Energy Sources
Remote sensing requires a source of energy, normally electromagnetic energy. The most convenient, abundant and inexpensive source of energy is the Sun.

The energy available from the sun is described by the electromagnetic spectrum. Unfortunateky, not all of this energy is available for use by remote sensing technologies. The atmosphere absorbs large portions of the spectrum leaving only specific 'bands' of energy, which are able to penetrate to the Earth's surface. Equally, the amount of energy available from the sun is not evenly distributed by wavelength. In fact, the amount of energy emitted by the sun reaches a peak in the wavelength range 0.4 to 0.7 µm, better known as the visible waveband i.e. the region in the electromagnetic spectrum at which human eyes function. Coincidence, eh?

What does this mean for remote sensing? Knowing the amount of solar energy available tells us if there is enough energy available for a passive sensor to function or if an active sensor (one which provides its own energy source) is required. For example, sensors operating in the visible, near-infrared and thermal infrared regions of the electromagnetic spectrum use the solar energy that illuminates the Earth's surface. Active sensors create their own energy and are, therefore, independent of the Sun. Satellite sensors such as Radarsat and ERS SAR operate in the microwave portion of the spectrum whereas recent developments in airborne LIDAR use shorter wavelengths.

Detecting Targets
Energy reaching the Earth's surface may be reflected at the interface, transmitted through the surface material or absorbed and stored within the material, depending on the specific wavelengths involved and the physical properties of the material receiving the radiation. In reality, the response of the surface, or target, is usually a complex combination of these forms of interaction: reflection, transmission, and absorption.

Surfaces can often be characterized in terms of their spectral response at different wavelengths. For example, our eyes observe healthy vegetation as green, due to the very high absorption of blue and red energy by chlorophyll in plant leaves compared to energy at green wavelengths (which is reflected). In the near- infrared part of the spectrum, an area commonly used in remote sensing to assess the health or vigour of vegetation, healthy vegetation is highly reflective. Unfortunately, our eyes are not sensitive enough to electromagnetic radiation at these wavelengths so instruments - sensors - have been built and their measurements recorded as images.

Specific objects or surfaces, commonly referred to as targets in remote sensing jargon, can be identified on the basis of their spectral response (among other things). A complex set of factors including size, shape, and contrast affect the detectability of targets. Most important are spectral characteristics unique to the target in comparison to their surroundings.

Choices, Choices
Remotely-sensed data can make a substantial contribution to Earth observation activities because of several inherent advantages, namely:

  • spatially consistent data over large areas,
  • uniform accuracy and precision,
  • multitemporal coverage, and
  • complete coverage regardless of site location.

The information generated by processing image data takes several forms:

  • as a series of measurements providing a spatially continuous record of Earth surface elevation, temperature and albedo
  • as an accurate base for visual or digital interpretation of Earth surface phenomena,
  • as a raster image which can be overlayed with vector data supplied by non-remote sensing sources, and
  • as an archive to detect and characterise changes on the Earth's surface.

With all of this data, how do you decide if Earth observation data can really help you? With the many data format options (print, film, digital, geometrically corrected, orthorectified etc.), how do you then decide which type of data is best suited to your needs? The answer lies in careful examination of your application and by answering some basic questions, which will help determine spatial, spectral, temporal and format requirements:

  • What is the problem you are trying to solve?
  • How is the problem being solved at the moment i.e. are traditional methods sufficient?
  • When do you need an answer?
  • What level of detail is required?
  • What are the budgetary constraints?

As with anything worthwhile, planning makes all the difference (there is an old adage - fail to plan and plan to fail!). In the use of technologies such as remote sensing and/or Geographic Information Systems (GIS), effective project planning is critical due in part to the relative newness of operational uses. These tools vary widely in their sophistication, cost, effectiveness, availability, and familiarity. Planning must be systematic and realistic and must focus on problem solving rather than a technology push. With proper planning, remote sensing can be a powerful tool, as evidenced by the numerous case studies published in the literature.

Condensed and Modified From: Press H (1993), The Layman's Guide to Remote Sensing in Northpoint Magazine, Winter 1993, p.10-1.