Application of remote sensing in geomorphology

Remote sensing is the observation of surfaces or objects while not being in direct contact with them. By this definition, cameras are remote sensors, observing the environment around us but not requiring us to touch the objects photographed; our eyes also fall into this category. The more commonly accepted example of remote sensing is the use of satellites in orbit around the earth to observe the surface for monitoring purposes. Since the development of Google Earth, access to such data has become available to everyone for free. However, remote sensing for environmental monitoring is more involved than simply looking at one's neighbourhood from above: it has the capability to provide wide-scale observations of all geomorphological features on Earth's surface. We are able to monitor the changing shape of Earth's surface, assess the processes occurring, and identify landforms in remote regions that might otherwise be inaccessible.

In its most simple application, we can take a remotely sensed image of Earth's surface and interpret what we see to produce a geomorphological map. This allows us to map regions rapidly that might otherwise take many weeks of manual exploration and cartography. Such mapping processes can even be automated, to a certain extent. One constraint that we have, however, relates to the spatial resolution of particular sensors, such as the smallest area on Earth's surface that a sensor can distinguish. For continental-scale features such as mountain ranges, sensors with a coarser resolution may be sufficient (for example, the NASA sensor, MODIS, which at best has a pixel size of 250 m) (see Figure 1). For smaller scale features, such as mountain glaciers, or even sand dunes (see Figure 2), the use of higher spatial resolution sensors will be necessary. For example, Worldview II is a new satellite launched in 2009 with a sub-metre spatial resolution.

What is also useful with regard to today's remote sensors is the availability of hyperspectral imagery; that is, imagery viewing the surface not just in the visible bands to produce what might look like a photograph, but imagery viewing the surface in different bands of the electromagnetic spectrum. This allows the detection of certain materials which often reflect differences in the geomorphology. For example, we can distinguish different rock and sediment types and can inspect for different minerals within rock; we can assess vegetation cover and we can, to a certain extent, determine the moisture content of the surface.

Aside from actual images of the surface, remote sensing also has the geomorphological application of being able to provide three-dimensional representations of the surface in the production of digital elevation models (see Figure 3). On a number of orbiting satellites (and also on some airplanes), radar systems actively beam electromagnetic radiation to Earth and detect these as they bounce off the surface and return to the corresponding sensor; the longer this process takes, the further the reflecting surface must be from the sensor, thereby indicating the shape of the land below. Not only is this useful for an instantaneous representation of the topography but it is immensely useful for monitoring how this may change over time, perhaps due to subsidence or uplift of the surface, or the movement of a glacier (see Figure 4).

The utility of remote sensing for geomorphological studies is immense. It allows for the rapid assessment of large areas and for the monitoring of changes to these areas – things that would be impossible to do using field studies alone. This is not to say that remote sensing might one day completely replace the requirement for on-the-ground field work but it will continue to provide an additional source of information for geomorphological studies at all spatial scales.

• Rao, D. (2002). Remote sensing application in geomorphology. Tropical Ecology 43, 49-59.
• Smith, M. and Pain, C. (2006). Applications of remote sensing in geomorphology. Progress in Physical Geography, 33, 568-582.