
Lars Eklundh
Professor

Optimizing Remote Sensing Data and Light Use Efficiency Model for Accurate Gross Primary Production Estimation in African Rangelands
Author
Summary, in English
This paper focuses on the meticulous selection of optimal remote sensing and climate datasets for Gross Primary Productivity (GPP) estimation in African rangelands. Utilizing Eddy Covariance Flux Tower data, we refine data selection and employ a Light Use Efficiency (LUE) model, with Sentinel 2 for photosynthetically active vegetation quantification, MODIS for Photosynthetically Active Radiation (PARin), and ERA5 Land reanalysis for climatic variables. The Eddy Covariance-based LUE-GPP model is identified as superior compare to other LUE based GPP models and further enhanced through fine-tuning LUEmax and climate scalars. Footprint analysis determines a 500m footprint size, aligning with literature recommendations. Comparative analyses with various LUE models reveal ECLUE's superiority. Statistical validations affirm key parameter selections, leading to a reliable LUE-based GPP model tailored for African rangelands. The proposed model contributes to accurate GPP assessment, essential for informed environmental stewardship in these critical ecosystems.
Department/s
- Dept of Physical Geography and Ecosystem Science
- BECC: Biodiversity and Ecosystem services in a Changing Climate
- LU Profile Area: Nature-based future solutions
- MERGE: ModElling the Regional and Global Earth system
Publishing year
2024
Language
English
Pages
4289-4293
Publication/Series
International Geoscience and Remote Sensing Symposium (IGARSS)
Links
Document type
Conference paper
Publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
Topic
- Physical Geography
- Remote Sensing
Keywords
- African Rangelands
- GPP
- LUEModel
- Remote Sensing
- Sentinel 2
Conference name
2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024
Conference date
2024-07-07 - 2024-07-12
Conference place
Athens, Greece
Status
Published
ISBN/ISSN/Other
- ISBN: 9798350360325