Although coastal habitat mapping is expensive, remote sensing is a more cost-effective technique than alternative field-survey methods (where effectiveness is defined as overall map accuracy). Satellite imagery is suitable for coarse detail habitat mapping where overall accuracies of c. 70% can be achieved but is inadequate for fine detail mapping, achieving c. 40% accuracy. Four types of cost are encountered when undertaking remote sensing: (1) set-up costs, (2) field survey costs, (3) image acquisition costs and (4) the time spent on analysis of field data and processing imagery. The largest of these are set-up costs such as the acquisition of hardware and software which may comprise 48–78% of the total cost of the project depending on specific objectives. For coarse-detail habitat mapping with satellite imagery, the second highest cost is field survey which can account for c. 20% of total costs and >80% of total costs if a remote sensing facility already exists. Field survey is a vital component of any habitat mapping programme and may constitute c. 70% of project duration. For mapping small coastal areas (<60 km in any direction) in coarse detail, SPOT XS is the most cost-effective satellite sensor, but for larger areas Landsat TM is the most cost-effective and accurate sensor. Detailed habitat mapping should be undertaken using digital airborne scanners or interpretation of colour aerial photography (API). The cost of commissioning the acquisition of such imagery can be high [£15 000–£27 000 (US$24 000–$43 000) even for small areas of 150 km] and may constitute 27–40% of total costs (64–75% if set-up costs are excluded). Acquisition of digital airborne imagery is more expensive than the acquisition of colour aerial photography but is offset against the huge investment in time required to create maps from API. If habitat maps are needed urgently, API may be prohibitively time-consuming. For small areas of say 150 km, a map could be created within 25 days using CASI but might take six times longer to create using API. We estimate that API is only cheaper if the staff costs for API are considerably less than 80 days. As the scope of the survey increases in size, the cost of API is likely to rise much faster than that arising from digital airborne scanners. If the costs of API and digital airborne scanners are similar, the latter instruments should be favoured because they are likely to yield more accurate results than API.
