Thesis subject
MSc thesis topic: Land surface phenology dynamics in Chile Mediterranean biodiversity hotspot.
Land Surface Phenology (LSP) has been defined as the study of the spatiotemporal patterns in the vegetated land surface as observed by synoptic sensors. LSP characterizes episodes of greening and browning of vegetated land surfaces using remote sensing imagery in a synoptic way. Time series of vegetation indices calculated from optical sensors such as MODIS, Landsat, or Sentinel are used to reconstruct LSP dynamics. Since it is an affordable state variable with global coverage based on vegetation index products, it can be used to assess changes in ecosystem functioning and to understand forest responses to disturbances. Accurately assessing the phenological dynamics of vegetation is key to understanding terrestrial ecosystem responses, especially in threatened biodiversity hotspots.
Despite the availability of global LSP products like MODIS MCD12Q2 and methods for LSP modelling, in Chile, LSP assessment studies are sparse. However, a recent step forward is the creation of the first National Phenological Network (PhenChile, http://phenchile.pucv.cl/). PhenChile provides a platform for vegetation monitoring with near-real time information of phenocams for 10 sites in Central Chile (30˚ – 37˚S). This thesis aims to compare current available methods for LSP modelling in mediterranean ecosystems.
Relevance to research/projects at GRS or other groups
With this research you will contribute to an ongoing PhD research project.
Objectives and Research questions
- Compare the state of the art methods available for LSP modelling with EO data.
- Assess general performance of the methods using phenocam data.
Requirements
- Geo-scripting
- Advanced Earth Observation
Literature and information
- Henebry, G. M., & De Beurs, K. M. (2013). Remote sensing of land surface phenology: A prospectus. In Phenology: An Integrative Environmental Science (pp. 385–411). Springer Netherlands.
- Broich, M., Huete, A., Paget, M., Ma, X., Tulbure, M., Coupe, N. R., Evans, B., Beringer, J., Devadas, R., Davies, K., & Held, A. (2015). A spatially explicit land surface phenology data product for science, monitoring and natural resources management applications. Environmental Modelling & Software, 64, 191–204.
- PhenChile Phenological Network (In Spanish).
Expected reading list before starting the thesis research
- Caparros-Santiago, J. A., Rodriguez-Galiano, V., & Dash, J. (2021). Land surface phenology as indicator of global terrestrial ecosystem dynamics: A systematic review. In ISPRS Journal of Photogrammetry and Remote Sensing (Vol. 171, pp. 330–347). Elsevier B.V.
- Kong, D., McVicar, T. R., Xiao, M., Zhang, Y., Peña-Arancibia, J. L., Filippa, G., Xie, Y., & Gu, X. (2022). phenofit: An R package for extracting vegetation phenology from time series remote sensing. Methods in Ecology and Evolution, 13(7), 1508–1527.
Theme(s): Sensing & measuring; Modelling & visualisation