MSc thesis topic: Relating Amazonian rainforest photosynthesis to clouds

Photosynthesis and evapotranspiration strongly regulate the moisture content available to clouds. To better understand and quantify the links between photosynthesis and clouds in the Amazon, it is important to investigate surface fluxes at different spatial and temporal scales. The Amazon Tall Tower Observatory offers a unique scientific platform to obtain a more detailed view on the surface-atmosphere interactions. In this project, the available tower data will be augmented by remotely sensed imagery. Multiple remotely sensed datasets are available at a daily or even more frequent temporal resolution but there is general a trade-off between spatial and temporal resolution of available data.

This project will produce an inventory of the available satellite imagery over the immediate surroundings of the tower, in the period of August 1-20, 2022 with a focus on photosynthesis. Canopy near-infrared reflectance and terrestrial photosynthesis will be characterised by a variety of different vegetation indices, including NIRv.

Relevance to research/projects at GRS or other groups

This project will bridge the ongoing collaboration between GRS and MAQ (Meteorology and Air Quality). More information on the project can be found here.

Objectives and Research questions

• Study and relate NIRv using Planet/Cubesat (or S2 and Landsat) to cloud patterns as well as evapotranspiration and photosynthesis.
• Comparison of NIRv products with in-situ observations taken at the ATTO tower.
• Focus on the diurnal variability of NIRv and clouds during the three-week campaign (August 2022).

Requirements

• Depending on the background of the candidate we will provide some support to meteorology: concepts, processes, and variables.
• Geo scripting
• Affinity with work with large scale remote sensing datasets

Literature and information

• Badgley, Grayson, Christopher B. Field, and Joseph A. Berry. (2017). Canopy near-infrared reflectance and terrestrial photosynthesis. Science advances3.3: e1602244.
• Kong, Juwon, et al. (2022). Matching high resolution satellite data and flux tower footprints improves their agreement in photosynthesis estimates.Agricultural and Forest Meteorology316: 108878.
• Vilà‐Guerau de Arellano, J., Hartogensis, O., Benedict, I., De Boer, H., Bosman, P. J., Botía, S., ... & Van Heerwaarden, C. C. (2023). Advancing understanding of land–atmosphere interactions by breaking discipline and scale barriers. Annals of the New York Academy of Sciences.
• Sanchez, A. H., Picoli, M. C. A., Camara, G., Andrade, P. R., Chaves, M. E. D., Lechler, S., ... & Queiroz, G. R. (2020). Comparison of Cloud cover detection algorithms on sentinel–2 images of the amazon tropical forest. Remote Sensing,12(8), 1284.

Expected reading list before starting the thesis research

• Depending on the background of the MSC student we can recommend additional literature.

Theme: Sensing & measuring