Improved ECOsystem PROductivity modeling by innovative algorithms and remotely sensed PHEnology indicaTors (ECOPROPHET).
Context and objectives
Ecosystems supply a huge variety of services to society. Many of those services are related to biomass production, for instance food and fibre production (provision services) and carbon sequestration (regulation services). This has encouraged substantial scientific efforts to estimate ecosystem productivity. Nevertheless, current estimates of net primary production are highly uncertain and there is room for improvement. The increasing availability of spaceborne observations and high capabilities of recently launched satellite missions represent important opportunities to improve current estimates.
In the ECOPROPHET project we intend to improve simulations of ecosystem productivity by using new Earth Observation products from different platforms (e.g. ESA Sentinel 2, Proba-V, MODIS, GOME) that reflect canopy functioning (e.g. chlorophyll content indices, green NDVI, Red-edge, Photochemical Reflectance Index (PRI), Clorophyll Fluorescense (CF)).
The scientific objectives of this project are:
- to identify the best photosynthesis-related RS indicator(s) for representing functional ecosystem phenology;
- to obtain a better estimation of GPP and energy balance by reparameterizing the phenology modules of two Land Surface models (LSMs; ORCHIDEE and SURFEX), and prescribing different phenology for a third (LSA-SAF);
- to explore the potential of the new RS indicator(s) for deriving a new GPP product; and
- to develop a new biomass production algorithm.
All products and simulations will be validated against field data available from several databases (ICOS, FLUXNET, SPECNET and the in-house biomass production database) and compared to other products available from different projects. A specific working package on validation will be set-up.
For further details see the ECOPROPHET web site (http://ecoprophet.meteo.be).
Methodology
The activities in the Ecoprophet project and the inter-institutional collaboration are organized in work packages, as illustrated in following scheme.
Results
RMI team contributes to ECOPROPHET at several levels, in particular doing research on moderate/high resolution modelling of water, energy and CO2 fluxes. As one of the first step, it has contributed to study the spatial homogeneity around ground fluxes sites in view to the selection of reference validation sites.
Histograms of NDVI values at a specific dates give insight on the heterogeneity in vegetated cover across a given area and how it varies in different seasons. The following Figure shows NDVI histograms derived from Sentinel-2 observations in winter and summer at two locations: Lonzee (crops) and Brasschaat (Scots pine forest). The histograms were built for three different area sizes around eddy covariance towers and may help in determining the diversity of sources impacting the measurements.
Execution
Period: 12/2016 – 1/ 2022.
RMI participants: Miguel Barrios, Jan De Pue (developers and scientists), Alirio Arboleda (scientist), Françoise Meulenberghs and Rafiq Hamdi (scientific coordination and administration).
Partner Institutions: The project is powered by the expertise of an international consortium of scientific institutions: the Centre of Excellence PLECO of the University of Antwerp, the Royal Meteorological Institute of Belgium, the Centre for Research on Ecology and Forestry Application (CREAF), Catalonia, Spain; the Laboratoire de Sciences du Climat et l’Environment (LSCE), France and the College of Urban and Environmental Sciences, Peking University, China.
Funding source: Belspo Stereo3 program (contract SR/00/334) and RMI.
References
Balzarolo, M., Van Hoolst, R., Vicca, S., Swinnen, E., Cai, W., Ghent, D., Bloomfield, K., Prentice, I. C., De Pue, Barrios, J. M., Gellens-Meulenberghs, F. Hamdi, R., Maleki, M., Wieneke, S., Ciais, Ph., Maignan, F. and Janssens, I., 2023: Development and validation of global productivity models using Earth Observations: the ECOPROPHET and TerrA-p projects. Abstract of oral presentation. LPVE23 - Workshop on Land Product Validation and Evolution. 12-14th June 2023, Frascati, Italy.
Barrios, J. M., Arboleda, A., De Pue, J., Chormanski, J. and Gellens-Meulenberghs, F., 2020: Continuous Daily Evapotranspiration with Optical Spaceborne Observations at Sub-Kilometre Spatial Resolution. Remote Sensing, 12, 2218; doi:10.3390/rs12142218.
