You learned how to resample and mosaic raster data. You changed the symbology of your DEM data and matched that symbology to your DSM layer. You also learned how to create quick, on-the-fly processing layers using raster functions and save them to disk when you have the output you want.


Clip and package raster data

There are many other types of rasters that you may want to add to your project. In this section, you'll work with one more type: a historical paper map that was scanned and is now a digital image in JP2 format. When all your raster layers areas are ready, you'll clip your data to the area of interest (AOI). Then you'll create a project package to deliver all the data that you have prepared, so that others can use it to perform further exploration and analysis.

Inspect and preprocess a scanned map

Scanned maps are often scanned drawings or photos. Since they are digital forms of a picture or drawing, they tend to be less useful for analysis but still can be used for visual analysis and as a background layer. In this case, you have a historical hand-drawn map of the Hallstatt area from the years 1824 to 1830. It offers a historical perspective on Hallstatt's development.

  1. In the Catalog pane, expand the ScannedMap folder.
  2. Right-click Hallstatt_HistoricDrawing.JP2 and choose Add to Current Map.
    Note:

    If the Calculate statistics window appears, click Yes.

    The Hallstatt_HistoricDrawing.JP2 adds to your map.

    Historical map

    This is a standard RGB color image, and it is represented as a three-band raster (red, green, and blue bands).

    Hallstatt_HistoricDrawing.JP2 legend

    Note:

    Digital images created with standard cameras or scanners are often stored in the RGB color model, which means that they are composed of three rasters for red, green, and blue. Such images can be readily displayed in ArcGIS Pro like any multiband raster dataset.

    You'll inspect this layer's properties.

  3. In the Catalog pane, right-click Hallstatt_HistoricDrawing.JP2 and choose Properties.

    The Raster Dataset Properties window appears.

  4. In the Raster Dataset Properties window, under Raster Information, you can see that the value for Number of Bands is 3, as expected due to the RGB representation.
  5. Under Spatial Reference, you can see that the Projected Coordinate System property is set to MGI_Austria_GK_Central.
    Note:

    This scanned map was provided to you already georeferenced in the coordinate system MGI Austria GK Central. This means that it was located spatially to display at the correct Earth location in a GIS such as ArcGIS Pro. To learn how to work with a scanned map or photo that has not yet been georeferenced, check out the Learn ArcGIS lesson Georeference imagery in ArcGIS Pro.

  6. Click OK to close the Raster Dataset Properties window.
  7. Use the navigation tools to zoom and explore the historical imagery.

    Explore and navigate the historic map.

  8. In the Contents pane, turn on Hallstatt_Image.tif and turn off all other layers, except the basemaps. Select the Hallstatt_Image.tif layer.
  9. On the Appearance tab, click the Band Combination drop-down list and choose Natural Color.

    Update Band Combination to Natural Color.

  10. In the Contents pane, turn on Hallstatt_HistoricDrawing.JP2, and select it.
  11. On the ribbon, on the Appearance tab, in the Compare group, click the Swipe tool, and use it to investigate the town of Hallstatt.

    Investigate historic Hallstatt.

    Due to the accurate georeference, the historical map appears well aligned with the aerial photo. Notice how Hallstatt has not changed much since the creation of the historic map.

  12. When you are finished, change the band combination for Hallstatt_Image.tif back to Color Infrared, and save your project.

Scanned maps generally do not require much processing and are good for background images and visual reference. In this case, the historical imagery of the Hallstatt area offers an opportunity to chart growth and changes that were recorded over time.

Note:

There are many other types of rasters. Thematic rasters are another important type. In a thematic raster, the cell values correspond to categories. A typical example is a land-use raster, in which each cell shows how the corresponding land is used (urban, forested, agriculture, and so on). Land-use rasters could be another useful supplement to analyze the Hallstatt area.

In this section, you worked with a scanned image and observed that, as long as it is properly georeferenced, it can be added to an ArcGIS Pro project like any other raster.

Now that you have preprocessed all of the layers, you'll clip them all to the same area of interest.

Clip rasters

Since you are only working with the town of Hallstatt, you only need to provide the town and the areas just outside it. Unneeded areas take up more storage space and take longer to process. You'll clip all your raster datasets using the Clip Raster tool. Since you want to process all your raster layers at once, you'll use that tool in batch mode.

  1. In the Contents pane, verify the map has the following raster layers:
    • Hallstatt_Image.tif
    • Hallstatt_DEM.tif
    • Hallstatt_DSM.tif
    • DEM_Slope.tif
    • Hallstatt_HistoricDrawing.JP2

    The Contents pane also contains the Hallstatt_Lake feature class and the basemap layers that will not be clipped. You'll add the boundaries of your area of interest.

