Software Application for Spectral Mixture Analysis for Surveillance of Harmful Algal Blooms (SMASH): A Tool for Identifying Cyanobacteria Genera from Remotely Sensed Data

Abstract

Remote sensing is often used to detect algae, but standard techniques do not provide information on the types of algae present or their potential to form a harmful algal bloom (HAB). We developed a framework for identifying algal genera based on reflectance: SMASH, short for Spectral Mixture Analysis for Surveillance of HABs. The Software Application for SMASH (SAS) was developed in MATLAB and makes use of a Multiple Endmember Spectral Mixture Analysis (MESMA) algorithm implemented in Python but packaged as a standalone executable. SAS includes functions for importing hyperspectral images, resampling spectral libraries, evaluating endmember spectral separability, performing MESMA, and generating various output data products.

Keywords

• harmful algal blooms (habs)
• hyperspectral remote sensing
• cyanobacteria genera
• multiple endmember spectral mixture analysis (mesma)