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.
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|
Download the session materials from our shared repository.
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.
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?
Now use the digitizing functionality of Google Earth Pro to digitize objects on the HU-Campus Adlershof.
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:
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.
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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