  2. In the Catalog pane, expand Databases and HallstattImagery.dgb. Right-click the Hallstatt_Boundary layer and choose Add to Current Map.

    Add the Hallstatt_Boundary layer to the map.

    The new feature class layer appears. It contains a single polygon feature, which represents the area of interest (AOI) that you'll use to clip your data.

  3. In the Geoprocessing pane, search for Clip Raster.
    Note:

    The Clip Raster tool is different from the Clip tool, which clips only feature classes (vector layers).

    Since you'll be clipping all raster datasets to the same extent, you'll use the batch geoprocessing mode.

  4. In the search results, right-click Clip Raster, and select Batch.

    Select the Batch mode.

    The Batch Clip Raster tool pane appears.

  5. In the Batch Clip Raster tool pane, verify that the batch parameter is set to Input Raster.

    This means that when the Clip Raster tool is run as a batch, a list of rasters will be fed to it to be clipped one after the other.

    Specify the batch parameter.

  6. Review the additional parameters, but do not make any changes.

    Make temporary batch tool is selected, as you'll only use the batch process once. If you want to create a reusable tool, you can choose the Save the batch tool option.

  7. Click Next.

    The Parameters tab appears.

  8. For Batch Input Raster, click the Add Many button, click Toggle All Checkboxes, and click Add.

    Add Many checklist

    All the raster layers in your project are added. They will all be clipped, one after the other.

  9. For Output Raster Dataset, click the Browse button, and open Folders, HallstattImagery, and ClippedOutputs. For Name, type Clip_%Name%, and click Save.
    Note:

    Each clipped raster output will be added to the ClippedOutputs folder, and its name will be the word Clip_ appended to the beginning of the source raster name, for example, Clip_Hallstatt_Image.tif.

  10. For Output Extent, choose Hallstatt_Boundary.

    The Output Extent parameter allows you to use the boundary of another layer to define the clipping boundary.

    Note:

    When you set Output Extent to a feature class, the Rectangle extent parameters are updated with the bounding box coordinates of the entire source layer. In addition, a new Use Input Features for Clipping Geometry check box is added.

  11. Check Use Input Features for Clipping Geometry.

    This ensures that the tool uses specifically the extent of the polygon representing the Hallstatt boundary as the clipping geometry, instead of using the extent of the entire feature class, which could be much larger.

    Clip Raster parameters

  12. Click Run.

    After the batch tool has executed, all the clipped layers are added to the map.

  13. In the Contents pane, verify each of the layers has a clipped version.

    The clipped layers appear in the Contents pane.

    Note:

    The Clip Raster tool does not clip the Hallstatt_Lake layer, because it is not a raster but a vector layer. You will leave that layer as it is for the purpose of this lesson. However, you could use the Clip tool to clip that layer.

    Next, you'll clean up the Contents pane.

  14. In the Contents pane, remove all the layers except for the following:
    • Hallstatt_Boundary
    • Hallstatt_Lake
    • Clip_Hallstatt_Image.tif
    • Clip_Hallstatt_DEM.tif
    • Clip_Hallstatt_DSM.tif
    • Clip_DEM_Slope.tif
    • Clip_Hallstatt_HistoricDrawing.tif
    • World Topographic Map and World Hillshade basemaps
  15. In the Contents pane, drag the layers to reorder them and match the list above. Turn off Hallstatt_Boundary so that you can see the layers below.
  16. On the map, examine how each layer has been clipped to the Hallstatt_Boundary feature extent by turning each layer on and off.
    Note:

    Some of the extents will be slightly different due to the different pixel sizes of the inputs.

    The rendering and symbolization options that were applied to the input rasters did not carry over to the clipped rasters. You'll quickly reapply the layer files you saved earlier in the lesson to the clipped rasters.

  17. In the Contents pane, right-click Clip_Hallstatt_Image.tif, and choose Symbology.
  18. In the Symbology pane, click the Menu button, and select Import from Layer File.
  19. In the Import Symbology window, browse to the Imagery folder, select Hallstatt_ColorInfrared.lyrx, and click OK.

    The preferred imagery rendering options are now applied to the clipped imagery.

  20. Similarly, apply the DEM_Layer.lyrx (stored in the DEM folder) to the clipped DEM and DSM layers.
  21. Save the project.

In this section, you learned how to use the Clip Raster tool and run it in batch mode. Next, you'll package the data so it can be delivered neatly.

Create a project package

You'll now create a project package, so it is easier to share the project and the data as a whole.

