This is the last in a series of posts devoted to reviewing the algorithms currently implemented in the cloud-based HICO Image Processing System (HICO IPS). Links to the other posts in this series are provided below. Here we provide an overview of the algorithm utilized for retrieving multiple layers of water and habitat information for shallow coastal environments.
Objective – Demonstrate the capability to simultaneously derive information on water properties, water depth and seabed features in shallow coastal environments using a complex hyperspectral image processing algorithm.
Algorithm – Derives inherent optical properties for absorption and backscattering (phytoplankton absorption, detritus and gelbstoff absorption, particle backscattering, total absorption, and total backscattering [m-1]), bottom albedo (reflectance at 550 nm), and water depth (depth [m]) using a semi-analytical inversion model (Goodman and Ustin 2007; Lee et al. 1999, 1998).
Note that this algorithm uses a computationally intensive optimization scheme, which can result in long processing times for large areas. As a reference, the example shown here required approximately 15 minutes to generate output. It is suggested that users select relatively small regions-of-interest when implementing this algorithm.
Inputs – User specified HICO scene, with optional region-of-interest; optional NDWI land/water mask, with user adjustable NDWI threshold; and specification of desired output parameter.
Output – Selected output parameter depicted using a blue-red color ramp, where blue represents low values and red represents high values. If the NDWI land/water mask was selected, then the selected optical property is only calculated and mapped for the water pixels.
Try it out today for yourself: http://hyspeedgeo.com/HICO/
Goodman J, Ustin SL (2007) Classification of benthic composition in a coral reef environment using spectral unmixing, Journal of Applied Remote Sensing, vol. 1(1), 011501-011501.
Lee Z, Carder KL, Mobley CD, Steward RG, Patch JS (1999) Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization, Applied Optics, vol. 38(18), 3831-3843.
Lee Z, Carder KL, Mobley CD, Steward RG, Patch JS (1998) Hyperspectral remote sensing for shallow waters. I. A semianalytical model, Applied Optics, vol. 37(27), 6329-6338.