Hyperspectral Remote Sensing Of The Coastal Ocean: Adaptive Sampling And Forecasting Of Nearshore In Situ Optical Properties
Abstract
LONG-TERM GOAL. We propose to develop and validate an integrated adaptive sampling and modeling system for nowcasting and forecasting the 3-dimensional evolution of inherent optical properties (IOPs) in coastal waters. This will be accomplished by developing an integrated observation network providing realtime data allowing for adaptive sampling in nearshore coastal waters. The data will also be used to develop hyperspectral remote sensing techniques for optically complex coastal waters while also providing physical/optical data for coupled data assimilative hydrodynamic ecosystem models currently under development. OBJECTIVES. Our objectives are to 1) develop and deploy moored, shipboard, and autonomous bio-optical systems in the coastal ocean to ground-truth remote sensing imagery, 2) quantify the physical, chemical and biological processes that define the spatial and temporal variability in the spectral IOPs for the nearshore coastal ocean during summer-time upwelling, 3) refine and calibrate existing hyperspectral optical models to derive IOPs from remotely sensed data using the above datasets and, 4) in collaboration with other principal investigators couple a radiative transfer ecosystem module to the data-assimilative hydrodynamic model.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 1999
- Accession Number
- ADA629702
Entities
People
- Dale Haidvogel
- Oscar Schofield
- Scott Glenn
Organizations
- Rutgers University–New Brunswick