Chapter 8
INTEGRATION OF NEW DATA TYPES WITH HISTORICAL ARCHIVES TO
PROVIDE INSIGHT INTO COASTAL ECOSYSTEM CHANGE AND
VARIABILITY
JENNIFER GEBELEIN
Department of International Relations, Florida International University, Miami,
Florida, 33199, USA. Jennifer.Gebelein@fiu.edu
1. Introduction
As populations increase around the world, anthropogenic influences are changing
the environment with unforeseen rapidity and unknown consequences (Lunetta, 1998).
The changes that are occurring result in environmental transformations at local,
regional, and global scales. Earth observing technologies now allow us to monitor
landscape changes at multitemporal (as well as regional and global spatial) scales.
However, the speed that technology has advanced has not been matched by parallel
progress in conservation, environmental management, or developmental regulations.
We can lessen this gap by making scientists and managers aware of historical data
archives as well as current baseline datasets and products.
Recently developed technologies allow scientists to integrate large and varied
datasets over many different spatial and temporal scales. This type of integration was
not possible 40 years ago (Chang, 2002). Since that time there has been an evolution of
remote sensing and Geographic Information Systems (GIS) technology which has
allowed for many types of data integration. The importance of data integration is
directly linked to current multidisciplinary research that incorporates aspects of both
human and physical science data sets (Konecny, 2003).
When current and historical data are combined, new patterns, relationships, and
results emerge (Maynard, 2003). Utilizing historical datasets for time series analyses
allows scientists to model what may happen in the future, based on observed change in
the past (Longely, 1996; DeMers, 2002). These types of historical, integrative analyses
allow researchers to ask new questions such as: Where are the most threatened
ecosystems? What types of anthropogenic stresses are influencing an ecosystem? How
do we identify indicators of ecosystem health at different scales? Is it possible to
predict what the effect of long-term environmental impacts will be (Lunetta, 1998)?
Since anthropogenic activities are the catalyst for most of the environmental changes
we are observing, data creation, integration, and analyses should address issues of not
only physical change, but also the social impetus for why such changes occurred.
Understanding the reasons driving such change allow scientists to better analyze data
and help managers develop better and creative conservation strategies (Walsh et al.,
2002).
1.1 ECOSYSTEM CHANGE
Many ecosystems are vulnerable to degradation through human misuse and
mismanagement. However, some are at a higher risk than others. According to the
World Resource Institute’s (WRI) Pilot Analysis of Global Ecosystems (PAGE) report
183
and Management Applications, 183-197.
© 2006 Springer. Printed in the Netherlands.
L.L. Richardson and E.F. LeDrew (eds.), Remote Sensing of Aquatic Coastal Ecosystem Processes: Science
INTEGRATION OF NEW DATA TYPES WITH HISTORICAL ARCHIVES TO
PROVIDE INSIGHT INTO COASTAL ECOSYSTEM CHANGE AND
VARIABILITY
JENNIFER GEBELEIN
Department of International Relations, Florida International University, Miami,
Florida, 33199, USA. Jennifer.Gebelein@fiu.edu
1. Introduction
As populations increase around the world, anthropogenic influences are changing
the environment with unforeseen rapidity and unknown consequences (Lunetta, 1998).
The changes that are occurring result in environmental transformations at local,
regional, and global scales. Earth observing technologies now allow us to monitor
landscape changes at multitemporal (as well as regional and global spatial) scales.
However, the speed that technology has advanced has not been matched by parallel
progress in conservation, environmental management, or developmental regulations.
We can lessen this gap by making scientists and managers aware of historical data
archives as well as current baseline datasets and products.
Recently developed technologies allow scientists to integrate large and varied
datasets over many different spatial and temporal scales. This type of integration was
not possible 40 years ago (Chang, 2002). Since that time there has been an evolution of
remote sensing and Geographic Information Systems (GIS) technology which has
allowed for many types of data integration. The importance of data integration is
directly linked to current multidisciplinary research that incorporates aspects of both
human and physical science data sets (Konecny, 2003).
When current and historical data are combined, new patterns, relationships, and
results emerge (Maynard, 2003). Utilizing historical datasets for time series analyses
allows scientists to model what may happen in the future, based on observed change in
the past (Longely, 1996; DeMers, 2002). These types of historical, integrative analyses
allow researchers to ask new questions such as: Where are the most threatened
ecosystems? What types of anthropogenic stresses are influencing an ecosystem? How
do we identify indicators of ecosystem health at different scales? Is it possible to
predict what the effect of long-term environmental impacts will be (Lunetta, 1998)?
Since anthropogenic activities are the catalyst for most of the environmental changes
we are observing, data creation, integration, and analyses should address issues of not
only physical change, but also the social impetus for why such changes occurred.
Understanding the reasons driving such change allow scientists to better analyze data
and help managers develop better and creative conservation strategies (Walsh et al.,
2002).
1.1 ECOSYSTEM CHANGE
Many ecosystems are vulnerable to degradation through human misuse and
mismanagement. However, some are at a higher risk than others. According to the
World Resource Institute’s (WRI) Pilot Analysis of Global Ecosystems (PAGE) report
183
and Management Applications, 183-197.
© 2006 Springer. Printed in the Netherlands.
L.L. Richardson and E.F. LeDrew (eds.), Remote Sensing of Aquatic Coastal Ecosystem Processes: Science