Profile
Abstract
Jian Peng is a full professor for Hydrology and Remote Sensing at the University of Leipzig. He is also leading the Remote Sensing Department at the UFZ in Leipzig. His research interests are the quantitative retrieval of land surface parameters from remote sensing data, the assimilation of remote sensing data into climate and land surface process models, understanding land-atmosphere interactions using earth system models and observational data, and quantification of climate change impact on water resources. His research in particular focuses on estimation of high-resolution land surface water and energy fluxes from satellite observations, and the investigation of hydrological and climatic extremes as well as their impacts on ecosystems. He has been involved in various national and international research projects funded by e.g., ESA, EU, UK space agency, NERC, and DFG. He is also Co-Editor-in-Chief of the journal "Geoscience Data Journal”.
Professional career
- since 01/2020
Professor for Hydrology and Remote Sensing, Leipzig University - since 01/2020
Head of Remote Sensing Department, Helmholtz Centre for Environmental Research – UFZ - 01/2018 - 01/2020
Senior researcher, University of Oxford - 01/2015 - 12/2017
Research scientist, University of Munich - 01/2013 - 01/2015
Post-Doc, Max Planck Institute for Meteorology
Education
- 01/2018 - 12/2020
Postgraduate Certificate in Teaching and Learning in Higher Education, University of Oxford - 01/2010 - 12/2013
PhD in Earth science, Max Planck Institute for Meteorology
- Hydrology and the atmospheric environment
- Satellite remote sensing
- Process-based modeling and data-driven methods
- Climate extremes and climate variability
- show detailsMahecha, M.; Bastos, A.; Bohn, F. J. et al.Biodiversity loss and climate extremes - study the feedbacksNature. 2022. pp. 30–32.
- show detailsPeng, J.; Albergel, C.; Balenzano, A. et al.A roadmap for high-resolution satellite soil moisture applications - confronting product characteristics with user requirementsRemote sensing of environment. 2021.
- show detailsPeng, J.; Tanguy, M.; Robinson, E.; Pinnington, E.; Evans, J.; Ellis, R.; Cooper, E.; Hannaford, J.; Blyth, E.; Dadson, S.Estimation and evaluation of high-resolution soil moisture from merged model and Earth observation data in the Great BritainRemote sensing of environment. 2021.
- show detailsBalenzano, A.; Mattia, F.; Satalino, G. et al.Sentinel-1 soil moisture at 1 km resolution: a validation studyRemote sensing of environment. 2021.