A team of scientists from the U.S. Geological Survey, in collaboration with researchers across academia, government and industry, published a dataset that provides information on water quality trends for more than 55,000 lakes across the country.
The dataset brings together over 35 years of data from the Landsat archive with data from the U.S. Environmental Protection Agency's National Lakes Assessment to identify shifts in lake water quality.
This work is the first to relate surface reflectance with lake trophic state in a way that can be used to understand how lakes may be greening, bluing or browning nationally. Lake trophic state is a metric intended to provide holistic assessments of a lake’s physical, chemical and biological processes.
The dataset is designed with computational reproducibility and customization at the forefront. All scripts used to create the dataset were written in R, an open-source coding language, using the ‘targets’ package. The ‘targets’ format creates an automated data pipeline infrastructure, which enables the dataset to be updated as new Landsat satellite imagery becomes available or as successive National Lakes Assessment sampling campaigns occur. The ‘targets’ pipeline is crystallized in a Docker container, which enables users to run the pipeline regardless of differences in operating systems.
The dataset’s emphasis on reproducibility earned it recognition as a USGS open science success story.
By coupling satellite-based remote sensing with fundamental limnological principles, the dataset provides the means to apply meaningful freshwater science frameworks at the national scale to identify macroscale patterns and trends in lake trophic state. This approach moves beyond remote sensing of individual parameters to provide holistic insights into the physical, chemical, biological and ecosystem properties of a lake.
Learn more about the dataset here: National-scale remotely sensed lake trophic state from 1984 through 2020 | Scientific Data (nature.com)