data of biophysical reef properties to be easily collected, georeferenced and placed
in a format able to be integrated with coral reef airborne or satellite images.
Continued improvements in the integration of field data with image data are
essential for the calibration and validation of thematic mapping and biophysical
applications on coral reefs.
1.4.2 Scientific Advances
At a scientific level there are two driving forces: (1) advances in image processing
algorithms; and (2) development of applications/algorithms/models for mapping
specific biophysical properties of coral reefs.
In the first case, image processing algorithms continue to be developed within
and external to the remote sensing field. Digital image processing spans mathematics, physics, computer vision, signal processing, astronomy and medical
imaging, to name a few; hence development of image correction, enhancement,
thematic mapping and modeling is widespread. The most recent advances finding
their way into coral reef applications are object-based image analysis, multivariate
data fusion and new forms of spatially explicit regression analysis and unmixing.
Once these new approaches have been identified, the next stage is testing their
applicability for mapping, monitoring or modeling relevant coral reef biophysical
properties. Thematic mapping of coral reef zones from multispectral and hyperspectral images will continue as the main application area in reef remote sensing,
but with increased integration of other image data sets (e.g., LiDAR; Chap. 7) into
object-based image analysis algorithms (e.g., segmentation then classification) and
classification models allowing multiple forms of data (e.g., support vector
machines, random forest). The application of analytic and semi-analytic modeling
approaches to estimate per-pixel water depth, water properties and bottom
reflectance is moving to operational status and the output data present a new set of
variables to be fully tested with thematic mapping approaches (Chap. 4).
The area of multispectral and hyperspectral coral reef remote sensing with the
most potential is the further development of techniques for mapping reef properties
such as: the amount of live coral, algae and sediment cover; structural forms of
coral cover; benthic micro-algae biomass; and coral and algae light absorption
efficiency. These properties provide key links for studies assessing coral productivity, coral reef biochemistry, carbon-fluxes and nutrient dynamics on reefs.
Advancements in these areas will require close collaboration between coral reef
ecosystem scientists and the biophysical remote sensing community.
Acknowledgments Ian Leiper for provision of selected figures and graphics for the chapter.
24
S. R. Phinn et al.
in a format able to be integrated with coral reef airborne or satellite images.
Continued improvements in the integration of field data with image data are
essential for the calibration and validation of thematic mapping and biophysical
applications on coral reefs.
1.4.2 Scientific Advances
At a scientific level there are two driving forces: (1) advances in image processing
algorithms; and (2) development of applications/algorithms/models for mapping
specific biophysical properties of coral reefs.
In the first case, image processing algorithms continue to be developed within
and external to the remote sensing field. Digital image processing spans mathematics, physics, computer vision, signal processing, astronomy and medical
imaging, to name a few; hence development of image correction, enhancement,
thematic mapping and modeling is widespread. The most recent advances finding
their way into coral reef applications are object-based image analysis, multivariate
data fusion and new forms of spatially explicit regression analysis and unmixing.
Once these new approaches have been identified, the next stage is testing their
applicability for mapping, monitoring or modeling relevant coral reef biophysical
properties. Thematic mapping of coral reef zones from multispectral and hyperspectral images will continue as the main application area in reef remote sensing,
but with increased integration of other image data sets (e.g., LiDAR; Chap. 7) into
object-based image analysis algorithms (e.g., segmentation then classification) and
classification models allowing multiple forms of data (e.g., support vector
machines, random forest). The application of analytic and semi-analytic modeling
approaches to estimate per-pixel water depth, water properties and bottom
reflectance is moving to operational status and the output data present a new set of
variables to be fully tested with thematic mapping approaches (Chap. 4).
The area of multispectral and hyperspectral coral reef remote sensing with the
most potential is the further development of techniques for mapping reef properties
such as: the amount of live coral, algae and sediment cover; structural forms of
coral cover; benthic micro-algae biomass; and coral and algae light absorption
efficiency. These properties provide key links for studies assessing coral productivity, coral reef biochemistry, carbon-fluxes and nutrient dynamics on reefs.
Advancements in these areas will require close collaboration between coral reef
ecosystem scientists and the biophysical remote sensing community.
Acknowledgments Ian Leiper for provision of selected figures and graphics for the chapter.
24
S. R. Phinn et al.