Comparing Rasters of Different Formats and Structures

Liz Sanderson
Liz Sanderson
  • Updated

FME Version

  • FME 2021.2

Introduction

In this article, we will have a look at a few different rasters while pointing out some of the important aspects in each. We will examine the similarities and differences between the raster images. It is possible to categorize rasters using 4 different criteria:

  1. georeferenced status
  2. interpretation (band number/type/bitness)
  3. scanned/photographed/rasterized
  4. contents - imagery/dem/topographic/thematic

For another approach to viewing rasters, check out this article on Viewing and Inspecting Rasters. Please begin by downloading and extracting the RasterPackage.zip from the Files section of this article. 
 

Step-by-step Instructions

The following examples will be using FME Data Inspector to view and inspect the data, but Visual Preview inside of FME Workbench can be used as well. 
 

Example 1: Smartphone Photo and Using FME Data Inspector 

In the FME Data Inspector, open 1_smartphonephoto.jpg using the JPEG (Joint Photographic Experts Group) format. For more information on JPEGs, see the documentation
DI-SmartphoneReader.png

To inspect the jpeg further, click on different individual pixels to discover information about them. A red dot will appear over the pixel that is selected. 
You can also drag a rectangle on the image in the Graphics View window and release it to get information about the whole raster. A grid of light blue dots will appear over the entire image when the whole raster is selected. 


Information about the raster will be displayed in the Feature Information window which you may need to open via View > Windows > Feature Information Window in FME Data Inspector, or by clicking on the Feature Information button in Visual Preview. 
FeatureInfoDI.png
Enabling the Feature Information Window in FME Data Inspector
FeatureInfoVP.png
Enabling the Feature Information Window in Visual Preview in FME Workbench
 
When viewing a simple JPEG raster, take note of the following:

  • Ground coordinates and distances are in pixel units
  • There are three bands RED8 (R), GREEN8 (G), and BLUE8 (B), their proportion on a pixel defines what color we see.
  • Selecting the image as a whole, we can see that the jpeg image has a lot of metadata (format attributes)


 

 

 

1_smartphonephoto.jpg as seen in the FME Data Inspector: In the bottom left we see the pixel information including the Ground Location and individual band values. This is a pixel from the leaf in the middle, note the high Band 0 Red value compared with the other bands. 
On the right, we see some of the metadata from the image which FME has picked up. Wondering what the numbers are in the band names (e.g., RED8)? This number represents the bit depth. A higher bit depth allows for more information or a greater range of values to be stored in a band. For 8 bit bands, we can only store values up to 255. The higher bit depth, however, usually means the file will typically become bigger in size.
 

Example 2: Orthophoto

In FME Data Inspector, open 2_Aerial.tif using TIFF (Tagged Image File Format) or GeoTIFF (Geo-referenced Tagged Image File Format) and inspect it. Either reader can be used regardless of if the TIFF file has a coordinate system attached.
TIFFReader.png

When viewing an orthophoto or other aerial image, take note of the following:

  • You should see that the image has a coordinate system
  • Cell size and the ground units are in meters.
  • Less metadata (feature attributes)
     


2_Aerial.tif: Similar to what we saw in the above example, however, now our image has a defined coordinate system and the image is georeferenced. If you have background maps enabled you should see that it sits nicely over Vancouver's waterfront.
 

Example 3: Scanned Topographic Map

In FME Data Inspector, open 3_scannedTopomap.tif using TIFF (Tagged Image File Format) or GeoTIFF (Geo-referenced Tagged Image File Format) and inspect it.
Scannedtopi.png

When viewing a scanned raster, take note of the following:

  • It has a single band (UNIT8) with just a few possible values
  • When the whole raster is selected, each UNIT8 pixel value corresponds to a defined RGB palette that tells what color each value should be - this works just like painting by number.


A section of 3_scannedTopomap.tif: Here we can see the palette information on the right, note that for each value in the UNIT8 band we can see a corresponding RGB color.
 

Example 4: Digital Elevation Model (DEM)

In FME Data Inspector, open 4_elevations_cded.dem usin the Canadian Digital Elevation Data (CDED) format. 
dem.png

When viewing a DEM, take note of the following:

  • The raster has a single band (INT32) with integer numeric values. In this case, each value represents the elevation at that point.

A section of 4_elevations_cded.dem as seen in the FME Data Inspector: Here we can see the INT32 band which has values corresponding to the elevation. The highest point I could find was 1497 m.
 

Example 5: Satellite Image 

In FME Data Inspector, open the Landsat image LC80480252014249LGN00.tif using TIFF (Tagged Image File Format) or GeoTIFF (Geo-referenced Tagged Image File Format). This one might take a little longer to load as it’s very large.
SatImage.png

When viewing a satellite image, take note of the following:

  • This particular image has four bands RED16, GREEN16, BLUE16, and ALPHA16. Others will have a different number of bands depending on the sensors available on the satellite itself. 
  • It also appears to be rotated. This is due to invisible pixels - it has transparent sections. These transparent sections are controlled by the alpha band. In this image, the ALPHA16 band can have values of anywhere between 0 and 65535. A value of ‘0’ will result in a fully invisible pixel and the maximum value (‘65535’) will result in a fully opaque pix. Values in between this range will result in partial transparency.

Landsat image as seen in the FME Data Inspector: Here we can see that it has four bands and one is called ALPHA16. An invisible pixel has been selected for the screenshot. Notice that the value is '0' for the ALPHA16 band, this corresponds to a fully transparent pixel. If we didn't have the alpha band here the border would look black (0,0,0). The reason this file is so large is that we have four 16 bit bands with a fairly high resolution.

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