The increasing global mean air temperature and other climatic changes are driven by the increases of atmospheric greenhouse gas concentrations, of which carbon dioxide (CO2) is the most important anthropogenic. The atmospheric concentration is moderated by the exchange of CO₂ between the atmosphere and the biosphere; the net exchange is a result of photosynthesis that takes up and respiration that releases CO2. Satellite sensor-derived data are suitable for regional or global estimations of CO2 exchange. By using vegetation indices, like the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), as input data to light use efficiency (LUE) models and LUE-based empirical models, the photosynthetic uptake of CO2 has been estimated for several ecosystems in the Nordic countries, Sahel in Africa and Greenland. Since LUE models describe how radiation energy is converted into biomass, also the incoming photosynthetically active radiation that is absorbed by vegetation (APAR) is an essential input to these models. For some ecosystems, also respiratory release of CO2 has been estimated by driving exponential relationships with satellite sensor-derived land surface temperature. If both the uptake and release of CO2 are known, then the net exchange can be calculated. All models have been tested, calibrated and validated with eddy covariance tower measurements of CO2 exchange. Some current research interests are:
- Estimating the fraction of incoming photosynthetically active radiation absorbed by vegetation (FAPAR), in order to use it as input to LUE models or LUE-based empirical models for estimations of CO2 uptake.
- Describing vegetation structure, such as the leaf area index (LAI), in order to integrate it in process-oriented carbon models.
- Developing methods for handling time series of satellite sensor-derived data, in order to generate improved time series of these data.
- Using near-ground sensors for spectral measurements for calibration of satellite sensor-derived data and better understanding of ecosystem processes.
- Monitoring changes in vegetation cover in different climate regions and ecosystems.
We have published a number of articles related to carbon estimation, of which some are given here:
- Schubert P., Lagergren F., Aurela M., Christensen T., Grelle A., Heliasz M., Klemedtsson L., Lindroth A., Pilegaard K., Vesala T., Eklundh L., 2012, Modeling GPP in the Nordic forest landscape with MODIS time series data - comparison with the MODIS GPP product, Remote Sensing of Environment, 126, 136-147. http://dx.doi.org/10.1016/j.rse.2012.08.00
- Tagesson T., Mastepanov M., Tamstorf M.P., Eklundh L., Schubert P., Ekberg A., Sigsgaard C., Christensen T.R., Ström L., 2012, High-resolution satellite data reveal an increase in peak growing season gross primary production in a high-Arctic wet tundra ecosystem 1992-2008, International Journal of Applied Earth Observations and Geoinformation, 18, 407-416. http://dx.doi.org/10.1016/j.jag.2012.03.016
- Sjöström, M., Ardö, J., Arneth, A., Cappelaere, B., Eklundh, L., de Grandcourt, A., Kutsch, W. L., Merbold, L., Nouvellon, Y., Scholes, B., Seaquist, J. and Veenendaal, E. M., 2011, Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems. Remote Sensing of Environment, 115, 1081-1089. http://dx.doi.org/10.1016/j.rse.2010.12.013
- Schubert, P., Lund, M., Ström, L., and Eklundh, L., 2010, Impact of nutrients on peatland GPP estimations using MODIS time series data, Remote Sensing of Environment, 114, 2137-2145. http://dx.doi.org/10.1016/j.rse.2010.04.018
- Schubert, P., Eklundh, L., Lund, M. and Nilsson, M., 2010, Estimating northern peatland CO2 exchange from MODIS time series data, Remote Sensing of Environment, 114, 1178-1189. http://dx.doi.org/10.1016/j.rse.2010.01.005
- Sjöström M., Ardö J., Eklundh L., El-Tahir B.A., El-Khidir H.A.M., Pilesjö P. and Seaquist J., 2009, Evaluation of satellite based indices for primary production estimates in a sparse savanna in the Sudan. Biogeosciences, 6, 129-138. http://www.biogeosciences.net/6/129/2009/bg-6-129-2009.html
- Olofsson, P., Lagergren, F.,Lindroth, A., Lindström, J., Klemedtsson, L., Kutsch, W. and Eklundh, L., 2008, Towards Operational Remote Sensing of Forest Carbon Balance across Northern Europe. Biogeosciences, 5, 817-832. http://www.biogeosciences.net/5/817/2008/bg-5-817-2008.html
- Olofsson, P. and Eklundh, L.,2007, Estimation of absorbed PAR across Scandinavia from satellite measurements. Part II: modeling and evaluating the fractional absorption. Remote Sensing of Environment, 110, 240-251. http://dx.doi.org/10.1016/j.rse.2007.02.020
- Olofsson, P., Eklundh, L.,Lagergren, F., Jönsson, P. and Lindroth, A., 2007, Estimating Net Primary Production for Scandinavian forests using data from Terra/MODIS. Advances in Space Research, 39, 125-130. http://dx.doi.org/10.1016/j.asr.2006.02.031
- Olofsson, P., Van Laake, P. E. and Eklundh, L., 2007, Estimation of absorbed PAR across Scandinavia from satellite measurements. Part I: Incident PAR. Remote Sensing of Environment, 110, 252-261. http://dx.doi.org/10.1016/j.rse.2007.02.021
- Seaquist, J. W., Olsson, L., Ardö, J. and Eklundh, L., 2006, Broad-scale increase in NPP Quantified for the African Sahel, 1982-1999. International Journal of Remote Sensing, 27, 5115-5122.
- Eriksson, H., Eklundh, L., Hall,K. and Lindroth, A., 2005, Estimating leaf area index in deciduous forest stands. Agricultural and Forest Meteorology, 129, 27-37.
- Eklundh, L., Hall, K., Eriksson, H., Ardö, J. and Pilesjö, P., 2003, Investigating the use of LANDSAT Thematic Mapper data for estimation of forest leaf area index in southern Sweden. Canadian Journal of Remote Sensing, 29, 349-362.
- Eklundh, L., Harrie, L. and Kuusk, A., 2001, Investigating relationships between Landsat ETM+ sensor data and leaf area index in a boreal conifer forest. Remote Sensing of Environment, 78, 239-249.