Mapping of submerged aquatic vegetation with a physically based process chain

Abstract

Mapping the submerse vegetation is of prime importance for the ecological evaluation of an entire lake. Remote sensing techniques are efficient for such mapping tasks, if the retrieval algorithms and processing methods are robust and mostly independent from additional ground truth measurements. The Modular Inversion Program (MIP) follows this concept. It is a processing tool designed for the recovery of hydro-biological parameters from multi- and hyper-spectral remote sensing data. The architecture of the program consists of physical inversion schemes that derive bio-physical parameters from the measured radiance signal at the sensor. Program modules exist for the retrieval of aerosols, sun glitter correction, atmospheric corrections, retrieval of water constituents among others. For the purpose of mapping the bottom coverage in optically shallow waters, two modules have been added to MIP. The first module calculates the bottom reflectance using the subsurface reflectance, the depth and an approximation of the water constituent concentrations as input. The second module fractionalizes the bottom reflectance to three endmembers of specific reflectance spectra by linear unmixing. The three endmembers are specific reflectance spectra of bottom sediments, small growing macrophytes (Characeae) and tall macrophytes such as Potamogeton perfoliatus & P. pectinatus. The processing system has been tested with data collected from the multi-spectral airborne scanner Daedalus AADS1268 at Lake Constance, Germany, for multi- temporal analysis.