GIS Files 6: Expert GIS concepts

6.4: Derived mapping (4)

Data from imagery

Imagery – usually from aerial or satellite sensors – is widely used on GIS platforms as a backdrop to vector mapping. An image may contain an abundance of visual information that is not conveyed by the points, lines and polygons of a vector map. As far as GIS software is concerned, however, an image is a dumb background. A key research challenge is to derive vector objects from imagery. An image is a raster dataset: it is a grid of squares or pixels. Each pixel has a numerical value that may relate to colour, height or indeed virtually anything measurable.

Human interpretation is often used to derive data from imagery. An operator traces lines over the on-screen image in a technique known as heads-up digitising. This process remains very labour intensive, however, and significant efforts are being made to find ways to automate it.

One approach is to look for abrupt changes or discontinuities in the image that will equate to a line feature in a map. This can be achieved using an edge detection algorithm that applies a mathematical function to each pixel and its immediate neighbours in turn. The result is an image of lines that can simply be converted into vectors. These lines are often very messy, however, and this method is best used where the discontinuity itself is distinct and separate. An alternative approach is to use software to look for similar clusters of pixels and thereby classify the image into distinct areas. Where successful, this will identify real objects such as buildings, fields and bodies of water within a classified image, which may then be converted into a vector map. Accurately and appropriately deriving vector data in this way is a complex activity at the forefront of research. The ability to automatically generate a map from an aerial photograph or satellite image is a holy grail of GIS because it would help make data far more inexpensive and up to date.

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