Dryland drought monitoring with ECOSTRESS, ENMAP, PRISMA, Sentinel-2
The topic is open and also suitable for GEM students in track 3 – GEM for Ecosystems & Natural Resources.
Suggested Elective Courses:
- Advanced Image Analysis
- Environmental Monitoring with Satellite Image Time Series
- Remote Sensing and Modelling of Primary Productivity and Plant Growth
Statistics, agronomy and programming background/experience recommended.
ET is the water lost to the atmosphere through plant stomata during photosynthesis and from the surface following a wetting event. It is an important component of the global water cycle and the energy cycle (as latent heat). Satellite-driven ET models are widely used to address important questions in Earth system science but contain much uncertainty. Uncertainties are especially high over drylands because of the lack of data and poor parameterization of process-based models. ET is traditionally estimated with thermal infrared imagery. Hyperspectral narrowbands are especially sensitive to biochemical and biophysical changes related to plant growth and development. The bands have rarely been used to reduce ET model uncertainty because sensors were in short supply. This roadblock no longer exists with the recent launch of spaceborne hyperspectral missions: Germany Space Agency’s ENMAP and Italian Space Agency’s PRISMA missions.
The main aim of this topic is to evaluate the performance of ECOSTRESS thermal infrared, ENMAP and PRISMA hyperspectral narrowbands, and Sentinel-2 multispectral broadbands in estimating evapotranspiration (ET) and ET-related drought monitoring indices, such as the evaporative stress index (ESI). The analysis focuses on the Kapiti Research station in Machakos County, Kenya where regular eddy covariance (EC) flux tower ET measurements were collected alongside ground-based FLOX tower spectroradiometric data in 2019-2020 and 2023-2024. The station is characterized as dryland agriculture and rangelands. The topic can be broken down into three main tasks: (i) collect and process ground data; (ii) extract ECOSTRESS ENMAP, PRISMA, Sentinel-2 spectral information in the footprint of the towers; and (iii) evaluate satellite data performance with machine learning or a process-based technique in terms of ET and ESI. The research supports an ongoing European Space Agency project: https://www.itc.nl/hyrelief/.
Marshall, M., Thenkabail, P., Biggs, T., Post, K., 2016. Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation). Agric. For. Meteorol. 218, 122–134.