Cite

Aber, J. D., Federer, C. A., 1992: A generalized, lumped-parameter model of photosynthesis, evapotranspi-ration and net primary production in temperate and boreal forest ecosystems. Oecologia, 92:463–474.10.1007/BF00317837Search in Google Scholar

Adelard, L., Boyer, H., Garde, F., Gatina, J.-C., 2000: A detailed weather data generator for building simulations. Energy and Buildings, 31:75–88.10.1016/S0378-7788(99)00009-2Search in Google Scholar

Aertsen, W., Kint, V., Muys, B., Van Orshoven, J., 2012: Effects of scale and scaling in predictive modelling of forest site productivity. Environmental Modelling & Software, 31:19–27.10.1016/j.envsoft.2011.11.012Search in Google Scholar

Allister, K. M., Harding, L. A., Vernon Cole, C., Parton, W. J., 1993: CENTURY Soil Organic Matter Model Environment. Available at: https://www2.nrel.colostate.edu/projects/century/MANUAL/html_manual/man96.html (accessed 12.8.18).Search in Google Scholar

Aschoff, T., Thies, M., Winterhalder, D., Kretschmer, U., Spiecker, H., 2004: Automatisierte Ableitung von forstlichen Inventurparametern aus terrestrischen Laserscannerdaten. 24. Wissenscgaftlich-Technische ahrestagung der DGPF 2004, Halle/saale, p. 341–348.Search in Google Scholar

Assmann, E., Franz, F., 1963: Vorläufige Fichten-Ertragstafel für Bayern. Institut für Ertragskunde der Forst-lichen Forschungsanstalt, München, 104 p.Search in Google Scholar

Auger, P., Lett, C., 2003: Integrative biology: linking levels of organization. Comptes Rendus Biologies, 326:517–522.10.1016/S1631-0691(03)00115-XSearch in Google Scholar

Biber, P., Borges, J. G., Moshammer, R., Barreiro, S., Botequim, B., Brodrechtová, Y. et al., 2015: How Sensitive Are Ecosystem Services in European Forest Landscapes to Silvicultural Treatment? Forests, 6:1666–1695.10.3390/f6051666Search in Google Scholar

Bienert, A., Scheller, S. T., 2008: Verfahren zur auto-matischen Bestimmung von Forstinventurparametern aus terrestrischen Laserscannerpunktwolken. 28. Wissenschaftlisch-Technische Jahrestagung der DGPF, p. 110–120.Search in Google Scholar

Blaschke, T., Tiede, D., Heurich, M., 2004: 3D-landscape metrics to modelling forest structure and diversity based on laser-scanning data. In: Thies, M., Koch, B., Spiecker, H.,Weinacker, H. (eds.): Laser Scanners for Forest and Landscape Assessment. Proceedings of the ISPRS Working Group VIII/2. Freiburg, Germany, October 3–6, 2004. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XXXVI, Part 8/W2, p. 129–132.Search in Google Scholar

Bohn, F. J., Frank, K., Huth, A., 2014.: Of climate and its resulting tree growth: Simulating the productivity of temperate forests. Ecological Modelling, 278:9–17.10.1016/j.ecolmodel.2014.01.021Search in Google Scholar

Botkin, D. B., Janak, J. F., Wallis, J. R., 1972: Some ecological consequences of a computer model of forest growth. Journal of Ecology, 60:849–872.10.2307/2258570Search in Google Scholar

Brandtberg, T., 1999: Automatic Individual Tree-Based Analysis of High Spatial Resolution Remotely Sensed Data, Acta Universitatis Agriculturae Sueciae, 16 p.Search in Google Scholar

Brandtberg, T., 2002: Individual tree-based species classification in high spatial resolution aerial images of forests using fuzzy sets. Fuzzy Sets and Systems, 132:371–387.10.1016/S0165-0114(02)00049-0Search in Google Scholar

Bruce, D., Mars, de, D. J., Reukema, D. C., 1977: Douglas-fir managed yield simulator: DFIT User’s Guide, USDA, Forest Serv. Gen. Techn. Report PNW-57, PNW Forest and Range Experimental Station, Portland, OR., 2 p.Search in Google Scholar

Brunner, A., 1998: A light model for spatially explicit forest stand models. Forest Ecology and Management, 107:19–46.10.1016/S0378-1127(97)00325-3Search in Google Scholar

Buckley, D. J., Ulbricht, C., Berry, J., 1998: The Virtual Forest: Advanced 3-D Visualization Techniques for Forest Managament and Research. ESRI, Proceedings GIS’98, 15 p.Search in Google Scholar

Bugmann, H. K. M., 1994. On the ecology of mountainous forests in a changing climate: a simulation study (Doctoral Thesis). ETH Zurich.Search in Google Scholar

Bugmann, H., 1996: A simplified forest model to study species composition along climate gradients, Ecology, 77:2055–2074.10.2307/2265700Search in Google Scholar

Bugmann, H., Grote, R., Lasch, P., Lindner, M., Sukkow, F., 1997: A New Forest Gap Model to Study the Effects of Environmental Change on Forest Structure and Functioning. Impacts of Global Change on Tree Physiology and Forest Ecosystems, p. 255–261.10.1007/978-94-015-8949-9_33Search in Google Scholar

Bugmann, H., Lindner, M., Lasch, P., Flechsig, M., Ebert, B., Cramer, W., 2000: Scaling issues in forest succession modelling. Climatic Change, 44:265–289.10.1023/A:1005603011956Search in Google Scholar