  1. In the Contents pane, ensure that all the clipped layers are turned on.
  2. On the ribbon, click the Share tab.

    The Share tab is used to create various packages and files.

  3. In the Package group, click the Project button.

    Create a project package.

    The Package Project pane appears.

  4. In the Package Project pane, for Start Packaging, choose Save package to file.

    This option allows you to save the project package as a file stored on your local computer. You can then choose to deliver the package to stakeholders in the way that is most convenient to you.

  5. Under Item Details, for Name, click Browse, and choose a suitable location to store the package, such as the HallstattImagery folder. For Name, type Prepared_HallstattImagery.ppkx. Click Save.

    Choose the package location and name.

  6. For Summary, type or paste the following text:

    The project package contains the raster layers prepared to analyze overtourism in the town of Hallstatt. The package includes an aerial image of the town; DEM, DSM, and slope layers; and a historical map.

  7. For Tags, add the following tags: Hallstatt, image, raster, DEM, DSM, slope, and historical map.
    Note:

    You can copy and paste all the tags separated by commas at one time.

  8. Uncheck Include Toolboxes and Include History Items.

    Now that all the information is entered, the next step is for the tool to analyze the content to verify that it is all set to create the package successfully.

  9. Click Analyze.

    Analyze button

    If there are any errors, you can right-click them to see how to fix them. Once errors have been fixed, analyze the package again. The next step is to create the package.

  10. Click Package.
    Note:

    You may get a notification that the project has been changed and needs to be saved. Click Yes to save the project.

    When the package has been successfully created, a green notification appears at the bottom of the Package Project pane.

    Package creation success notification

  11. Click the Manage the package link to open the folder containing the project package in the .ppkx format. You have successfully created a project package that is ready to be delivered to other analysts or clients.
    Note:

    If the clients download the package to their desktop and have ArcGIS Pro installed, they can double-click the file, and the whole project opens in ArcGIS Pro.

  12. Save the project.

In this module, you prepared one more raster type and then clipped all your raster layers to the area of interest, and you created a project package to share all the prepared data.


Solve common spatial reference and projection issues

When preparing raster data for analysis, you will often encounter spatial reference issues. To function in a GIS, every layer needs to be defined within a coordinate system. To supplement the workflow you followed so far, you'll discover three spatial reference-related issues and learn how to fix them.

Fix an image with a missing spatial reference

For this first case, you'll work with a scanned historical map similar to the one used earlier in the lesson. However, in that new version, its spatial reference is unknown. Rasters usually have several auxiliary files, and one of them contains the spatial reference information. If that file gets lost or erased, the information is gone.

First, you'll inspect the image properties.

  1. In the Catalog pane, expand Folders, and expand the HallstattImagery, SpatialReferenceData, and ScannedMap folders.

    Catalog pane folders expanded to the ScannedMap folder

  2. Right-click Hallstatt_HistoricDrawing.JP2 and choose Properties.
  3. In the Raster Dataset Properties window, expand Spatial Reference and review the Name property.

    Spatial Reference section in the Raster Dataset Properties window for Hallstatt_HistoricDrawing.JP2

    The spatial reference is Unknown. This means that you need to specify one.

  4. Expand the Extent section.

    Extent properties in the Raster Dataset Properties window for Hallstatt_HistoricDrawing.JP2

    Notice that the extent values are not zero or near zero. This means that the raster has an extent and is thus properly georeferenced: it has all the information needed to locate it properly on a map, if the coordinate system used were known. So, you only need to fix the lack of a coordinate system definition.

  5. Click OK to close the Raster Dataset Properties window.

    Next, you'll display the image on a map. You'll create a map to avoid any interferences with the layers present on the previous map.

  6. On the ribbon, on the Insert tab, in the Project group, click New Map.

    New Map button

    A new map appears.

    A new map appears.

  7. In the Catalog pane, right-click Hallstatt_HistoricDrawing.JP2 and choose Add To Current Map.

    The Calculate statistics window appears that states the raster data source does not have statistics.

  8. In the Calculate statistics window, click Yes.

    A warning appears, mentioning that the layer has an unknown coordinate system. The layer does not seem to appear on the map.

    Unknown Coordinate System warning

  9. In the Contents pane, right-click Hallstatt_HistoricDrawing.JP2 and choose Zoom To Layer. Zoom out progressively to see where the imagery is actually located.

    It is off the coast of Africa.

    Added image with an unknown coordinate system adds to the map off the west coast of Africa

    You'll now define the projection. By reading some external documentation about the scanned map, you determined that it is using the MGI_Austria_GK_Central coordinate system.

