An UAV and Satellite Multispectral Data Approach to Monitor Water Quality in Small Reservoirs

Abstract

A multi-sensor and multi-scale monitoring tool for the spatially explicit and periodic monitoring of eutrophication in a small drinking water reservoir is presented. The tool was built with freely available satellite and in situ data combined with Unmanned Aerial Vehicle (UAV)-based technology. The goal is to evaluate the performance of a multi-platform approach for the trophic state monitoring with images obtained with MultiSpectral Sensors on board satellites Sentinel 2 (S2A and S2B), Landsat 8 (L8) and UAV. We assessed the performance of three different sensors (MultiSpectral Instrument (MSI), Operational Land Imager (OLI) and Rededge Micasense) for retrieving the pigment chlorophyll-a (chl-a), as a quantitative descriptor of phytoplankton biomass and trophic level. The study was conducted in a waterbody affected by cyanobacterial blooms, one of the most important eutrophication-derived risks for human health. Different empirical models and band indices were evaluated. Spectral band combinations using red and near-infrared (NIR) bands were the most suitable for retrieving chl-a concentration (especially 2 band algorithm (2BDA), the Surface Algal Bloom Index (SABI) and 3 band algorithm (3BDA)) even though blue and green bands were useful to classify UAV images into two chl-a ranges. The results show a moderately good agreement among the three sensors at different spatial resolutions (10 m., 30 m. and 8 cm.), indicating a high potential for the development of a multi-platform and multi-sensor approach for the eutrophication monitoring of small reservoirs.

Evaluation of Unoccupied Aircraft System (UAS) Remote Sensing Reflectance Retrievals for Water Quality Monitoring in Coastal Waters

“…Many UAS aquatic remote sensing studies use Structure-from-Motion (SfM) photogrammetric techniques to stitch individual UAS images into ortho-and georectified mosaics (Arango and Nairn, 2019;Castro et al, 2020;McEliece et al, 2020;Olivetti et al, 2020). This approach applies matching key points from overlapping UAS imagery in camera pose estimation algorithms to resolve 3D camera location and scene geometry (Westoby et al, 2012;Arango et al, 2020).…”

“…UAS fill an operational gap between in situ and satellite remote sensing methods. While the current available commercial multispectral UAS sensor technology is geared toward terrestrial applications, mostly precision agriculture, the spectral bands have been useful in retrieving water quality parameters in aquatic water bodies (Choo et al, 2018;Arango and Nairn, 2019;Baek et al, 2019;Castro et al, 2020;Olivetti et al, 2020). A UAS sensor package designed for aquatic environments would undoubtedly improve remotely sensed retrievals and water quality measurements.…”

Cloud Cover throughout All the Paddy Rice Fields in Guangdong, China: Impacts on Sentinel 2 MSI and Landsat 8 OLI Optical Observations

“…Therefore, conversion functions need to be developed to convert spectral data from Landsat 8, Sentinel 2, and other sensors to mitigate inconsistencies in surface reflectance and vegetation indices due to spatial resolution and spectra configuration [52]. Nowadays, unmanned aerial system (UAS) platforms' low dependence on cloudless conditions, high mobility during data acquisition, controlled revisit cycles, and extremely high ground resolution make them an excellent complement to satellite imagery [53,54]. In particular, most of the world's rice paddies are located in areas with continuous cloudy conditions, and therefore satellite data can be less available than for other crops [55,56].…”

Applications of Unmanned Aerial Systems (UASs) in Hydrology: A Review

“…Penmetcha et al [140] proposed a deep learning-based algae detector and a multi-robot system algae removal planner integrated by an UAS and a USV. More recently, Castro et al [38] presented a multisensor tool to monitor water quality in a Spanish reservoir affected by eutrophication. Their approach combined satellite, in situ data and multispectral UAS imagery to retrieve chl-a concentrations, which indicates the trophic status of the system.…”