- Related Research Areas
- Carbon Cycle & Ecosystems
Bio-optical models have been claimed to be spatially, temporally and instrumentally transferable. Nevertheless, these advantages of bio-optical models have not been systematically addressed for inland waters. This research is aimed at testing the robustness of bio-optical models for mapping inland water quality variables (chlorophyll-a, phycocyanin, color dissolved organic matter (CDOM), tripton) from the measurement of field portable spectroradiometer, satellite hyperspectral (Hyperion) and multispectral (MODIS/SeaWiFS) sensors. Multi-temporal datasets collected by each sensor type will be acquired for three central Indiana Reservoirs: Eagle Creek, Geist and Morse Reservoirs. A field campaign concurrent with satellite image acquisition will be conducted to measure field reflectance and collect water samples. The water constituent concentration and inherent optical properties will be determined in field and laboratories. Using these data as input to bio-optical models, we will evaluate 1) whether bio-optical models developed for one reservoir perform well when applied to another reservoir without recalibration (spatial transferability) or a model developed at one season is applicable to the same area at another season (temporal transferability); and 2) whether a bio-optical model has high predictive capability when applied to the dataset which is acquired by another instrument (instrumental transferability). These tests will be carried out by combining bio-optical models with sensitivity analysis to 1) separate the spatial transferability from the temporal transferability, 2) identify the situations where the bio-optical algorithms are applicable to satellite imagery, and 3) determine how the spectral band configuration/spectral resolution will affect the performance of bio-optical models. Broadly, the accessibility to a set of well-documented inherent optical properties (IOPs) of the water quality variables and software provides the remote sensing community with a space remote sensing-based measurement tool for monitoring the spatial distribution and concentration of blue-green algae from satellite observations, and a stepping-stone for other users aiming at deriving the IOPs of water quality variables for other inland waters. The result from the instrumental transferability test will help design spectral configuration of future sensors and provide the scientific basis for the next generation of water quality remote sensing.
Project PI: Lin Li/Indiana University-Purdue University at Indianapolis
UPUI Department of Earth Sciences 723 West Michigan Street, Room SL118 Indianapolis, Indiana 46202-5191
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