Context and objectives
Algorithms for remote sensing of suspended particulate matter and chlorophyll concentration are quite mature and applications relating to coastal sediment transport and environmental monitoring are routinely using satellite data. The challenge is now to estimate more than just concentration. Spaceborne hyperspectral instruments offer the potential to yield more information on aquatic particles, both algal and non-algal.
Dedicated ocean colour missions provide daily data but only at moderate spatial resolution (~300-1000m). Many high resolution (~10-100m) spaceborne instruments designed for land applications are suitable for aquatic applications if algorithms for atmospheric correction and for aquatic product retrievals are developed. For patchy distributions of micro- and macro-algae this high spatial resolution will be important to ensure that spectral features are not missed.
The general objective is to develop and test algorithms for remote sensing of turbid coastal and inland waters, using both hyperspectral and high resolution multispectral satellite data.
Specific remote sensing objectives include:
• Design and testing of hyperspectral algorithms for phytoplankton species composition in turbid waters and identification of their limitations.
• Design and testing of hyperspectral algorithms for macro-algae cover and type.
• Design and testing of new algorithms for retrieval of particulate backscatter spectral slope and particulate backscatter:absorption for non-algal particle size/type in turbid waters.
• Refinement of algorithms for high spatial resolution missions with limited spectral bands
• Design of an in situ instrument system for a hyperspectral validation network
• Validation and exploitation of high spatial resolution data as a tool to study plankton and benthic algal dynamics and bloom formation in coastal and inland waters
• Provide recommendations for future satellite missions as regards design of spectral bands and signal:noise for aquatic applications
Specific scientific exploitation objectives include:
• Increase understanding of multi-species micro-algal blooms in a shallow turbid coastal area with pronounced spatial/temporal variation in turbidity and nutrients related.
• Increase our understanding of micro- and macro-algal blooms in shallow freshwater and brackish inland waters, with focus on benthic-pelagic interaction and algal groups.
• Increase our understanding of sediment transport in coastal and estuarine systems by supplementing existing remotely sensed concentration data with particle size information.
Expected scientific results
• New validated algorithms based on hyperspectral data:
- For phytoplankton species composition in turbid waters;
- For floating and submerged macro-algae;
- For suspended particle size/type in turbid waters.
• Improve algorithms for and exploitation of high spatial resolution missions.
• An automated in situ spectroradiometer system for deployment on platforms and buoys to provide validation data for optical missions.
• Provide quantified signal:noise requirements for future hyperspectral satellite missions and optimal “aquatic application” band sets for future multispectral satellite missions.
Expected products and services
Algorithms will be developed for the following new products:
- Micro-algae species composition (in turbid waters)
- Macro-algae coverage and, if possible, composition or physiological state
- Non-algae particle type and/or size
Potential users include water quality managers, aquatic scientists including biologists and sediment transport specialists, dredging companies, space agencies, industrial designers of hyperspectral space missions as well as other remote sensing scientists.
|Project leader(s):||IRSNB/KBIN - Directorate Natural Environment - Ecosystems data processing and modelling|