AEDMA-NDMAI: Automatic Extraction and Daily Monitoring of Algal Blooms Using Normalized Difference MODIS Algae Index

Algal blooms are ecological phenomena with long-lasting effects on the ecosystem and on the climate. Often, they reduce the oxygen level underwater, creating adverse circumstances for aquatic species’ survival, development, and reproduction. In this article, the mapping of algal bloom incidents and their daily monitoring is automated using Python script and the Earthdata website. The automation is carried out in eight separate modules and then integrated. Test site dictionary, configuration, query data, download MODIS data, open image data, clip data, implementing a novel Normalized Difference MODIS Algae Index (NDMAI), and threshold are the eight modules used for automating the extraction and daily monitoring. This automation requires two inputs: firstly, the bounding box, i.e., lower left coordinate (LLC) and upper right coordinate (URC) of the test site, and secondly, the date range. In this article, eight test sites are used to extract algal bloom incidents, and a ninth test site is used for the extraction and daily monitoring, which are reported by the NASA Earth Observatory (NEO). The proposed framework automates the process of enhancing algal bloom features in MODIS imagery, and daily monitoring is successfully accomplished, and the results perfectly match the algal bloom region in the test sites reported by the NEO.