Buongiorno, J., 2001: Generalization of Faustmanns formula for stochastic forest growth and prices with Markov decision process models. Forest Science, 47:466–474.Search in Google Scholar

Burkhart, H. E., Tomé, M., 2012: Modeling Forest trees and planter stands. Springer, 457 p.10.1007/978-90-481-3170-9Search in Google Scholar

Campbell, G. S., 1986: Extinction coefficients for radiation in plant canopies calculated using an ellipsoidal inclination angle distribution. Agricultural and Forest Meteorology, 36:317–321.10.1016/0168-1923(86)90010-9Search in Google Scholar

Campbell, G. S., 1990: Derivation of an angle density function for canopies with ellipsoidal leaf angle distribution. Agricultural and Forest Meteorology, 49:173–176.10.1016/0168-1923(90)90030-ASearch in Google Scholar

Černý, M., Bukša, I., 2005: Field-Map – Advanced measurement technology for forest management, nature conservation and landscaping. In: Conference proceedings, International anniversary scientific conference devoted to the 75th anniversary of Ukrainian forestry research institute founding, 30 – 31 March 2005, Kharkov, Ukraine, p. 84–85.Search in Google Scholar

Clark, M. L., Clark, D. B., Roberts, D. A., 2004: Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape. Remote Sensing of Environment, 91:68–89.10.1016/j.rse.2004.02.008Search in Google Scholar

Clemence, B. S. E., 1997: A brief assessment of a weather data generator (CLIMGEN) at Southern African sites. Short Communication. Water SA, 23:271–274.Search in Google Scholar

Clutter, J. L., 1963: Compatible growth and yield models for loblolly pine. Forest Science, 9:354–371.Search in Google Scholar

Collalti, A., Perugini, L., Santini, M., Chiti, T., Nolè, A., Matteucci, G., Valentini, R., 2014. A process-based model to simulate growth in forests with complex structure: Evaluation and use of 3D-CMCC Forest Ecosystem Model in a deciduous forest in Central Italy. Ecological Modelling, 272:362–378.10.1016/j.ecolmodel.2013.09.016Search in Google Scholar

Cornea, 2017: Webpage of CORNEA CAVE system at KAUST Visualization Core Lab (King Abdullah University of Science and Technology). Available at: http://kvl.kaust.edu.sa/Pages/cornea.aspx 2017, [accessed March 8, 2017].Search in Google Scholar

Cruz-Neira, C., Sandin, D. J., DeFanti, T. A., 1993: Surround-screen projection-based virtual reality: the design and implementation of the CAVE. In: Proceedings of the 20th annual conference on Computer graphics and interactive techniques. ACM SIGGRAPH, p. 135–142.10.1145/166117.166134Search in Google Scholar

Cruz-Neira, C., Sandin, D. J., DeFanti, T. A., Kenyon, R. V., Hart, J. C., 1992: The CAVE: audio visual experience automatic virtual environment. Communications of the ACM, 35:64–72.10.1145/129888.129892Search in Google Scholar

Cyberith, 2017: CYBERITH GmbH webpage–Cyberith Virtualizer product description. Available at: http://cyberith.com/ 2017, [accessed March 8, 2017].Search in Google Scholar

de Willigen, P., 1991. Nitrogen turnover in the soil-crop system; comparison of fourteen simulation models. Fertilizer Research, 27:141–149.10.1007/978-94-011-3434-7_1Search in Google Scholar

Dealle, K., Rudemo, M., 1997: Automatic estimation of individual tree positions from aerial photos. Canadian Journal of Forest Research, 27:1728–1736.10.1139/x97-130Search in Google Scholar

Deckmyn, G., Verbeeck, H., Op de Beeck, M., Vans-teenkiste, D., Steppe, K., Ceulemans, R., 2008. ANA-FORE: A stand-scale process-based forest model that includes wood tissue development and labile carbon storage in trees. Ecological Modelling, 215:345–368.10.1016/j.ecolmodel.2008.04.007Search in Google Scholar

DeFanti, T. A., Acevedo, D., Ainsworth, R. A., Brown, M. D., Cutchin, S., Dawe, G.et al., 2011: The future of the CAVE. Central European Journal of Engineering, 1:16–37.10.2478/s13531-010-0002-5Search in Google Scholar

DeFanti, T. A., Dawe, G., Sandin, D. J., Schulze, J. P., Otto, P., Girado, J. et al., 2009: The StarCAVE, a third-generation CAVE and virtual reality OptIPortal. Future Generation Computer Systems, 25:169–178.10.1016/j.future.2008.07.015Search in Google Scholar

Dieckmann, U., Law, R., Metz, J. A. J., 2000: The geometry of ecological interactions: Simplifying spatial complexity, Cambridge University Press, Cambridge, 564 p.10.1017/CBO9780511525537Search in Google Scholar

Donatelli, M., Bellocchi, G., Habyarimana, E., Bregaglio, S., Confalonieri, R., Baruth, B., 2009: CLIMA: a weather generator framework. In: 18th World IMACS / MODSIM Congress, Cairns, Australia, 13–17 July 2009, Avaiable at: http://mssanz.org.au/modsim09.Search in Google Scholar

Dubrovský, M., 1997: Creating daily weather series with use of the weather generator. Environmetrics, 8:409–424.10.1002/(SICI)1099-095X(199709/10)8:5<409::AID-ENV261>3.0.CO;2-0Search in Google Scholar

