Detecting Cyanobacterial Blooms in the Caloosahatchee River and Estuary Using PlanetScope Imagery and Deep Learning

Freshwater cyanobacterial blooms pose a major threat to local ecosystems, economies, and public health. Monitoring these occurrences is essential for water resource managers worldwide. Satellite remote sensing techniques can detect and quantify blooms in large inland and estuarine water bodies but monitoring blooms in small water bodies (< 10 km2), including narrow river/canal systems, remains challenging. This is due to the coarse spatial resolution (>300 m) or low re-visit frequency (>10 days) of most operational satellite sensors. The ephemeral nature of cyanobacterial blooms and their tendency to form dense surface mats (or “scums”) that aggregate nearshore further highlight the need for sensors with higher spatial and temporal resolutions. In this study, a deep learning model based on convolutional neural network U-net was developed to detect cyanobacterial blooms (i.e., scums) in the highly modified and managed Caloosahatchee River (i.e., C-43 canal) and Caloosahatchee River Estuary (CRE) (Florida, USA) using Dove imagery (3-m resolution) obtained near-daily from the PlanetScope satellite constellation. The approach consisted of three steps: 1) training and validating the U-net model with “ground truth” images; 2) classifying bloom pixels; and 3) quantifying bloom area using linear unmixing. Validation results indicate an overall F1 score of 89.6% when assessing bloom area. Application of the model revealed the westward expansion of a cyanobacteria bloom from C-43 to CRE in summer 2018, indicating the physical transport of the bloom originating upstream in Lake Okeechobee to the estuary. This approach was tested on other inland water bodies, indicating potential for monitoring cyanobacterial blooms on a global scale.

I. Introduction

Cyanobacterial blooms are frequently reported in oceanic, coastal, and inland water bodies worldwide, with global expansion linked to eutrophication and climate change [1], [2]. These blooms often negatively impact local ecosystems, public health, and economies. High-biomass blooms can damage ecosystems by reducing levels of dissolved oxygen and obstructing light to the benthos [3], [4]. Many freshwater cyanobacteria genera produce toxins that can harm human health by affecting the liver, nervous system, and skin [5], [6]. The economic impacts of cyanobacterial blooms, while widely recognized, remain poorly understood [7], [8].