Algae blooms occur when certain kinds of algae grow very quickly, forming patches, or "blooms,” in the water. These blooms can be indicators of water degradation and emit powerful toxins that can endanger human and animal health.
According to the World Health Organization, waterborne diseases cause approximately 1.5 million human deaths annually. It is estimated that 58% of that burden, or 842,000 deaths per year, is attributable to a lack of safe drinking water supply, sanitation and hygiene. Public access to safe drinking water supply and sanitation has never been more important to reduce the spread of pandemic diseases, such as COVID-19.
Scientists from around the world are working on developing an alert system for algae bloom to improve current water resources management in Latin America. This project is one of 32 projects selected as part of the Group on Earth Observations (GEO) - Google Earth Engine (GEE) Program that provides funding to tackle environmental and social challenges using open Earth Observation (EO) data.
We spoke with Project Lead, Felipe Lobo from the Federal University of Pelotas, Brazil, to learn more about the project and how his team is using GEE to develop an alert system for algae blooms that can be accessed and shared by the general public—especially water managers.
Felipe, what challenge are you tackling with this project?
The lack of water quality data and information in Latin America is preventing better water resources management. The use of remote sensing is still incipient, something we want to change by providing easy and quick information about water degradation caused by algal blooms.
So far, most of the effort towards algal bloom monitoring has been done in North America and Europe, while in Latin America such a tool has not been developed yet. A series of factors explain this lack of information such as incomplete databases to validate water quality products and an absence of large research groups for pre-processing satellite images needed to generate information on an operational basis.
Fortunately, cloud-computing provided by GEE allows small research groups to advance on satellite image processing and generate important information for water quality managers.
Can you provide us with an overview of your project?
Our project aims to create an Algae Bloom Monitoring Application (named AlgaeMAp) for the main reservoirs and lakes in cities of Latin America. The idea is to use the Sentinel-2 collection to generate NDCI (Normalised Difference Chlorophyll-a Index) as an indicator of algal blooms, chlorophyll-a and trophic state index (TSI) all within a five day time frame.
- The first step is to develop a code in GEE to process Sentinel-2A MuliSpectral Instrument S2A-MSI imagery for atmospheric correction, cloud mask, water mask and NDCI (Normalized Difference Chlorophyll Index) function. Here, we would like to use machine learning to classify TSI classes and give the probability per pixel of belonging to this or that class.
- Secondly, we gather water quality information to validate the index. Project participants will share some of their in situ data to support the validation of NDCI derived from the imagery or even calibrate/validate other chlorophyll-a algorithms.
- Third step is to build this script into a GEE application, so any end-user can query for location and date, choose the visualisation map, create time-series charts, spatial stats maps. All the data, layers and charts, would be downloadable.
How will AlgaeMAp impact your community?
This project will bring together water quality and remote sensing specialists, and programmers to develop resourceful tools focused on algal blooms in the Latin America region. This project will also have impacts on other sectors including human and ecosystem health, agriculture, fishing and food insecurity.
The approach of this project is transdisciplinary, involving colleagues from different disciplines such as physics, mathematics, computing, biology, chemistry, but also institutions from different levels such as Science Institutes, Government dependencies and Universities.
At the end of the project, we'd like to generate a diagnosis of water quality in the main cities of Latin America. Once we have the scientific article published, a full version will be released for open access.
How does Google Earth Engine help you achieve your project-related goals?
GEE has provided our project with big data processing capabilities and an application interface for information access. Here is a demonstration of the first version of the AlgaeMAp developed for the Tietê River Basin, São Paulo, Brazil:
How will the GEO-GEE funding help your project?
The GEO-GEE funding will help with capacity building for our researchers as well as students. It will also help with script development to improve coding techniques, and building the actual Google Earth Engine application.
EO Data Science’s role in the GEO-GEE Program
EO Data Science partnered with Google Earth Engine and the Group on Earth Observations to launch the GEO-GEE Program, which supports GEO member countries to operationalise their science as they strive to tackle the world’s biggest sustainable development challenges.
In July 2020, 32 projects across 22 countries were selected for the program which offers $3 million USD towards product licenses and $1 million USD in technical support from EO Data Science. This funding and support will help these projects tackle global challenges using open Earth data. Read the announcement and list of winners here.