Barrios, J.M., Gellens-Meulenberghs, F., Hamdi, R., Wieneke, S., Janssens, I., Balzarolo, M., 2017: Landscape heterogeneity around ICOS Belgian eddy covariance sites investigated through satellite imagery.Poster presented at: ICOS Belgium Science Conference. Gembloux, Belgium.
Barrios, J.M., Gellens- Meulenberghs, F., Hamdi, R., Wieneke, S., Janssens, I. and Balzarolo, M., 2018: Landscape heterogeneity around flux measurement stations investigated through Sentinel-2 and PROBA-V satellite imagery. Proceedings of the SPIE Remote Sensing. Berlin, 10-13 September 2018, 13 pp.
De Pue, J., Barrios, J. M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Balzarolo, M., Janssens, I., Maignan, F., and Gellens-Meulenberghs, F., 2021: Evaluation of key parameters controlling phenology-induced variability of surface fluxes in land surface models, EGU General Assembly 2021, online, Abstracts, EGU21-11445.
De Pue, J., Barrios, J. M., Liu, L., Ciais, Ph., Arboleda, A. , Hamdi, R., Balzarolo, M., Maignan, F. and Gellens-Meulenberghs, F., 2022 : Local scale evaluation of the simulated interactions between energy, water and vegetation in land surface models. BioGeosciences Discussion, https://doi.org/10.5194/bg-2021-355.
De Pue, J., Barrios, J. M., Liu, L., Ciais, Ph., Arboleda, A. , Hamdi, R., Balzarolo, M., Maignan, F. and Gellens-Meulenberghs, F., 2022 : Local-scale evaluation of the simulated interactions between energy, water and vegetation in ISBA, ORCHIDEE and a diagnostic model. BioGeosciences, 19, 4361-4386, https://doi.org/10.5194/bg-19-4361-2022, 26 pp.
De Pue, J., Barrios, J. M., Maignan, F., Liu, L., Ciais, Ph., Arboleda, A., Hamdi, R., Balzarolo, M. and Gellens-Meulenberghs, F., 2020: Phenology-induced energy and carbon fluxes in land surface models. EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17702.
De Pue, J., Wieneke S., Barrios, J. M., Liu, L., Maleki M ., Ciais, P., Arboleda, A., Hamdi, R., Bastos A., Janssens, I., Maignan, F., and Gellens-Meulenberghs, F., Balzarolo, M., 2021: Seasonal variability of GPP and phenology in remote sensed observations and land surface models, Oral presentation to IGARSS 2021, Brussels, on line.
De Pue, J., Wieneke, S., Bastos, A., Barrios, J. M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Maleki, M., Maignan, F., Gellens-Meulenberghs, F., Janssens, I., and Balzarolo, M., 2023: Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-994.
Janssens, I., Balzarolo, M., Wieneke, S., Maleki, M., Vicca, S., Campioli, M., Gellens-Meulenberghs, F., Hamdi, R., Barrios, M., Ciais, P., Maignan, F., Bastos, A., Piao, S., Peng, S., 2017: ECOPROPHET Improved ECOsystem PROductivity Modeling by Innovative Algorithms and Remotely Sensed PHEnology Indicators. Poster presented at: ICOS Belgium Science Conference, Gembloux, Belgium.
Maleki, M., Arriga, N., Roland M., Wieneke, S., Barrios, J.M., Van Hoolst, Janssens, I., Balzarolo, M. Accounting the drought into the in situ vegetation indices in heathland ecosystem. IGARSS 2021.
Maleki, M.; Wieneke, S.; Barrios, J. M.: Liu, Q.; Janssens, I.; Balzarolo, M., 2018: Identification of Novel Remote Sensed Based Indicators for Phenology. Abstract, EGU 2018, 8-13 April, Vienna, Austria.
Wieneke, S., Bastos, A., Balzarolo, M., Barrios, J.M., Janssens, I., 2021: Evaluating the relationship between SIF and GPP under climate extremes. EGU General Assembly Conference Abstracts.
Wieneke, S., Bastos, A., Barrios, J.M., Janssens, I., Balzarolo, M., 2021: Relationship between SIF and GPP at sub-seasonal time-scales from different satellites products. IGARSS 2021.