Model
Digital Document
Publisher
Florida Atlantic University
Description
Invasive exotic plant species cause a number of problems in native south
Florida ecosystems, and a great deal of effort is being put into controlling the
populations ofthese species. Control efforts require updated information on the
locations of exotic species. This information can be obtained from high resolution
remotely sensed data such as digital orthoimagery and LIDAR. Extraction of
information from these data sources is often problematic using traditional pixel-based
image processing techniques. An object oriented method of image analysis, however,
has been shown to be better suited to this task.
One invasive exotic species that has become widespread in south Florida is
Casuarina equisetifolia, also known as Australian pine. This study develops a semiautomated
procedure for detecting Australian pine over a large, diverse area with high
resolution remotely sensed data using the object oriented method of analysis.
Florida ecosystems, and a great deal of effort is being put into controlling the
populations ofthese species. Control efforts require updated information on the
locations of exotic species. This information can be obtained from high resolution
remotely sensed data such as digital orthoimagery and LIDAR. Extraction of
information from these data sources is often problematic using traditional pixel-based
image processing techniques. An object oriented method of image analysis, however,
has been shown to be better suited to this task.
One invasive exotic species that has become widespread in south Florida is
Casuarina equisetifolia, also known as Australian pine. This study develops a semiautomated
procedure for detecting Australian pine over a large, diverse area with high
resolution remotely sensed data using the object oriented method of analysis.
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