  10. In the Geoprocessing pane, search for and open the Define Projection tool.

    Define Projection tool

  11. In the Define Projection tool pane, for Input Dataset or Feature Class, choose Hallstatt_HistoricDrawing.JP2. For Coordinate System, choose Select coordinate system.

    Define Projection parameters

  12. In the Coordinate System window, in the search box, type MGI Austria GK Central and press Enter. Under XY Coordinate Systems Available, expand Projected Coordinate System, National Grids, and Austria, and select MGI Austria GK Central. Click OK.

    Search for and select MGI Austria GK Central.

  13. In the Define projection tool pane, under Coordinate System, verify MGI Austria GK Central has been added, and click Run.
    Note:

    The Define Projection tool is used to assign a known spatial reference to a layer that already has an extent. If the extent is not available or is incorrect, you need to georeference the raster dataset.

    See the lesson Georeference imagery in ArcGIS Pro to learn more about georeferencing historic imagery.

  14. In the Contents pane, right-click Hallstatt_HistoricDrawing.JP2 and choose Zoom To Layer.

    On the map, the Hallstatt_HistoricDrawing.JP2 layer now appears properly located in the Hallstatt area.

    The Hallstatt_HistoricDrawing.JP2 layer correctly georeferenced and appears in the correct location in Austria.

  15. In the Catalog pane, right-click Hallstatt_HistoricDrawing.JP2 and choose Properties.
  16. In the Raster Dataset Properties window, expand Spatial Reference and review the Projected Coordinate System property.

    Verify projection definition updates.

    The spatial referencing has been updated to reflect the projected coordinate system as MGI_Austria_GK_Central.

  17. Click OK to close the Raster Dataset Properties window.
  18. Save the project.

In this section, you discovered that a raster dataset was missing spatial reference information, and you used the Define Projection tool to fix it.

Reproject a DSM

In this second case you'll work with, a DSM file has valid spatial reference information. However, you will find that the coordinate system it uses does not match the one chosen for the project.

  1. In the Contents pane, turn off Hallstatt_HistoricDrawing.JP2.
  2. In the Catalog pane, expand Folders, HallstattImagery, SpatialReferenceData, and DSM.
  3. Right-click DSM.tif and choose Properties.

    Properties for DSM.tif in the DSM folder under SpatialReferenceData on the Catalog pane

  4. In the Raster Dataset Properties window, review the Spatial Reference settings.

    Review DSM spatial reference.

    The coordinate system is set as GK_M31. This spatial reference is valid, but it does not match the one used for other rasters in the project, MGI_Austria_GK_Central. You'll need to reproject the raster.

    Note:

    There are different ways to reproject a raster layer. Earlier in the lesson, you saw how to reproject rasters while assembling them with the Mosaic to New Raster tool. This time you perform the reprojection as a stand-alone step, using the Project Raster tool.

  5. Click OK to close the dataset properties.
  6. In the Geoprocessing pane, click the Back button. Search for and open Project Raster.

    This tool is used to reproject a raster dataset from one coordinate system to another. You'll match the spatial reference to the one for Hallstatt_HistoricDrawing.jp2, which you just set to MGI_Austria_GK_Central in the previous section.

  7. In the Project Raster pane, select the following settings:
    • For Input Raster, browse to HallstattImagery, SpatialReferenceData, and DSM, and select DSM.tif.
    • For Output Raster Dataset, browse to HallstattImagery, SpatialReferenceData, and DSM. For Name, type Hallstatt_DSM.tif and click Save.
    • For Output Coordinate System, choose Hallstatt_HistoricDrawing.jp2 (MGI_Austria_GK_Central).
    • For Resampling Technique, choose Bilinear interpolation.
    • For Output Cell Size X and Y, keep the values 0.5.

    Project Raster tool parameters

  8. Click Run.

    The reprojected DSM layer is added to the map.

  9. In the Contents pane, right-click Hallstatt_DSM.tif and choose Properties.
  10. In the Layer Properties window, click the Source tab. Expand Spatial Reference and verify that Projected Coordinate System is now set to MGI_Austria_GK_Central.
    Note:

    Reprojecting a raster is a slightly lossy process, since the pixels have to be resampled to fit in the new projection. You should avoid performing too many reprojections one after the other on a raster to avoid moving too far away from the original data. However, reprojecting once to match a project's preferred coordinate system is justified.

  11. Click OK to close the Properties window.
  12. Save the project.

In this section, you discovered that a raster had a valid spatial reference, but that it was different from the one chosen for the project, and you reprojected it to the preferred coordinate system.

