Matching Issue to Utility: An Hierarchical Store of Remotely Sensed Imagery for Coastal Zone Management

Abstract

The ultimate goal of any environmental scientist, sociologist or manager is to understand how the environment works. As knowledge is the key to understanding, data must be collected about the environment and analysed in the context of the specific issues being investigated. This will yield information that can be gathered and stored, and will further contribute to the body of knowledge surrounding the said issue. A simplified way of regarding the environment is as a collection of objects that relate to each other, and interact with each other over space and through time. This being the case, much of the data collected is geo-spatial in nature; that is, it has a geographical variability. Remotely sensed imagery of the Earth is one source of geo-spatial data that can be used to help explain how the environment works, and can therefore be used for environmental management. Over the past twenty years, the number of different sensors used to collect remotely sensed data has grown considerably, and this proliferation has led to a vast store of multi-spectral, multi-spatial and multi-temporal data of different scales which is theoretically available for use in environmental management. Such a large database is a unique resource for the environmental scientist because real world processes operate at a range of different scales, and hence all the differently specified data will have their own particular uses. Despite this, the vast array of data available has arguably limited the practical use of remote sensing in the management arena, largely because the non-specialist user does not know what data source will aid in the problems that they wish to solve. The coastal zone is an example of a unique and dynamic environment, the effective management of which requires a thorough understanding of how it works. For the coastal zone manager, geo-spatial data and information is therefore a necessity. Although remote sensing has the potential to provide much of this information, the coastal manager will not necessarily know which sensor will provide the best imagery (in terms of spatial, spectral and temporal resolution) for each particular problem that has to be resolved. There is a need, therefore, for a generic set of guidelines that will help the coastal manager decide what set of imagery, from which sensor, will best provide the information required to solve the specific problem. In essence, the issue to be resolved must be matched with the utility (or characteristics) of the sensor. Initially, such a set of guidelines may be constructed using a paper-based matrix.