Dufour-Kowalski S., Courbaud B., Dreyfus P., Meredieu C., de Coligny F., 2012. Capsis: an open software framework and community for forest growth modelling. Annals of Forest Science, 69:221–233.10.1007/s13595-011-0140-9Search in Google Scholar

Dufrêne, E., Davi, H., François, C., Maire, G. le, Dantec, V.L., Granier, A., 2005. Modelling carbon and water cycles in a beech forest. Ecological Modelling, 185:407–436.10.1016/j.ecolmodel.2005.01.004Search in Google Scholar

Eckersten, H., Jansson, P.-E., 1991. Modelling water flow, nitrogen uptake and production for wheat. Fertilizer Research, 27:313–329.10.1007/978-94-011-3434-7_16Search in Google Scholar

Ek, A. R., Monserud, R. A., 1974: Trials with program FOREST: Growth and reproduction simulation for mixed species even- or uneven-aged forest stands. In: Fries, J. (Hrsg.): Growth models for tree and stand simulation. Royal College of Forestry, Stockholm, Sweden, Research Notes, 30:56–73.Search in Google Scholar

Fabrika, M., 2005: Simulátor biodynamiky lesa SIBYLA. Koncepcia, konštrukcia a programové riešenie. Habilitačná práca, Technická univerzita vo Zvolene, 238 p.Search in Google Scholar

Fabrika, M., Ďurský, J., 2005: Algorithms and software solution of thinning models for SIBYLA growth simulator. Journal of Forest Science, 51:431–445.10.17221/4577-JFSSearch in Google Scholar

Fabrika, M., Ďurský, J., 2006: Implementing Tree Growth Models in Slovakia. In: Hasenauer, H. (Ed.), Sustainable Forest Management: Growth Models for Europe. Springer Berlin Heidelberg, Berlin, Heidelberg, p. 315–341.10.1007/3-540-31304-4_19Search in Google Scholar

Fabrika, M., Pretzsch, H., 2013: Forest Ecosystem Analysis and Modelling. Technical University in Zvolen, 619 p.Search in Google Scholar

Fan, Y., Roupsard, O., Bernoux, M., Le Maire, G., Panferov, O., Kotowska, M.M., Knohl, A., 2015. A sub-canopy structure for simulating oil palm in the Community Land Model (CLM-Palm): phenology, allocation and yield. Geoscientific Model Development, 8:3785–3800.10.5194/gmd-8-3785-2015Search in Google Scholar

Febretti, A., Nishimoto, A., Thigpen, T., Talandis, J., Long, L., Pirtle, J. D. et al., 2013: CAVE2: A Hybrid Reality Environment for Immersive Simulation and Information Analysis. In: IS&T/SPIE Electronic Imaging. International Society for Optics and Photonics, p. 864903-864903-12.10.1117/12.2005484Search in Google Scholar

Fernandes, K. J., Raja, V., Eyre, J., 2003: Immersive learning system for manufacturing industries. Computers in Industry, 51:31–40.10.1016/S0166-3615(03)00027-7Search in Google Scholar

Fox, T. R., Allen, L., Wynne, R. H., Blinn, Ch. E., 2008: Precision Silviculture in the 21st Century: Linking GIS and Remote Sensing to Develop Site Specific Silvicultural Regimes in Southern Pine Plantations, In: Bettinger, P., Merry, K., Frei, S., Drake, J., Nibbelink, Heinstall, (eds.): Proceedings of the 6th Southern Forestry and Natural Resources GIS Conference. Warner School of Forestry and Natural Resources, University of Georgia, Athens.Search in Google Scholar

Franc, A., Gourlet-Fleury, S., Picard, N., 2000: Une Introduction á la Modélisation des Forêts Hétérogènes. ENGREF, Nancy, France.Search in Google Scholar

Franz, F., 1968: das EDV-Programm STAOET – zur Herleitung mehrgliedriger Standort-Leistungstafeln. Manuskriptdruck, München unveröff.Search in Google Scholar

Gadow, von K., 1987: Untersuchungen zur Konstruktion von Wuchsmodellen für schnellwüchsige Plan-tagenbaumarten. Forstliche Forschungsber. Mün-chen, No. 77, 147 p.Search in Google Scholar

Geng S., Auburn, J., Brandstetter, E., Li, B., 1988: A Program to Simulate Meteorological Variables. Documentation for SIMMETEO. (Agronomy Report No. 204). University of California, Davis Crop Extension, Davis, California.Search in Google Scholar

Geng, S., Penning De Vries, F. W. T., Supit, I., 1986: A simple method for generating daily rainfall data. Agricultural and Forest Meteorology, 36:363–376.10.1016/0168-1923(86)90014-6Search in Google Scholar

Gitelson, A. A., Kaufman, Y. J., Stark, R., Rundquist, D., 2002: Novel algorithm for remote estimation of vegetation fraction. Remote Sensing of Environment, 80: 76–87.10.1016/S0034-4257(01)00289-9Search in Google Scholar

Gougeon, F. A., 1995: A crown following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images. Canadian Journal of Remote Sensing, 21:274–284.10.1080/07038992.1995.10874622Search in Google Scholar

Grote, R., 1998. Integrating dynamic morphological properties into forest growth modelling. Forest Ecology and Management, 111:193–210.10.1016/S0378-1127(98)00328-4Search in Google Scholar

Grote, R., Kiese, R., Grünwald, T., Ourcival, J.-M., Granier, A., 2011. Modelling forest carbon balances considering tree mortality and removal. Agricultural and Forest Meteorology, 151:179–190.10.1016/j.agrformet.2010.10.002Search in Google Scholar

