Software application for spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A tool for identifying cyanobacteria genera from remotely sensed data
Journal of Open Research Software (JORS)
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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.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Software application for spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A tool for identifying cyanobacteria genera from remotely sensed data |
| Series title | Journal of Open Research Software (JORS) |
| DOI | 10.5334/jors.499 |
| Volume | 12 |
| Issue | 1 |
| Year Published | 2024 |
| Language | English |
| Publisher | Ubiquity Press |
| Contributing office(s) | WMA - Observing Systems Division |
| Description | 17 p. |
| Google Analytic Metrics | Metrics page |