Learning goals

  • Understand the basic principles of visual image interpretation
  • Explore very high spatial resolution images in Google Earth
  • Digitize objects in Google Earth
  • Temporal analysis in Google Earth to observe change


Google Earth

Google Earth is a digital globe which displays the Earth’s surface primarily based on mosaics of very high resolution satellite images (after zooming in far enough). Google Earth thus serves as common entry point to remote sensing and, moreover, opened up the remote sensing technology to the broad public. The desktop application Google Earth Pro offers several features and tools which are useful for visual image interpretation and remote sensing research in general. Among others, these include the availability of various geodata layers (e.g., borders, roads, 3D buildings, etc.) and the possibilities to display historical images, to import both vector and raster geodata, and to digitize objects.

HU-Campus Adlershof from above in 2019 (Source: Google Earth Pro)

Visual image interpretation

The analysis of Earth observation data allows us to draw conclusions about conditions and processes of the Earth’s surface. We often make use of satellite and aerial images taken from spaceborne and, respectively, airborne platforms. Different image properties, such as object features and context, can be used to interpret what is on the ground. With the help of images from different dates, we can observe and analyze changes of the Earth’s surface.

The quantity and quality of both satellite and aerial images have enhanced over time. With regard to very high spatial resolution images that are well suited for detailed visual image interpretation, satellite images with a spatial resolution of less than 1 m are available for most parts of the Earth. In urban agglomerations, aerial images often even exceed 10 cm spatial resolution.

Visual image interpretation implies the human’s ability to analyze the content of images, e.g., land cover and land use from remote sensing imagery. Visual image interpretation encompasses two steps, first the perception of objects according to their external attributes and, second, the actual interpretation of their meaning.

Attribute Description (example) Interpretation (example)
Contrast, color, brightness Transition from light to dark blue Variations in water depth
Geometry (shape, size) Sinuous ribbon-like object River
Texture (structure of a surface) Rough surface with vertical line patterns Maize cultivation
Spatial context (functional interrelationship) Rail tracks that intersect a building Railway station
3D structure Visible facade and long shadow Tower

Example subsets used for interpretation in table above (Source: images from Google EarthTM)

Session materials

Download the session materials from our shared repository.


Visual image interpretation

Let´s start with a practical example of visual image interpretation by exploring very high resolution imagery of Berlin using the desktop application of Google Earth Pro. If you did not yet install Google Earth Pro Desktop, please do so now.

  • Open Google Earth Pro. Get an overview about the different features and information layers in the lower left panel. You may want to disable multimedia (e.g. photos) and other layers.
  • Zoom to an arbitrary location of interest within Berlin (press “R” to change from oblique view to nadir view). Answer the following questions with help of the very high resolution images:
    • Which season of the year was the image captured?
    • Is it possible to find out the exact month and/or day?
    • What was the day of the week?
    • What was the time of day?

Share your insights within the group via screen sharing. Which features of the images allowed you to answer the questions for your locations? Did you notice anything peculiar?

Digitize objects

Now use the digitizing functionality of Google Earth Pro to digitize objects on the HU-Campus Adlershof.

  • Navigate to the HU-Campus Adlershof.
  • Right-click on ‘My places’ and create a new folder called ‘FE1’.
  • Select the created folder with a left-click (highlighted in blue when selected).
  • Take a look the different digitizing tools… .
  • … and use them to digitize:
    • the wind tunnel as a point,
    • a 2 km long section of the S-Bahn track as a line,
    • the Geography Department as polygon (outlined, semitransparent).
  • Save your results as .kmz file by right-clicking on your folder containing the digitized objects (use drag & drop if your digitized objects are not located in your folder).

Observing change

Now let´s look at changes in land cover. Use the date tool to observe older/historical photos of Adlershof and answer the following questions:

  • How dense is the temporal coverage of available images before and after 2010?
  • What major changes can be detected in Adlershof in 2000, 2010 and 2019?
  • Do your digitization results fit older images as well?
  • Describe the differences of image data in 1953, 2000 and 2019. Why do they differ?

Adlershof from above in 2005 and 2019 (Source: Google Earth Pro)


The objective of this assignment is to characterize the land cover and land use change in Berlin-Mitte and in Berlin-Adlershof with the help of Google Earth.

Digitize objects

  • Load the .kmz files of Berlin-Mitte and Berlin-Adlershof into Google Earth.
  • Choose three suitable objects within each site and outline them with the digitizing tools. These can be for instance buildings, parks, parking lots, sports grounds.

Observing change

  • Find three time steps (depending on the available data) that show a change process for your digitized objects.
  • Answer the following questions for your three objects:
    • Which land cover change do you observe and how would you describe and interpret the change process?
    • How is the change represented in the images?


  • Document your answers to the above question using screenshots and bullet points in PowerPoint, Word or another software package. Please use the following layout suggestion:

  • Upload your documentation as a PDF file on Moodle.

  • General submission notes: Submission deadline for the weekly assignment is always the following Monday at 10am. Please use the naming convention indicating session number and family name of all students in the respective team, e.g. ‘s01_surname1_surname2_surname3_surname4.pdf’. Each team member has to upload the assignment individually. Provide single file submissions, in case you have to submit multiple files, create a *.zip archive.

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