Grote, R., Pretzsch, H., 2002. A Model for Individual Tree Development Based on Physiological Processes. Plant Biology, 4:167–180.10.1055/s-2002-25743Search in Google Scholar

Grote, R., Pretzsch, H., 2002: A model for individual tree development based on physiological processes. Plant Biology, 4:167–180.10.1055/s-2002-25743Search in Google Scholar

Grote, R., Reiter, I.M., 2004. Competition-dependent modelling of foliage biomass in forest stands. Trees, 18.10.1007/s00468-004-0352-9Search in Google Scholar

Guillemot, J., Francois, C., Hmimina, G., Dufrêne, E., Martin-StPaul, N. K. et al., 2016: Environmental control of carbon allocation matters for modelling forest growth. New Phytologist, 214:180–193.10.1111/nph.14320Search in Google Scholar

Halaj, et al., 1987: Rastové tabuľky hlavných drevín ČSSR. Bratislava, Príroda, 361 p.Search in Google Scholar

Hamilton, G., Christie, J. M., 1973: Construction and application of stand yield tables. British For. Com. Res. and Developm. Paper, London, No. 96, 14 p.Search in Google Scholar

Hansen, J. W., Mavromatis, T., 2001: Correcting low-frequency variability bias in stochastic weather generators. Agricultural and Forest Meteorology, 109:297–310.10.1016/S0168-1923(01)00271-4Search in Google Scholar

Harding, D. J., Lefsky, M. A., Parker, G. G., Blair, J. B., 2001: Laser altimetry canopy height profiles methods and validation for closed-canopy, broadleaf forests. Remote Sensing of Environment, 76:283–297.10.1016/S0034-4257(00)00210-8Search in Google Scholar

Hauhs, M., Kastner-Maersch, A., Rost-Siebert, K., 1995: A model relating forest growth to ecosystem-scale budgets of energy and nutrients. Ecological Modelling, 83:229–243.10.1016/0304-3800(95)00101-ZSearch in Google Scholar

Hayhoe, H. N., 2000: Improvements of stochastic weather data generators for diverse climates. Climate Research, 14:75–87.10.3354/cr014075Search in Google Scholar

Heurich, M., Schneider, T., Kennel, E., 2003: Laser Scanning for Identification of Forest Structures in the Bavarian Forest National Park. In: Hyyppä, Naesset, Olsson, Pahlen, Reese (eds.): Proceedings of the Scandlaser Scientific Workshop on Airborne Laser Scanning of Forests., p. 97–106.Search in Google Scholar

Heurich, M., Perssson, A., Holmgren, J., Kennel, E., 2004: Detecting and measuring individual trees with laser scanning in mixed mountain forest of Central Europe using an algorithm developed for Swedish boreal forest conditions. International Archives Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVI:307–312.Search in Google Scholar

Hidy, D., Barcza, Z., Marjanović, H., Ostrogović Sever, M.Z., Dobor, L., Gelybó, G. et al., 2016. Terrestrial Ecosystem Process Model Biome-BGCMuSo: Summary of improvements and new modeling possibilities. Geoscientific Model Development Discussions, p. 1–60.10.5194/gmd-2016-93Search in Google Scholar

Holdridge, L. R., 1947: Determination of World Plant Formations from Simple Climatic Data. Science, 105: 367–369.10.1126/science.105.2727.367Search in Google Scholar

Holmgren, J., Persson, Å., 2004: Identifying species of individual trees using airborne laser scanner. Remote Sensing of Environment, 90:415–423.10.1016/S0034-4257(03)00140-8Search in Google Scholar

Hopkinson, C., Chasmer, L., Young-Pow, C., Treitz, P., 2004: Assesing forest metrics with a ground-based scanning lidar. Canadian Journal of Forest Research, 34:573–583.10.1139/x03-225Search in Google Scholar

Houllier, F., 1995: A propos des modèles de la dynamique des peuplements hétérogènes structures, processus démographiques et mécanismes de regulation. Revue d‘Écologie, 50: 273–282.10.3406/revec.1995.2177Search in Google Scholar

Hurtt, G. C., Moorcroft, P. R., Pacala, S. W., 2013: Ecosystem Demography Model: Scaling Vegetation Dynamics Across South America.Search in Google Scholar

Huth, R, Mládek, R., Metelka, L., Sedlák, P., Huthová, Z., Kliegerová, S. et al., 2003: On the integrability of limited-area numerical weather prediction model ALADIN over extended time periods. Studia Geophysica et Geodaetica, 47:863–873.10.1023/A:1026351004242Search in Google Scholar

Jansson, P.-E., Karlberg, L., 2004: Coupled heat and mass transfer model for soil-plant-atmosphere systems. Royal Institute of Technology, Department of Civil and Environmental Engineering.Search in Google Scholar

Jonard, M., André, F., 2018: Heterofor [Capsis] [WWW Document]. URL http://capsis.cirad.fr/capsis/help_en/heterofor (accessed 12.8.18).Search in Google Scholar

Jones, P. G., Thornton, P. K., 2000: MarkSim: software to generate daily weather data for Latin America and Africa. Agronomy Journal, 92:445–453.10.2134/agronj2000.923445xSearch in Google Scholar

Kahn, M., 1994: Modellierung der Höhenentwicklung ausgewählter Baumarten in Abhängigkeit vom Stan-dort. Forstliche Forschungsber. München, Vol. 141, 221 p.Search in Google Scholar

