[Baldocchi, D., Hicks, B., Meyers, T. 1988. Measuring biosphere-atmosphere exchanges of biologically related gases with micrometeorological methods. - Ecology, 69, 1331-1340.]Search in Google Scholar
[Baret, F., Pavageau, P, Beal, D., Weiss, M., Berthelot, B., Regner, P. 2006. Algorithm Theoretical Basis Document for MERIS Top of Atmosphere Vegetation Land Products (TOA_VEG), version 3. ESA.]Search in Google Scholar
[Buck, A.L. 1981. New equations for computing vapour pressure and enhancement factor. - Journal of Applied Meteorology, 20, 1527-1532.]Search in Google Scholar
[Eenmäe, A., Nilson, T., Lang, M. 2011. A note on meteorological variables related trends in the MODIS NPP product for Estonia. - Forestry Studies / Metsanduslikud Uurimused, 55, 58-61.]Search in Google Scholar
[Frolking, S.E., Bubier, J.L. et al. 1998. Relationship between ecosystem productivity and photosynthetically active radiation for northern peatlands. - Global Biogeochemical Cycles, 12(1),115-126.]Search in Google Scholar
[Gobron, N., Aussedat, O., Pinty, B., Taberner, M., Verstraete, M. 2004. Medium Resolution Imaging Spectrometer (MERIS). Level 2 Land Surface Products. - Algorithm Theoretical Basis Document. Institute of Environmental Sustainability JRC, Publication No. EUR 21387 EN.]Search in Google Scholar
[Heinsch, F.A. et al. 2003. - User’s guide. GPP and NPP (MOD17A2/A3) products. NASA MODIS land algorithm. Version 2.0.]Search in Google Scholar
[Hordo, M., Metslaid, S. and Kiviste, A. 2009. Response Scots pine (Pinus sylvestris L.) radial growth to climate factors in Estonia. - Baltic Forestry 15(2), 195-205.]Search in Google Scholar
[Hordo, M., Henttonen, H., Helama, S., Mäkinen, H. and Kiviste, A. 2011. Annual growth variation of Scots pine in Estonia and Finland. - Baltic Forestry 17 (1), 35-49.]Search in Google Scholar
[Jönsson, P., Eklundh, L. 2002. Seasonality extraction by function fitting to time series of satellite sensor data. - IEEE Transactions on Geoscience and Remote Sensing, Vol. 40, pp. 1824−1832, ISSN 0196-2892.]Search in Google Scholar
[Kim, Y. Il, Kang, S., Kim J. 2007. Enhancing the reliability of MODIS gross primary productivity (GPP) by improving input data. - Korean Journal of Agricultural and Forest Meteorology, 9(2),132-139.]Search in Google Scholar
[Luhamaa, A., Kimmel, K., Männik, A., Rõõm, R. 2011. High resolution re-analysis for the Baltic Sea region during 1965-2005 period. - Climate Dynamics, 36:727-738. DOI 10.1007/s00382-010-0842-y.10.1007/s00382-010-0842-y]Search in Google Scholar
[Metsa korraldamise juhend. 2006. - RTL. 21.12.2006, 1684. Lisa 12. (In Estonian).]Search in Google Scholar
[Monteith, J. 1972. Solar radiation and productivity in tropical ecosystems. - Journal of Applied Ecology, 9, 747-76610.2307/2401901]Search in Google Scholar
[Monteith, J. 1977. Climate and effieciency of crop production in Britain. - Philosophical Transactions of the Royal Society of London. Ser. B, 277-294.]Search in Google Scholar
[MODIS, 2012. [WWW document]. - URL https://lpdaac.usgs.gov/products/modis_products_table/ mod17a3. [Accessed May 17, 2012]. ]Search in Google Scholar
[Huang, N., Niu, Z., Wu, C., Tappert, M.C. 2010. Modeling net primary production of a fast-growing forest using a light use efficiency model. - Ecological Modelling, 221, 2938-2948.]Search in Google Scholar
[Olofsson, P., Eklundh, L., Lagergren, F., Jönsson, P., Lindroth, A. 2007. Estimating net primary production for Scandinavian forest using data from Terra/MODIS. - Advances in Space Research, 39,125-130.]Search in Google Scholar
[Rinn, F. 2003. TSAP-Win. Time Series Analysis and Presentation for Dendrochronology and Related Applications. User Reference, Heidelberg, 91 p.]Search in Google Scholar
[Schwalm, C.R., et al. 2010. A model-data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis. - Journal of Geophysical Research, 115, G00H05, doi:10.1029/2009JG001229.10.1029/2009JG001229]Search in Google Scholar
[Seixas, J., Carvalhais, N., Nunes, C., Benali, A. 2009. Comparative analysis of MODIS-FAPAR and MERIS-MGVI datasets: Potential impacts on ecosystem modeling. - Remote Sensing of Environment, 113(12), 2547-2559.]Search in Google Scholar
[Statistical Yearbook of Estonia, 2013. - ISSN 1406-1783, ISBN 978-9985-74-526-7; 440pp. - URL http:// www.stat.ee/65374.]Search in Google Scholar
[Turner, D.P., Ollinger, S., Smith, M.-L., Krankina, O., Gregory, M. 2004. Scaling net primary production to a MODIS footprint in support of Earth observing system product validation. - International Journal of Remote Sensing, 25(10), 1961-1979.]Search in Google Scholar
[United Nations Framework Convention on Climate Change. Kyoto Protocol, 2012. [WWW document]. - URL http://unfccc.int/kyoto_protocol/items2830.php. [Accessed May 17, 2013].]Search in Google Scholar
[Vaus, M. 2005. Metsatakseerimine (Forest mensuration). Tartu, OÜ Halo Kirjastus, 178 pp. (In Estonian).]Search in Google Scholar
[Xiao, X.M., Hollinger, D., Aber, J., Goltz, M., Davidson, E.A., Zhang, Q.Y., Moore, B., 2004. Satellite-based modeling of gross primary production in an evergreen needleleaf forest. - Remote Sensing of Environment, 89, 519-534.10.1016/j.rse.2003.11.008]Search in Google Scholar
[Yearbook Forest. 2009. [WWW document]. - URL http://www.keskkonnainfo.ee/publications/16337_PDF.pdf.]Search in Google Scholar
[Zhao, M., Heinsch, F.A., Nemani, R.R., Running, S.W. 2005. Improvements of the MODIS terrestrial gross and net primary production global dataset. - Remote Sensing of Environment, 95, 164-176.]Search in Google Scholar
[Zhao, M., Running, S. 2010. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. - Science, 329, 940-943.]Search in Google Scholar
[Zhao, M., Running, S. 2010a. Supporting online material for: Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. - Science, 329, 940-943. Doi:10.1126/ science.1192666.]Search in Google Scholar
[Zhao, M., Running, S., Heinsch, F.A., Nemani, M. 2011. Ch 28. Modis-derived terrestrial primary production. - Ramachandran, B. et al. (eds). Land Remote Sensing and Global Environmental Change. - Remote Sensing and Digital Image Processing 11. DOI 10.1007/978-1-4419-6749-7_28. Springer Science+Business Media, pp 635-660. ]Search in Google Scholar