Description

Climate exerts the main control on the seasonal cycles of natural vegetation. For African rangelands, plant water availability is the most limiting factor and consequently vegetation growth is mostly driven by rainfall. Climate change is causing an amplification of the hydrological cycle in many of these rangelands, implying that heavier rainfall events are alternated by longer and more intense drought periods. Remote sensing helps to map and understand vegetation dynamics, and as such allows to evaluate how changing climate affects these dynamics. In relation to satellite image time series, the term “land surface phenology” is frequently used to refer to the analysis of spatial-temporal patterns of vegetation development.

Traditionally, phenology has been assessed with coarse-resolution observation (e.g. MODIS at 250m), taking advantage of the daily revisit capability, allowing to obtain sufficient cloud-free observations throughout the season. However, image time series at this spatial resolution cannot reveal detailed spatial phenological patterns, making it less suited for precise understanding of the functioning of spatially heterogeneous rangelands. In the past decade, various new satellites have been launched. The past decade has seen the launch of multiple fine-resolution satellite sensors with short repeat cycles. These include the European Sentinel-1 and -2 satellites, which have been successfully explored in various phenology studies. While many studies initially focussed on case studies for small areas, funded initiatives exist to bring phenology estimation to scale, i.e. to assess phenology at 10-30m resolution for an entire continent. A challenge for African rangelands is however that herbaceous vegetation reacts rapidly to rainfall events, as well as to drought, making vegetation cycles often short and with possible ‘interruptions’ of reduced photosynthesis/greenness. This proposed study will explore how both radar observations from Sentinel-1 and optical observations from Sentinel-2 can help in the effective retrieval of phenology for African rangelands.

Objectives and Methodology

The main objective is to assess how both Sentinel-1 (radar) and Sentinel-2 (optical) can be used for effective assessment of vegetation seasonality at 10m resolution across African rangelands. The precise objectives need to be defined, but may comprise:
- To assess if and where temporal signals from Sentinel-1 and Sentinel-2 allow for an effective description of vegetation cycles;
- To design an approach for complementary use of both data sources for effective estimation of vegetation phenology;
- To test the approach against in-situ data, such as for example from digital repeat photography (phenoCams)

The study can take a stronger focus on specific sites (with in-situ data), but also take a sampling approach to compare and understand the Sentinel-1 and -2 signals across the African continent.

Good programming experience is a prerequisite for successful execution of this project.

Further reading

Cheng, Y., Vrieling, A., Fava, F., Meroni, M., Marshall, M., & Gachoki, S. (2020). Phenology of short vegetation cycles in a Kenyan rangeland from PlanetScope and Sentinel-2. Remote Sensing of Environment, 248, 112004
Meroni, M., d'Andrimont, R., Vrieling, A., Fasbender, D., Lemoine, G., Rembold, F., Seguini, L., & Verhegghen, A. (2021). Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2. Remote Sensing of Environment, 253, 112232
Schlund, M., & Erasmi, S. (2020). Sentinel-1 time series data for monitoring the phenology of winter wheat. Remote Sensing of Environment, 246
Meroni, M., d'Andrimont, R., Vrieling, A., Fasbender, D., Lemoine, G., Rembold, F., Seguini, L., & Verhegghen, A. (2021). Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2. Remote Sensing of Environment, 253, 112232