Karjalainen, E., Tyrväinen, L., 2002: Visualization in forst lanscape preference reaearch: a Finnish perspective. Lanscape and Urban Planning, 59:13–28.10.1016/S0169-2046(01)00244-4Search in Google Scholar

Keenan, T., Niinemets, Ü., Sabate, S., Gracia, C., Peñuelas, J., 2009. Process based inventory of isoprenoid emissions from European forests: model comparisons, current knowledge and uncertainties. Atmospheric Chemistry and Physics, 9: 4053–4076.10.5194/acp-9-4053-2009Search in Google Scholar

Kimmins, H., Blanco, J. A., Seely, B., Welham, C., Scoullar, K., 2010: Forecasting Forest Futures – A Hybrid Modelling Approach to the Assessment of Sustainability of Forest Ecosystems and Their Values. New York, Earthscan, 304 p.Search in Google Scholar

King, A. W., 1991: Translating models across scales in the landscape. In: Turner, M. G., Gardner, R. H. (eds.). Quantitative methods in landscape ecology: the analysis and interpretation of landscape heterogeneity, New York, Springer, Vol. 82, p. 470–517.10.1007/978-1-4757-4244-2_19Search in Google Scholar

Klemmt, H. J., Tauber, R., 2008: Automatisierte Ermittlung forstinventurrelevanter Parameter aus 3D-Laserscanning-Daten sowie aus 2D-DendroScandaten – Eine vergleichende Feldstudie. In: DVFFA – Sektion Ertragskunde, Jahrestagung 2008, Trippstadt, 5.–8. Mai 2008, p. 169–179.Search in Google Scholar

Kniemeyer, O., 2008: Design and Implementation of a Graph Grammar Based Language for Functional-Structural Plant Modelling. Dissertation. Fakultät für Mathematik, Naturwissenschaften und Informatik der Brandenburgischen Technischen Universität Cottbus, 432 p.Search in Google Scholar

Koreň, M., Mokroš, M., Bucha, T., 2017: Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods. International Journal of Applied Earth Observation and Geoinformation, 63:122–128.10.1016/j.jag.2017.07.015Search in Google Scholar

Kramer, K., Buiteveld, J., Forstreuter, M., Geburek, T., Leonardi, S., Menozzi, P. et al., 2008: Bridging the gap between ecophysiological and genetic knowledge to assess the adaptive potential of European beech. Ecological Modelling, 216:333–353.10.1016/j.ecolmodel.2008.05.004Search in Google Scholar

Kramer, K., van der Werf, B., Schelhaas, M. J., 2015: Bring in the genes: genetic-ecophysiological modeling of the adaptive response of trees to environmental change. With application to the annual cycle. Frontiers in Plant Science, 5:742.10.3389/fpls.2014.00742429223325628628Search in Google Scholar

Kramer, K., van der Werf, D. C., 2010: Equilibrium and non-equilibrium concepts in forest genetic modelling: population- and individually-based approaches. Forest Systems, 19:100–112.10.5424/fs/201019S-9312Search in Google Scholar

Kurth, W., 1994: Growth Grammar Interpreter GROGRA 2.4: A software tool for 3-dimensional interpretation of stochastic, sensitive growth grammars in the context of plant modelling. Intoduction and Reference Manual. Berichte des Forsungszentrums Waldökosysteme der Universität Göttingen, Ser. B, Vol. 38, 192 p.Search in Google Scholar

Kurth, W., 1999: Die Simulation der Baumarchitektur mit Wachstumsgrammatiken. Wissenschaftlicher Verlag Berlin, 327 p.Search in Google Scholar

Landsberg, J., Sands, P., 2011: Physiological Ecology of Forest Production, Principles, Processes and Models, Volume 4 in the Terrestrial Ecology Series. Elsevier Inc., 331 p.10.1016/B978-0-12-374460-9.00001-9Search in Google Scholar

Landsberg, J. J., Waring, R. H., 1997: A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management, 95:209–228.10.1016/S0378-1127(97)00026-1Search in Google Scholar

Lembcke, G., Knapp, E., Dittmar, O., 1975: Die neue DDR-Kiefernertragstafel 1975. Beiträge für die Forstwirtschaft, 15:55–64.Search in Google Scholar

Lexer, M. J., Hönninger, K., 2001: A modified 3D-patch model for spatially explicit simulation of vegetation composition in heterogeneous landscapes. Forest Ecology and Management, 144:43–65.10.1016/S0378-1127(00)00386-8Search in Google Scholar

Liang, X., Kankare, V., Hyyppä, J., Wang, Y., Kukko, A., Haggrén, H. et al., 2016. Terrestrial laser scanning in forest inventories. ISPRS Journal of Photogrammetry and Remote Sensing, 115:63–77.10.1016/j.isprsjprs.2016.01.006Search in Google Scholar

Lim, K., Treitz, P., Wulder, M., St-Onge, B., Flood, M., 2003: LIDAR remote sensing of forest structure. Progress in Physical Geography, 27:88–106.10.1191/0309133303pp360raSearch in Google Scholar

Lischke, H., 2001: New developments in forest modeling: convergence between applied and theoretical approaches. Natural Ressource Modeling, 14:71–102.10.1111/j.1939-7445.2001.tb00051.xSearch in Google Scholar

Lischke, H., Löffler, Th. J., Thornton, P. E., Zimmer-mann, N. E., 2006: Model up-scaling in landscape research. In: Kienast et al. (eds): A Changing World. Challenges for Landscape Research, p. 259–282.10.1007/978-1-4020-4436-6_16Search in Google Scholar

