Chapter 10
THE ROLE OF INTEGRATED INFORMATION ACQUISITION AND
MANAGEMENT IN THE ANALYSIS OF COASTAL ECOSYSTEM CHANGE
STUART PHINN, KAREN JOYCE, PETER SCARTH AND CHRIS ROELFSEMA
Centre for Remote Sensing & Spatial Information Science, School of Geography,
Planning and Architecture, The University of Queensland, 4072, Australia
s.phinn@uq.edu.au
1. Introduction
Coastal aquatic ecosystems are often perceived as a complex and “difficult” area
from a management perspective due to their dynamic nature and joint management by
multiple local, state, and national level government agencies. Additionally, collecting
information to understand, monitor, and manage these ecosystems necessitates the use
of spatial information suited to the management agency and/or agencies (Belfiore,
2003; Treitz, 2003). The objective of this chapter is to demonstrate how environmental
indicators can be used to provide a basis for designing and implementing mapping and
monitoring programs using remotely-sensed and field data for coastal and coral reef
environments. This chapter complements Whitehouse and Hutt (2005 – this book), by
providing a practical approach for matching remotely sensed data sets within common
requirements for monitoring and managing coastal environments.
2. Information Requirements for Understanding, Monitoring and Managing
Coastal and Coral Reef Environments
2.1 NATURAL RESOURCE MANAGEMENT IN COASTAL AQUATIC ECOSYSTEMS
The material covered in this chapter concerns the application of remote sensing
technologies to coastal aquatic systems. Coastal aquatic ecosystems are defined here as
substrate, benthos, water column, and water surface features extending from the meanhigh water level to the edge of the continental shelf. This definition includes inter-tidal
mangroves and saltmarsh, tidal flats, rocky shores, seagrass beds, coral reefs, organic
and inorganic water column contents (seston), and water surface characteristics. As an
interface between terrestrial, atmospheric, and aquatic environments this is a highly
dynamic area characterised by processes and structures that change on hourly to daily
time-scales due to tidal, wind, wave, and river processes.
Due to the number of human activities conducted in coastal environments, they are
monitored and managed at local to regional, national, and in some cases, international
levels. Common activities range from extractive resource use (fishing, tourism),
recreation (boating, diving, swimming), and urban development (housing, port,
industrial, commercial) to natural functions (habitat, aesthetics, shoreline stabilisation,
flood reduction, nutrient sinks/sources). As a result, there is a critical requirement for
information to support ecosystem management.
Numerous types of remote sensing approaches have been used for monitoring
coastal environments around the world, mainly through a combination of field survey
217
and Management Applications, 217-249.
© 2006 Springer. Printed in the Netherlands.
L.L. Richardson and E.F. LeDrew (eds.), Remote Sensing of Aquatic Coastal Ecosystem Processes: Science
THE ROLE OF INTEGRATED INFORMATION ACQUISITION AND
MANAGEMENT IN THE ANALYSIS OF COASTAL ECOSYSTEM CHANGE
STUART PHINN, KAREN JOYCE, PETER SCARTH AND CHRIS ROELFSEMA
Centre for Remote Sensing & Spatial Information Science, School of Geography,
Planning and Architecture, The University of Queensland, 4072, Australia
s.phinn@uq.edu.au
1. Introduction
Coastal aquatic ecosystems are often perceived as a complex and “difficult” area
from a management perspective due to their dynamic nature and joint management by
multiple local, state, and national level government agencies. Additionally, collecting
information to understand, monitor, and manage these ecosystems necessitates the use
of spatial information suited to the management agency and/or agencies (Belfiore,
2003; Treitz, 2003). The objective of this chapter is to demonstrate how environmental
indicators can be used to provide a basis for designing and implementing mapping and
monitoring programs using remotely-sensed and field data for coastal and coral reef
environments. This chapter complements Whitehouse and Hutt (2005 – this book), by
providing a practical approach for matching remotely sensed data sets within common
requirements for monitoring and managing coastal environments.
2. Information Requirements for Understanding, Monitoring and Managing
Coastal and Coral Reef Environments
2.1 NATURAL RESOURCE MANAGEMENT IN COASTAL AQUATIC ECOSYSTEMS
The material covered in this chapter concerns the application of remote sensing
technologies to coastal aquatic systems. Coastal aquatic ecosystems are defined here as
substrate, benthos, water column, and water surface features extending from the meanhigh water level to the edge of the continental shelf. This definition includes inter-tidal
mangroves and saltmarsh, tidal flats, rocky shores, seagrass beds, coral reefs, organic
and inorganic water column contents (seston), and water surface characteristics. As an
interface between terrestrial, atmospheric, and aquatic environments this is a highly
dynamic area characterised by processes and structures that change on hourly to daily
time-scales due to tidal, wind, wave, and river processes.
Due to the number of human activities conducted in coastal environments, they are
monitored and managed at local to regional, national, and in some cases, international
levels. Common activities range from extractive resource use (fishing, tourism),
recreation (boating, diving, swimming), and urban development (housing, port,
industrial, commercial) to natural functions (habitat, aesthetics, shoreline stabilisation,
flood reduction, nutrient sinks/sources). As a result, there is a critical requirement for
information to support ecosystem management.
Numerous types of remote sensing approaches have been used for monitoring
coastal environments around the world, mainly through a combination of field survey
217
and Management Applications, 217-249.
© 2006 Springer. Printed in the Netherlands.
L.L. Richardson and E.F. LeDrew (eds.), Remote Sensing of Aquatic Coastal Ecosystem Processes: Science