Chloe-Marie Hawley
Published in
6 min readMay 2


Phytoplankton are microscopic aquatic phototrophs, ubiquitous in both marine and freshwater ecosystems, that are critical to the health and functioning of the oceans and the climate. Phytoplankton biomass is a measure for marine primary productivity; phytoplankton form the bases of all aquatic food chains and account for approximately half of the production of organic matter on Earth (Boyce et al., 2010). Additionally, phytoplankton is an important agent in the global carbon cycle; as phototrophs, phytoplankton fix carbon dioxide through photosynthesis, accounting for about 40% of the total carbon dioxide fixed naturally (Falkowski, 1994). These two important roles exemplify the ecosystem services phytoplankton provide, services that can extend to the whole planetary biogeochemical system. Consequently, variation in the ocean’s phytoplankton biomass can explain trends in the global carbon budget and possible changes in trophic level interactions, which are important to understand particularly in the face of climate change.

The distribution of phytoplankton across the oceans is driven primarily by patterns in nutrient levels. Oligotrophic regions, such as the subtropical gyres (deep blue areas, Figure 1), are nutrient poor areas that sustain low levels of phytoplankton biomass and thus low primary productivity levels. In contrast, eutrophic regions are nutrient rich and maintain high phytoplankton biomass, sometimes with frequent algal blooms when nutrients are in excess. The North Atlantic and the majority of coastal zones are eutrophic (see green areas, Figure 1). As phytoplankton biomass is tightly coupled to nutrient availability, changes, such as expansions or reductions, in these eutrophic and oligotrophic regions can predict spatial changes in phytoplankton abundances.

Figure 1: Oceanic chlorophyll concentration (proxy for phytoplankton biomass) follows the patterns of nutrient levels in the oceans: nutrient-poor oligotrophic regions show low levels of chlorophyll (blue) and nutrient-rich eutrophic regions show high levels of chlorophyll (green). (Modified image from Uitz et al., 2006).

Natural variability in phytoplankton abundance is in synchrony with seasonal change in climatic variables, notably daylight, temperature, and nutrient levels. In general, phytoplankton abundances vary over a 12-month period, in a cycle known as the spring-bloom. Like terrestrial plants, phytoplankton bloom at the onset of spring when daylight increases and nutrients, brought up the water column by storms and turbulent flows during the winter months, settle near the surface. Certain regions can instead experience a dominant 6-month period of phytoplankton abundance, blooming once in spring and once in autumn. Variability around these natural cycling patterns follows annual variation in climatic and oceanic parameters, especially sea surface temperatures. Moreover, the natural patterns are confounded by other driving forces, including human activity, anomalous weather events, and changes in trophic interactions. Partly due to the multiplicity of interactions, no global wide trend of increase or decrease in phytoplankton biomass in the past century has been robustly observed (Wernand et al., 2013). However, this is also due to the inconsistent quantitative analysis of phytoplankton biomass over sufficient spatio-temporal scales.

The importance of phytoplankton is undeniable as the primary producers of the oceans and key contributors to global carbon sequestration. So how can we better understand and monitor phytoplankton biomass at the global scale?

Phytoplankton biomass is readily derived from Earth Observation data that records several important oceanographic parameters. Satellite imagery records ocean colour which can be used to derive chlorophyll concentration in the ocean, a proxy for the phytoplankton biomass present. This is because changes in water colour are caused by a change in the composition of optically active substances, such as biological pigments. An increase in chlorophyll concentration colours the water green, and sometimes red due to the carotenoids in certain phytoplankton species. Thus, by measuring the blue, green, and red wavelengths within the ocean image, an estimate of the chlorophyll concentration can be calculated. We set out to illustrate the ease at which phytoplankton populations can be located, and observed to record change over time, using satellite observations from space.

Our methodology was simple, and while the full details of an accurate calculation are much more involved, it serves to demonstrate how quickly and easily we can start to get a sense of the global abundance of these microorganisms that are crucial for sustaining delicate marine ecosystems and maintaining Earth’s climate balance.