Lischke, H., Zimmermann, N. E., Bolliger, J., Ricke-busch, S., Löffler, T. J., 2006: TreeMig: A forest-landscape model for simulating spatio-temporal patterns from stand to landscape scale. Ecological Modelling, 199:409–420.10.1016/j.ecolmodel.2005.11.046Search in Google Scholar

Liu, J. G., Ashton, P.S., 1998: FORMOSAIC: An Individual Based, Spatially Explicit Model for Simulating Forest. In: Dynamics in Landscape Mosaics, Ecological Modelling, p. 106–177.10.1016/S0304-3800(97)00191-9Search in Google Scholar

Loustau, D., 2010. Forests, Carbon Cycle and Climate Change. Editions Quae.10.35690/978-2-7592-0385-7Search in Google Scholar

Loustau, D., Bosc, A., Colin, A., Ogee, J., Davi, H., Francois, C. et al., 2005: Modeling climate change effects on the potential production of French plains forests at the sub-regional level. Tree Physiology, 25:813–823.10.1093/treephys/25.7.813Search in Google Scholar

Magnussen, S., Boudewyn, P., 1998: Derivations of stand heights from airborne laser scanner data with canopy-based quantile estimators. Canadian Journal of Forest Research, 28:1016–1031.10.1139/x98-078Search in Google Scholar

McCaskill, M. R., 1990: TAMSIM—a program for preparing meteorological records for weather driven models. Tropical Agronomy Technical Memorandum, No. 65.Search in Google Scholar

McGaughey, R. J., 1997: Visualizing forest stand dynamics using the stand visualization system. In: Seattle, W. A., Bethesda, D: Proceedings of the 1997, ACSM/ASPRS Annual Convention and Exposition; April 7–10, 1997. American Society for Photogrammetry and Remote Sensing, 4:248–257.Search in Google Scholar

Medvigy, D., Wofsy, S. C., Munger, J. W., Hollinger, D. Y., Moorcroft, P. R., 2009: Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2. Journal of Geophysical Research-Biogeosciences, 114 p.10.1029/2008JG000812Search in Google Scholar

Merganič, J., Sterba, H., 2006: Characterisation of diameter distribution using the Weibull function: method of moments. European Journal of Forest Research, 125:427–439.10.1007/s10342-006-0138-2Search in Google Scholar

Merrill, S., 2009: KAUST: Visualization beyond the CAVE. Available at: http://techcrunch.com/2009/09/22/kaust-visualization-beyond-the-cave/ September 22, 2009, [accessed March 8, 2017].Search in Google Scholar

Mikita, T., Janata, P., Surový, P., 2016. Forest stand inventory based on combined aerial and terrestrial close-range photogrammetry. Forests, 7: 1–14.10.3390/f7080165Search in Google Scholar

Mohan, M., Silva, A. C., Klauberg, C., Jat, P., Catts, G., Cardil, A. et al., 2017: Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest. For.10.3390/f8090340Search in Google Scholar

Mokroš, M., Liang, X., Surový, P., Valent, P., Černňava, J., Chudý, F. et al., 2018a: Evaluation of Close-Range Photogrammetry Image Collection Methods for Estimating Tree Diameters. ISPRS International Journal of Geo-Information, 7:1–13.10.3390/ijgi7030093Search in Google Scholar

Mokroš, M., Výbošťok, J., Tomaštík, J., Grznárová, A., Valent, P., Slávik, M., Merganič J., 2018b: High Precision Individual Tree Diameter and Perimeter Estimation from Close-Range Photogrammetry. Forests, 9:1–12.10.3390/f9110696Search in Google Scholar

Moser, J. W., 1974: A system of equations for the components of forest growth. In: Fries, J. (Hrsg.): Growth models for tree and stand simulation. Royal College of Forestry, Stockholm, Sweden, Research Notes, No. 30, 397 p.Search in Google Scholar

Munro, D. D., 1974: Forest growth-models: A prognosis. In: Fries, J. (ed.): Growth models for tree and stand simulation. Royal College of orestry Res Notes, 30, Stockholm, p. 7–21.Search in Google Scholar

Nagel, J., 1996: Anwendungsprogramm zur Bestandesbewertung und zur Prognose der Bestandesentwicklung. Forst und Holz, 3:76–78.Search in Google Scholar

Nagel, J., Biging, G. S., 1995: Schätzung der Parameter der Weibullfunktion zur Generierung von Durchmesserverteilungen. Allgemeine Forst- und Jagdzeitung, 166:185–189.Search in Google Scholar

Naudts, K., Ryder, J., McGrath, M. J., Otto, J., Chen, Y., Valade, A. et al., 2015: A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes. Geoscientific Model Development, 8:2035–2065.10.5194/gmd-8-2035-2015Search in Google Scholar

Oculus, 2017: Oculus Rift – Virtual Reality Headset for 3D Gaming | Oculus VR® webpage–product description. Available at: http://oculus.com/ 2017, [accessed March 8, 2017].Search in Google Scholar

Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Levis, S. et al., 2013: Technical Description of version 4.5 of the Community Land Model (CLM), 434 p.Search in Google Scholar

Orland, B., (ed.), 1992: Data Visualization Techniques in Environmental Managament. Special Issue, Landscape Urban Planning, 21:237–319.10.1016/0169-2046(92)90030-4Search in Google Scholar

