A constrained optimization technique for estimating environmental parameters from CZMIL hyperspectral and lidar data

Airborne imaging spectroscopy to monitor urban mosquito microhabitats

“…In reality the observed spectrum is affected by the bottom reflectance as well as optical properties of the water (Kim et al, 2010). Residential pools have a wide range of synthetic colors and materials.…”

“…However, it is possible that the spectral data could also estimate other physical attributes. For example, the semianalytical treatment of Lee et al (1999); Kim et al (2010) models optically deep water by expressing subsurface reflectance as a function of optical properties such as absorption and diffuse attenuation. One could add bottom reflectance and depth terms to model shallow water such as pools.…”

Combining Lidar Data and Hyperspectral Imagery for Coastal Engineering and Environmental Characterization

“…Prior to performing a constrained inversion technique, preprocessing steps must be performed on the imagery. The radiance for each flight line is divided by the downwelling solar radiance and normalized [3]. Here, the Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS) model, is used to make this conversion from radiance to total at sensor reflectance [4].…”

“…The SHOALS data must first be synced to the CASI flightlines using automated processes within the DPS that combine the IMU and GPS navigation data from both sensors. During this process, the CASI raw data are radiometrically corrected, in which values are converted from a digital number to radiance (µWcm -2 sr -1 nm -1 ) [3]. Following this step, a lidar pointcloud is generated from the SHOALS data.…”

Overview of the coastal zone mapping and imaging lidar (CZMIL): a new multisensor airborne mapping system for the U.S. Army Corps of Engineers

“…It employs a photogrammetric backprojection technique and delauncy triangulation to rapidly produce the RGB image mosaics. The second is a new approach to the constrained inversion of the passive spectral data to produce spectral seafloor reflectance images, seafloor endmember fraction images, and environmental images characterizing the water column 17 . This spectral optimization algorithm, developed at Optech International, delivers significantly improved accuracies in the passive seafloor reflectance image cube, as compared to the ambiguity-search approach previously implemented in REA 18 .…”