[Adermann, V. 2009. Forests of Estonia. (Eesti Metsad 2008). Metsakaitse-ja Metsauuendus-keskus, Tallinn. (In Estonian).]Search in Google Scholar
[Bontemps, J.D., Bouriaud, O. 2014. Predictive approaches to forest site productivity: recent trends, challenges and future perspectives. – Forestry, 87, 109–128.10.1093/forestry/cpt034]Search in Google Scholar
[DeLucia, E.H., Drake, J.E., Thomas, R.B., Gonzalez-Meler, M. 2007. Forest carbon use efficiency: Is respiration a constant fraction of gross primary production? – Global Change Biology, 13, 1157–1167.10.1111/j.1365-2486.2007.01365.x]Open DOISearch in Google Scholar
[D’Odorico, P., Gonsamo, A., Pinty, B., Gobron, N., Coops, N., Mendez, E., Schaepman, M.E. 2014. Intercomparison of fraction of absorbed photosynthetically active radiation products derived from satellite data over Europe. – Remote Sensing of Environment, 142, 141–154.]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, 60–63.]Search in Google Scholar
[FAO, IIASA, ISRIC, ISS-CAS, JRC. 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.]Search in Google Scholar
[Finér, L., Ohashi, M., Noguchi, K., Hirano, Y. 2011. Fine root production and turnover in forest ecosystems in relation to stand and environmental characteristics. – Forest Ecology and Management, 262, 2008–2023.]Search in Google Scholar
[GFOI. 2013. Integrating remote-sensing and ground-based observations for estimation of emissions and removals of greenhouse gases in forests: Methods and Guidance from the Global Forest Observations Initiative: Pub: Group on Earth Observations, Geneva, Switzerland, 2014. ISBN 978-92-990047-4-6.]Search in Google Scholar
[Härkönen, S., Lehtonen, A., Eerikäinen, K., Peltoniemi, M., Mäkelä, A. 2011. Estimating forest carbon fluxes for large regions based on process-based modelling, NFI data and Landsat satellite images. – Forest Ecology and Management, 262, 2364–2377.]Search in Google Scholar
[Härkönen, S., Pulkkinen, M., Duursma, R., Mäkelä, A. 2010. Estimating annual GPP, NPP and stem growth in Finland using summary models. – Forest Ecology and Management, 259, 524–533.]Search in Google Scholar
[Härkönen, S., Tokola, T., Packalén, P., Korhonen, L., Mäkelä, A. 2013. Predicting forest growth based on airborne light detection and ranging data, climate data, and a simplified processbased model. – Canadian Journal of Forest Research, 43, 364–375.10.1139/cjfr-2012-0295]Open DOISearch in Google Scholar
[IDB. 2016. State register for accounting of forest resource. (Metsaressursi arvestuse riikliku registri põhimäärus). – Riigi Teataja, RT I, 12.01.2016, 2. (In Estonian).]Search in Google Scholar
[IPCC. 2006. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. – Eggelston. S., Buendia. L., Miwa. K., Ngara. T., Tanabe. K (eds.). Hayama: Institute of Global Environmental Strategies (IGES). Volume 4: Agriculture, Forestry and Other Land Use.]Search in Google Scholar
[IUSS Working Group WRB. 2014. World Reference Base for Soil Resources 2014. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. FAO, Rome.]Search in Google Scholar
[Kandare, K., Ørka, H.O., Dalponte, M., Næsset, E., Gobakken, T. 2017. Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data. – International Journal of Applied Earth Observation and Geoinformation, 60, 72–82.]Search in Google Scholar
[Kiviste, A., Hordo, M., Kangur, A., Kardakov, A., Laarmann, D., Lilleleht, A., Metslaid, S., Sims, A., Korjus, H. 2015. Monitoring and modeling of forest ecosystems: the Estonian Network of Forest Research Plots. – Forestry Studies / Metsanduslikud Uurimused, 62, 26–38.]Search in Google Scholar
[Kliimaatlas. 1970. Climate data in Estonia (Eesti NSV kliimaatlas). Eesti NSV Hüdrometeoroloogia teenistuse valitsus. Tallinn.]Search in Google Scholar
[Kõlli, R. 1988. Phytoproductivity of Estonian soils in forest land. – Почвоведение, 4, 96−107. (In Russian).]Search in Google Scholar
[Kõlli, R., Asi, E., Köster, T. 2004. Organic carbon pools in Estonian forest soils. – Baltic Forestry, 10(1), 19–26.]Search in Google Scholar
[Kõlli, R., Ellermäe, O., Köster, T., Lemetti, I., Asi, E., Kauer, K. 2009. Stocks of organic carbon in Estonian soils. – Estonian Journal of Earth Sciences, 58, 95–108.]Search in Google Scholar