Orland, B., 1997: Final Report: SmartForest. Part II. Forest visual modeling for forest pest management and planning. USDA Forest Service, FPM-FHTET, State and Private Forestry, Washington, DC.Search in Google Scholar

Parton, W. J., Schimel, D. S., Cole, C. V., Ojima, D. S., 1987: Analysis of Factors Controlling Soil Organic Matter Levels in Great Plains Grasslands 1. Soil Science Society of America Journal, 51:1173–1179.10.2136/sssaj1987.03615995005100050015xSearch in Google Scholar

Persson, Å., Holmgren, J., Söderman, U., 2002: Detecting and measuring individual trees using an airborne laser scanner. Photogrammetric Engineering & Remote Sensing, 68:925–932.Search in Google Scholar

Perttunen, J., Sievänen, R., Nikinmaa, E., 1998: LIGNUM: a model combining the structure and the functioning of trees. Ecological Modelling, 108:189–198.10.1016/S0304-3800(98)00028-3Search in Google Scholar

Pfeifer, N., Gorte, B., Winterhalder, D., 2004: Automatic reconstruction of single trees from terrestrial laser scanner data, ISPRS – International Archie-ves of Photogrammetry, Remote Sensing and Spatial informatik Sciebce. Vol. XXXV, Part B: 114–119.Search in Google Scholar

Pfreundt, J., 1988: Modellierung der räumlichen Verteilung von Strahlung, Photosynthesekapazität und Produktion in einem Fichtebestand und ihre Bezie-hung zur Bestandesstruktur. Dissertation, Universität Göttingen, 163 p.Search in Google Scholar

Polhemus, 2017: POLHEMUS innovation to motionTM webpage–Electromagnetic motion tracking systems. Available at: http://polhemus.com/ 2017, [accessed March 8, 2017].Search in Google Scholar

Pommerening, A., 1999: Methoden zur Reproduktion und Forstschreibung einzelner konzentrischer Proberkreise von Betriebs- und Landeswaldinventuren. In DVFF – Sektion Ertragskunde, Volpriehausen.Search in Google Scholar

Pommerening, A., Biber, P., Stoyan, D., Pretzsch, H., 2000: Neue Methoden zur Analyse und Charakterisierung von Bestandesstrukturen. Photogrammetric Engineering & Remote Sensing, 119 p.10.1007/BF02769127Search in Google Scholar

Popescu, S.,Wynne, R. H., Nelson, R. F., 2002: Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size. Computers and Electronics in Agriculture, 37:71–95.10.1016/S0168-1699(02)00121-7Search in Google Scholar

Porte, A., Bartelink, H. H., 2002: Modelling mixed forest growth a review of models for forest management. Ecological Modelling, 150:141–188.10.1016/S0304-3800(01)00476-8Search in Google Scholar

Prentice, I. C., Cramer, W., Harrison, S. P., Leemans, R., Monserud, R. A., Solomon, A. M., 1992: A global biome model based on plant physiology and dominance, soil properties and climate. Journal of Biogeography, 19:117–143.10.2307/2845499Search in Google Scholar

Pretzsch, H., 1997: Analysis and modeling of spatial stand structures. Methodological considerations based on mixed beech-larch stands in Lower Saxony, Forest Ecology Management, 97:237–253.10.1016/S0378-1127(97)00069-8Search in Google Scholar

Pretzsch, H., 2001: Modellierung des Waldwachstums. Parey Buchverlag Berlin, 341 p.Search in Google Scholar

Pretzsch, H., 2009: Forest Dynamics, Growth and Yield. From Measurement to Model. Springer, 664 p.10.1007/978-3-540-88307-4Search in Google Scholar

Pretzsch, H., Biber, P., Ďurský, J., 2002: The single tree-based stand simulator SILVA: construction, application and evaluation, Forest Ecology and Management, 162:3–21.10.1016/S0378-1127(02)00047-6Search in Google Scholar

Pretzsch, H., Grote, R., Reineking, B., Rötzer, T. H., Seifert, S. T., 2007: Models for forest ecosystem management: a European perspective. Annals of Botany, 101:1065–1087.10.1093/aob/mcm246271027817954471Search in Google Scholar

Prusinkiewicz, P., Lindenmayer, A., 1990: The Algorithmic Beauty of Platns. Springer-Verlag, New York, 228 p.10.1007/978-1-4613-8476-2Search in Google Scholar

Puliti, S., Gobakken, T., Ørka, H.O., Næsset, E., 2017. Assessing 3D point clouds from aerial photographs for species-specific forest inventories. Scandinavian Journal of Educational Research, 32:68–79.10.1080/02827581.2016.1186727Search in Google Scholar

Rastetter, E. B., King, A. W., Cosby, B. J., Hornberger, G. M., Oneill, R. V., Hobbie, J. E., 1992: Aggregating Fine-Scale Ecological Knowledge to Model Coarser-Scale Attributes of Ecosystems. Ecological Applications, 2:55–70.10.2307/194188927759192Search in Google Scholar

Richardson, C.W., Wright, D. A., 1984: WGEN: a model for generating daily weather variables. U.S. Department of Agriculture, Agricultural Research Service, ARS-8, Washington, D.C, USA.Search in Google Scholar

Rötzer, T., Leuchner, M., Nunn, A. J., 2010: Simulating stand climate, phenology, and photosynthesis of a forest stand with a process-based growth model. International Journal of Biometeorology, 54:449–464.10.1007/s00484-009-0298-020084520Search in Google Scholar