Planet Lab PBC’s PlanetScope satellite constellation produces comprehensive daily images of the globe at a 3m resolution. Using the surface reflectance product we were able to download pre-processed surface reflectances in 8 spectral bands for a variety of locations along the north-east coast of Australia around the Great Barrier Reef (Figure 2). Near-surface chlorophyll concentration can be calculated using empirical relationships derived from ground truth and remote sensing surface reflectances in the 440–670 nm spectral regime. Following the band difference approach established by Hu et al. (2019), we generated a measure that is proportional to chlorophyll concentration and therefore the abundance of phytoplankton, validating this measure against NASA’s publicly available chlorophyll concentration data product obtained using MODIS. MODIS measures at a 4km resolution, so the pixel values of the surface reflectance data were averaged over a 4km area for this validation. This allowed us to plot colour enhanced visuals of the same region, and observe how the abundance of these microorganisms change on short timescales. Our area of interest was a region of the Great Barrier Reef in the Coral Sea, Eastern Australia (Figure 2).

Figure 2: Area of interest along the Queensland coast. Coordinates (longitude, latitude) of top left corner are (145.486, -16.518) and bottom right is (145.584, -16.573). (Source Google Earth)

The results were as follows:

Figure 3: Distribution of phytoplankton populations on 20/09/2022 (left) and 02/10/2022 (right). Greener regions correspond to areas with more phytoplankton. Images derived from satellite imagery provided by Planet Labs PBC.

Simply, an abundance of near surface phytoplankton looks greener than the surrounding plankton-free ocean, so by comparing surface reflectance in the blue and green spectral bands, we can literally see the phytoplankton from space. This is pretty amazing.

The method is faced with many limitations, such as a lack of comparison to in situ measurements; noise in the data due to reef structures and significant changes in ocean depth; and neglect of the algorithmic complexity required to deal with many different concentrations of phytoplankton (see here for detail on the algorithms used to assemble the NASA Earth Data chlor_a product). However, this project was not intended to be a rigorous scientific study. Instead, we show that qualitative changes in phytoplankton biomass over time can be observed despite difficulties in determining accurate quantitative measurements. These observations are made in a region close to the shore, an important stepping stone to overcoming one of the biggest limitations within this field; the lack of phytoplankton data derived from satellite imagery for areas within 100km of the shoreline. In effect, PlanetScope provides satellite imagery for coastal areas that have typically been excluded, and thus is an important contributor to improving the observations, and thereby understanding, of phytoplankton biomass in coastal ecosystems.

The finer resolution of satellite imagery coupled with the development of algorithms that can distinguish between different types of phytoplankton (Xi et al., 2020) and increase the accuracy of existing algorithms, promises a leap in the improvement with which we can observe and monitor phytoplankton biomasses across time and space. This project was meant only as an exploration of what can be obtained quickly with PlanetScope data, and a primitive demonstration of the abundance of these microorganisms and how they change over time.

There has been growing concern over the anthropogenic effects on phytoplankton populations, for example, it has been shown that barge trafficking in the River Ganga, India, causes a significant decrease in plankton biomass and damage to their cell structure (Das Sarkar, 2019). The high resolution daily imaging available on PlanetScope could prove invaluable to assessing the live impact of human activity such as change in commercial shipping routes or an increase in the number of fishing vessels in any given location.

About The Authors:

Maximilian Hadley (MPhys), Joseph Phelps (MPhys) and Chloe-Marie Hawley (MBiol) are final year masters students at the University of Oxford with research interests spanning Climate Science, Earth Observation and Marine Ecology. This project took place as part of the Oxford University Micro-Internship Programme with industry participant Amentum Scientific. Under the guidance and expertise of Dr Iwan Cornelius, Managing Director of Amentum Scientific, we have learnt a great deal about how to derive important parameters from satellite imagery and how to interpret these observations with biological and ecological relevance. The data used for the project was obtained using the PlanetScope constellation of cubesats (SuperDoves) and made available via the Planet Explorer web-tool. We have all greatly appreciated the opportunity to access this relatively new platform and get first-hand experience with industry leaders. Ultimately, the outcome of our exploratory project has been to help direct the company’s use of fine-scale satellite imagery to monitor phytoplankton biomass across the Eastern Australian coastline, to flag up important limitations and their solutions, and finally to suggest possible ways to monitor the effects of human activity (such as shipping) on phytoplankton biomass within the Coral Sea, Australia.