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Accurate estimates of chlorophyll-a concentration (Chl-a) from remotely sensed data for inland waters are challenging due to their optical complexity. In this study, a framework of Chl-a estimation is established for optically complex inland waters based on combination of water optical classification and two semi-empirical algorithms. Three spectrally(More)
Morse Reservoir (MR), a major source of the water supply for the Indianapolis metropolitan region, is now experiencing nuisance cyanobacterial blooms. These blooms cause water quality degradation, as well as reducing the aesthetic quality of water by producing toxins, scums, and foul odors. Hyperspectral remote sensing data from both in situ and airborne(More)
— Accurate remote estimation of chlorophyll-a (CHL) concentration for turbid inland waters is a challenging task due to their optical complexity. In situ spectra (n = 666) measured with ASD and Ocean Optics spectrometers from three drinking water sources in Indiana, USA, were used to calibrate the partial least squares model (PLS), artificial neural network(More)
Phycocyanin (PC) is the unique and important accessory pigment for monitoring toxic cyanobacteria in inland waters. In this study, a semi-analytical algorithm combining both three band indices and a baseline algorithm (TBBA) was developed to estimate PC concentrations and then tested in three eutrophic and turbid reservoirs. TBBA does not need to optimize(More)
Locations of collapsed buildings (CBs) caused by earthquake are the most needed information by the disaster reduction team, due to their strong correlation with losses of properties and human lives. Optical remote sensing images with high spatial resolution (OIHR) play an important role in extracting CBs. Currently there are mainly two approaches: manual(More)
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