Remote Sensing Facilities
Remote sensing plays an important role in the coastal, open-ocean and climate-change related research being performed at Bigelow Laboratory for Ocean Sciences. The main advantage is that large regions of ocean and coastal habitats can be surveyed in literally minutes, providing a synoptic view, not possible with standard oceanographic sampling. Ocean color imagery allows the quantification of plant chlorophyll (an indicator of phytoplankton biomass) within spatial scales ranging from kilometers to 10,000 km (i.e. entire ocean basins). Bigelow researcher Barney Balch has also been involved with developing algorithms for the quantification of calcium carbonate from space. Joaquim Goes and Helga Gomes have been developing satellite algorithms for estimating nitrate and nitrate-based carbon export into the oceans. Paty Matrai and Mike Sieracki have been developing an algorithm for estimating community respiration in coastal waters and Matrai and co-workers are using ocean color to estimate primary production in the Arctic Ocean, both hindcasting and forecasting changes.
The National Aeronautics and Space Administration (NASA) has three ocean color satellite sensors currently in orbit - the Sea Wide Field of view Sensor (SeaWiFS) and two Moderate Resolution Imaging Spectrometers (MODIS) aboard the TERRA and AQUA satellite platforms, respectively. These sensors provide the bulk of ocean color images used by Bigelow investigators, but ocean color imagery also is utilized from satellite sensors such as the Medium Resolution Imaging Spectrometer (MERIS, run by the European Space Agency, ESA), the Ocean Colour Monitor (OCM; aboard the Indian Remote Sensing Satellite IRS-P4) plus historical data taken by the Coastal Zone Color Sensor (CZCS; NASA) and Advanced Earth Observing Satellite (ADEOS-1 and -2; Japanese Space Agency, NASDA). Bigelow investigators also utilize remotely sensed wind data (e.g. NSCAT) and sea surface height data (e.g. TOPEX) that provide estimates of basin - and mesoscale ocean circulation.
Remote sensing also is a critical tool for classification of terrestrial and aquatic environments in coastal biomes. At Bigelow, this work is being done by Peter Larsen. Advances in the spatial and spectral resolution capabilities of satellite-borne sensors has allowed affordable investigations of macrotidal coastal systems that previously relied exclusively on costly aircraft based imagery. Reliable estimates of the habitat areas of major marine producer groups now allow ecosystem modeling in the macrotidal Cobscook Bay, Maine. Results are comprehensive, synoptic, objective, and affordable, and match the spatial scales of the coastal environments better than conventional sampling permits. The bulk of this work has utilized Landsat Thematic Mapper and IKONOS imagery as input into a computer-generated, unsupervised, classification technique.