[Kõlli, R., Kanal, A. 2010. The management and protection of soil cover: an ecosystem approach. – Forestry Studies / Metsanduslikud Uurimused, 53, 25–34.]Search in Google Scholar
[Kuusk, A., Kuusk, J., Lang, M. 2016. Albedo of the forested landscape at the SMEAR-Estonia research station. – Baltic Forestry, 22(2), 390−395.]Search in Google Scholar
[Lang, M., Traškovs, A., Gulbe, L. 2013. Assessment of NTSG MODIS NPP product for forests in Kurzeme region, Latvia. – Forestry Studies / Metsanduslikud Uurimused, 58, 26–36.]Search in Google Scholar
[Liu, C., Westman, C.J., Berg, B., Kutsch, W., Wang, G.Z., Man, R., Ilvesniemi, H. 2004. Variation in litterfall-climate relationships between coniferous and broadleaf forests in Eurasia. – Global Ecology and Biogeography, 13, 105–114.10.1111/j.1466-882X.2004.00072.x]Open DOISearch in Google Scholar
[Liu, J., Chen, J.M., Cihlar, J., Park, W.M. 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. – Remote Sensing of Environment, 62, 158–175.10.1016/S0034-4257(97)00089-8]Open DOISearch in Google Scholar
[Mäkelä, A., Valentine, H.T. 2001. The ratio of NPP to GPP: evidence of change over the course of stand development. – Tree Physiology, 21, 1015-1030.10.1093/treephys/21.14.101511560815]Open DOISearch in Google Scholar
[Makkonen, K., Helmisaari, H.S. 2001. Fine root biomass and production in Scots pine stands in relation to stand age. – Tree Physiology, 21, 193–198.10.1093/treephys/21.2-3.19311303650]Open DOISearch in Google Scholar
[Metsakorralduse. 2017. Forest inventory act. (Metsa korraldamise juhend). – RT I, 22.02. 2017, 11. (In Estonian).10.17851/1982-0739.22.2.312-314]Search in Google Scholar
[Moreno, A., Hasenauer, H. 2016. Spatial down-scaling of European climate data. – International Journal of Climatology, 36, 1444–1458.10.1002/joc.4436]Open DOISearch in Google Scholar
[Moreno, M., Neumann, M., Hasenauer, H. 2016. Optimal resolution for linking remotely sensed and forest inventory data in Europe. – Remote Sensing of Environment, 183, 109–119.]Search in Google Scholar
[Mullakaardi. 2001. The fine-scale map of Estonian soils. (Vabariigi digitaalse suuremõõtkavalise mullastiku kaardi seletuskiri). Maa-amet, Tallinn. [WWW document]. – http://geoportaal.maaamet.ee/est/Andmed-jakaardid/Mullastiku-kaart-p33.html [Accessed 16 April 2016]. (In Estonian).]Search in Google Scholar
[Neumann, M., Moreno, A., Thurnher, C., Mues, V., Härkönen, S., Mura, M., Bouriaud, O., Lang, M., Cardellini, G., Thivolle-Cazat, A., Bronisz, K., Merganic, J., Alberdi, I., Astrup, R., Mohren, F., Zhao, M., Hasenauer, H. 2016. Creating a regional MODIS satellite-driven net primary production dataset for European forests. – Remote Sensing, 8(7), 554, doi:10.3390/rs8070554.10.3390/rs8070554]Open DOISearch in Google Scholar
[Neumann, M., Mues, V., Moreno, A., Hasenauer, H., Seidl, R. 2017. Climate variability drives recent tree mortality in Europe. Global Change Biology, 00, 1–10, https://doi.org/10.1111/gcb.13724 (In press).10.1111/gcb.13724()]Open DOISearch in Google Scholar
[Nilson, T., Rennel, M., Luhamaa, A., Hordo, M., Olesk, A., Lang, M. 2012. MERIS GPP/NPP product for Estonia: I. Algorithm and preliminary results of simulation. – Forestry Studies / Metsanduslikud Uurimused, 56, 56–78.]Search in Google Scholar
[Noe, S.M., Niinemets, Ü., Krasnova, A., Krasnov, D., Motallebi, A., Kängsepp, V., Jõgiste, K., Hõrrak, U., Komsaare, K., Mirme, S., Vana, M., Tammet, H., Bäck, J., Vesala, T., Kulmala, M., Petäjä, T., Kangur, A. 2015. SMEAR Estonia: Perspectives of a large-scale forest ecosystem – atmosphere research infrastructure. – Forestry Studies / Metsanduslikud Uurimused, 63, 56–84.]Search in Google Scholar
[Olofsson, P., Eklundh, L., Lagergren, F., Jonsson, P., Lindroth, A. 2007. Estimating net primary production for Scandinavian forests using data from Terra/MODIS. – Advances in Space Research, 39, 125–130.]Search in Google Scholar
[Olson, R.J., Johnson, K.R., Zheng, D.L., Scurlock, J.M.O. 2001. Global and regional ecosystem modeling: Databases of model drivers and validation measurements. Oakridge Laboratory: Oak Ridge, TN, USA.10.2172/814241]Search in Google Scholar
[Ostonen, I., Lõhmus, K., Pajuste, K. 2005. Fine root biomass, production and its proportion of NPP in a fertile middle-aged Norway spruce forest: Comparison of soil core and ingrowth core methods. – Forest Ecology and Management, 212, 264–277.10.1016/j.foreco.2005.03.064]Search in Google Scholar