Update the geographic transformation to align layers

In this third case, you'll resolve a problem of misalignment between your imagery and the basemap.

First, you'll create a map, and add an image to it.

  1. On the ribbon, on the Insert tab, in the Project group, click New Map.

    A new map, Map1, appears.

    A new map, Map1, appears. You'll add to the new map the same Hallstatt_Image.tif imagery you used earlier in the lesson.

  2. In the Catalog pane, expand Folders, HallstattImagery, and the Imagery folder. Right-click Hallstatt_Image.tif and choose Add To Current Map.
  3. In the Contents pane, ensure Hallstatt_Image.tif is selected.
  4. On the ribbon, on the Appearance tab, in the Effects group, update Transparency to 60%.

    Update layer transparency to 60%.

    Notice that Hallstatt_Image.tif is not lining up correctly with the basemap layer.

    Layers not lined up correctly

    You'll inspect the image properties to see if you can identify the issue.

  5. In the Contents pane, right-click Hallstatt_Image.tif, and click Properties.
  6. In the Layer Properties window, if necessary, click Source.
  7. In the Source properties, expand Spatial Reference.

    Notice that the spatial reference is set to MGI Austria GK Central.

    Identify layer projection.

    MGI Austria GK Central is the correct projected coordinate system for this region, so the reason Hallstatt_Image.tif is not lining up with the basemap layer must be something else. You'll explore the properties of the map to determine why.

  8. In the Layer Properties window, click OK to close.
  9. In the Contents pane, right-click Map1, and click Properties.

    Map1 in the Contents pane

  10. In the Map1 Properties window, click the Coordinate Systems tab.

    Map1 coordinate system information

    Notice that the map also has the MGI Austria GK Central coordinate system set. This means that the map is currently using the same spatial reference as Hallstatt_Image.tif.

    Note:

    When creating a map, the default coordinate system is WGS 1984 Web Mercator (auxiliary sphere). However, when you add a first layer to a map, the map's coordinate system is immediately updated to match the one from the layer. This explains why both Hallstatt_Image.tif and Map1 have MGI Austria GK Central listed as their coordinate system.

    Since everything looks normal, and you have not yet found the problem, you'll inspect the transformation information.

  11. Click the Transformation tab.

    Map1 coordinate system transformation information

    To convert on the fly between the map's coordinate system, WGS 1984 Web Mercator (auxiliary sphere), and the one from Hallstatt_Image.tif, MGI Austria GK Central, an additional transformation called a geographic datum transformation is needed. By default, the transformation is set to a default value, MGI To WGS 1984. The problem is that it is not correct for this region. In this case, the correct transformation is MGI To WGS 1984 3.

    Note:

    Very often, ArcGIS Pro chooses the correct geographic transformation, but not always. To find the appropriate transformation, refer to Geographic and Vertical Transformation Tables. If you scroll to page 39, you can see there are several versions of MGI_To_WGS_1984. If you look at the Area of Use, there are two appropriate transformations for Austria: MGI_To_WGS_1984_2 and MGI_To_WGS_1984_3.

  12. From the MGI To WGS 1984 drop-down list, select the MGI To WGS 1984 3 transformation, and click OK.

    Change the transformation to MGI to WGS 1984 3.

    The map updates.

  13. Explore the map and confirm that Hallstatt_Image.tif now aligns correctly with the World Topographic Map basemap layer.

    Review layer alignment

  14. Zoom out on the map and confirm that the entire Hallstatt_Image.tif layer aligns correctly to the basemap.

    Verify regional image alignment

  15. Save the project.
    Note:

    You might wonder why there was no misalignment when you first used Hallstatt_Image.tif in Hallstatt Map. This was because that map had been preset with the right transformation, MGI To WGS 1984 3, in the project you downloaded. Optionally, you can verify that fact in the Hallstatt Map properties.

In this section, you fixed a misalignment between an image and the basemap by changing the geographic transformation of the map. In this module, you learned about three types of spatial reference issues that can occur and you learned how to fix them.

In this Learn lesson, you learned to inspect and preprocess various types of raster data to ready it for analysis. You worked with aerial imagery, used DEM and DSM elevation data, and derived a slope layer from the DEM. You also worked with a scanned historical map. Then, you took all those layers and clipped them to an area of interest to ensure that the data is more focused and easier to process and analyze. You created a project package so that you can deliver the content of the project as a single file to the stakeholders. Finally, you learned to solve three types of spatial reference issues.

You can find more lessons like this on the Introduction to Imagery & Remote Sensing page.