Development of a Suspended Particulate Matter (SPM) Algorithm forthe Coastal Zone Mapping and Imaging Lidar (CZMIL)

摘要

Algorithms for estimation of the concentrations of suspended particulate matter (SPM) are being developed in order tofulfill USAGE design requirements for the Coastal Zone Mapping and Imaging Lidar (CZMIL). The lidar sensor will beused to characterize bottom depth as well as water column reflectance properties that can be related to SPMconcentrations. Because lidar uses an artificial light source (i.e., the laser), it is considered an active system.Additionally, CZMIL will make observations of the water column with a hyperspectral imaging sensor, which acquiresimages of the magnitude of water leaving radiance at multiple wavelengths. Since the hyperspectral sensor relies solelyon ambient light, it is considered a passive system.Current research includes the testing and validation of published algorithms for estimating SPM from passive spectraldata produced by ship-borne, airborne and satellite-based sensors, as well as the development of a new active-passivedata fusion algorithm. The new algorithm will combine observations from CZMIL's lidar and hyperspectral sensors.Data which are being collected in the northern Gulf of Mexico as part of an NSF-funded project will be applied to thisresearch. These data come from ship-borne hyperspectral radiometers, as well as in situ SPM and optical observations.These observations will be used to validate the applicability of published SPM algorithms to the project site. This paperexplores the relationship between SPM and two optical parameters used in algorithm development, remote sensingreflectance and the backscattering coefficient.