[Quaife, T., Quegan, S., Disney, M., Lewis, P., Lomas, M., Woodward F.I. 2008. Impact of land cover uncertainties on estimates of biospheric carbon fluxes. – Global Biogeochemical Cycles, 22, 1–12.10.1029/2007GB003097]Open DOISearch in Google Scholar
[Raich, J.W., Nadelhoffer, K.J. 1989. Belowground carbon allocation in forest ecosystems: global trends. – Ecology, 70, 1346–1354.10.2307/1938194]Open DOISearch in Google Scholar
[Raudsaar, M., Pärt, E., Adermann, V. 2016. Forest resources. In: Yearbook Forest 2014. Tallinn, Keskkonnaagentuur. 1–61.]Search in Google Scholar
[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.]Search in Google Scholar
[Sims, A., Mändma, R., Laarmann, D., Korjus, H. 2014. Assessment of tree mortality on the Estonian Network of Forest Research Plots. – Forestry Studies / Metsanduslikud Uurimused, 60, 57–68.]Search in Google Scholar
[Stagakis, S., Markos, N., Vanikiotis, T., Tzotsos, A., Sykioti, O., Kyparissis, A. 2015. sCASE: A primary productivity monitoring system for the forests of North Pindus National Park (Epirus, Greece). – European Journal of Remote Sensing, 48, 223–243.]Search in Google Scholar
[Tan, B., Woodcock, C.E, Hu, J., Zhang, P., Ozdogan, M., Huang, D., Yang, W., Knyazikhin, Y., Myneni, R.B. 2006. The impact of gridding artifacts on the local spatial properties of MODIS data: Implications for validation, compositing, and band-to-band registration across resolutions. – Remote Sensing of Environment, 105, 98–114.10.1016/j.rse.2006.06.008]Open DOISearch in Google Scholar
[Tang, J., Luyssaert, S., Richardson, A.D., Kutsch, W., Janssens, I.A. 2014. Steeper declines in forest photosynthesis than respiration explain age-driven decreases in forest growth. – Proceedings of the National Academy of Sciences, 111, 8856–8860.]Search in Google Scholar
[Tomppo, E., Gschwantner, T., Lawrence, M., McRoberts, R. 2010. National Forest Inventories: Pathways for common reporting. Springer: Berlin, Germany.10.1007/978-90-481-3233-1]Search in Google Scholar
[Tooming, H. 1977. Solar radiation and yield formation. Gidrometeoizdat, Leningrad, Russia.]Search in Google Scholar
[Turner, D.P., Ritts, W.D., Cohen, W.B., Gower, S.T., Running, S.W., Zhao, M., Costa, M.H., Kirschbaum, A.A., Ham, J.M., Saleska, S.R., Ahl, D.E. 2006. Evaluation of MODIS NPP and GPP products across multiple biomes. – Remote Sensing of Environment, 102, 282–292.10.1016/j.rse.2006.02.017]Open DOISearch in Google Scholar
[Vanninen, P., Mäkelä, A. 1999. Fine root biomass of Scots pine stands differing in age and soil fertility in southern Finland. – Tree Physiology, 19, 823–830.10.1093/treephys/19.12.82310562399]Open DOISearch in Google Scholar
[Varik, M., Aosaar, J., Uri, V. 2009. Biomass production in silver birch stands in Oxalis site type. – Forestry Studies / Metsanduslikud Uurimused, 51, 5–16.]Search in Google Scholar
[Waring, R.H., Milner K.S., Jolly, W.M., Phillips, L., McWethy, D. 2006. Assessment of site index and forest growth capacity across the Pacific and Inland Northwest U.S.A. with a MODIS satellite-derived vegetation index. – Forest Ecology and Management, 228, 285–291.]Search in Google Scholar
[Xin, Q., Olofsson, P., Zhu, Z., Tan, B., Woodcock, C.E. 2013. Toward near real-time monitoring of forest disturbance by fusion of MODIS and Landsat data. – Remote Sensing of Environment, 135, 234–247.]Search in Google Scholar
[Yuan, Z.Y., Chen, H.Y.H. 2012a. Indirect methods produce higher estimates of fine root production and turnover rates than direct methods. – PLoS ONE 7(11): e48989. doi:10.1371/journal.pone.004898.]Search in Google Scholar
[Yuan, Z.Y., Chen, H.Y.H. 2012b. A global analysis of fine root production as affected by soil nitrogen and phosphorus. – Proceedings of the Royal Society B: Biological Sciences, 279, 3796–3802.]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 data set. – Remote Sensing of Environment, 95, 164–176.]Search in Google Scholar
[Zhao, M., Running S.W., Heinsch F.A., Nemani R.R. 2011. MODIS-derived terrestrial primary production. – Ramachandran, B., Justice, C.O., Abrams, M.J. (eds.). Land Remote Sensing and Global Environmental Change: NASA’s Earth Observing System and the Science of ASTER and MODIS. New York, Springer-Verlag, 635-660.]Search in Google Scholar
