CHAPTER 34
Matching Issue to Utility: An Hierarchical Store of Remotely Sensed
Imagery for Coastal Zone Management
S.D. King and D.R. Green
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
473
D.R. Green and S.D. King (eds.), Coastal and Marine Geo-Information Systems, 473–486.
© 2003 Kluwer Academic Publishers. Printed in the Netherlands.
Matching Issue to Utility: An Hierarchical Store of Remotely Sensed
Imagery for Coastal Zone Management
S.D. King and D.R. Green
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
473
D.R. Green and S.D. King (eds.), Coastal and Marine Geo-Information Systems, 473–486.
© 2003 Kluwer Academic Publishers. Printed in the Netherlands.