Rötzer, T., Seifert, T., Gayler, S., Priesack, E., Pretzsch, H., 2012. Effects of Stress and Defence Allocation on Tree Growth: Simulation Results at the Individual and Stand Level. In: Matyssek, R., Schnyder, H., Oßwald, W., Ernst, D., Munch, J. C., Pretzsch, Hans (eds.), Growth and Defence in Plants: Resource Allocation at Multiple Scales, Ecological Studies. Springer Berlin Heidelberg, Berlin, Heidelberg, p. 401–432.10.1007/978-3-642-30645-7_18Search in Google Scholar

Rötzer, T., Seifert, T., Pretzsch, H., 2009: Modelling above and below ground carbon dynamics in a mixed beech and spruce stand influenced by climate. European Journal of Forest Ressearch, 128:171–182.10.1007/s10342-008-0213-ySearch in Google Scholar

Running, S., Hunt, E., 1993. Generalization of a Forest Ecosystem Process Model for Other Biomes, BIOMEBCG, and an Application for Global-Scale Models. Scaling Physiological Processes: Leaf to Globe: A volume in Physiological Ecology, p. 141–158.10.1016/B978-0-12-233440-5.50014-2Search in Google Scholar

Scheller, R., Hua, D., Bolstad, P., A. Birdsey, R., Mladenoff, D., 2011: The effects of forest harvest intensity in combination with wind disturbance on carbon dynamics in Lake States Mesic Forests, 222:144–153.10.1016/j.ecolmodel.2010.09.009Search in Google Scholar

Schmidt, A., 1971: Wachstum und Ertrag der Kiefer auf wirtshaftlich wichtigen Standorteinheiten der Oberpfalz. Forstliche Forschungsber. München, Bd. 1, 178 p.Search in Google Scholar

Seidl, R., Baier, P., Rammer, W., Schopf, A., Lexer, M. J., 2007: Modelling tree mortality by bark beetle infestation in Norway spruce forests. Ecological Modelling, 206:383–399.10.1016/j.ecolmodel.2007.04.002Search in Google Scholar

Seidl, R., Lexer, M. J., Jäger, D., Hönninger, K., 2005: Evaluating the accuracy and generality of a hybrid patch model. Tree Physiology, 25:939–951.10.1093/treephys/25.7.93915870060Search in Google Scholar

Seidl, R., Rammer, W., Bellos, P., Hochbichler, E., Lexer, M. J., 2009: Testing generalized allometries in allocation modeling within an individual-based simulation framework. Trees, 24:139–150.10.1007/s00468-009-0387-zSearch in Google Scholar

Seidl, R., Rammer, W., Scheller, R. M., Spies, T. A., 2012: An individual-based process model to simulate landscape-scale forest ecosystem dynamics. Ecological Modelling, 231:87–100.10.1016/j.ecolmodel.2012.02.015Search in Google Scholar

Seidl, R., Thom, D., Kautz, M., Martin-Benito, D., Peltoniemi, M., Vacchiano, G. et al., 2017: Forest disturbances under climate change. Nature Climate Change, 7:395.10.1038/nclimate3303557264128861124Search in Google Scholar

Semenov, M. A., Brooks, R. J., Barrow, E. M., Richardson, C. W., 1998: Comparison of WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Resourses, 10:95–107.10.3354/cr010095Search in Google Scholar

Shinozaki, K., Yoda, K., Hozumi, K., Kira, T., 1964: A Quantitative analysis of plant form-the pipe model theory: i. Basic analyses. Japanese Journal of Ecology, 14:97–105.Search in Google Scholar

Shugart, H. H., 1984: A Theory of Forest Dynamics. The Ecological Implications of Forest Succesion Models. Springer-Verlag New York, Berlin, Heidelberg, Tokio, 278 p.Search in Google Scholar

Shugart, H. H., West, D. C., 1977: Development of an Appalachian deciduous forest succesion model and its application to assessment of the impact of the chestnut blight. Journal of Environmental Management, 5:161–179.Search in Google Scholar

Sievänen, R., Perttunen, J., Nikinmaa, E., Kaitaniemi, P., 2008: Toward extension of a single tree functional–structural model of Scots pine to stand level: effect of the canopy of randomly distributed, identical trees on development of tree structure. Functional Plant Biology, 35:964–975.10.1071/FP0807732688846Search in Google Scholar

Simonse, M., Aachhoff, T., Spiecker, H., Thies, M., 2003: Automatic Determinantion of Forest inventory parameters using terrestrial laser scanning, Institute for Growth, Freiburg, ScandLaser scientific Workshop on Airborne Laser Scanning, p. 1–7.Search in Google Scholar

Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W. et al., 2003. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biology, 9:161–185.10.1046/j.1365-2486.2003.00569.xSearch in Google Scholar

Sloboda, B., 1976: Mathematische und stochastische Modelle zur Beschreibung der Statik und Dynamik von Bäumen und Beständen – insbesondere das bestandesspezifische Wachstum als stochasticher Prozeß. Habil.-Schrift, Univ. Freiburg, 310 p.Search in Google Scholar

Smith, B., Prentice, I. C., Sykes, M. T., 2001: Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecology and Biogeography, 10:621–637.10.1046/j.1466-822X.2001.t01-1-00256.xSearch in Google Scholar

Smith, B., Wårlind, D., Arneth, A., Hickler, T., Lead-ley, P., Siltberg, J., Zaehle, S., 2014: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences, 11:2027–2054.10.5194/bg-11-2027-2014Search in Google Scholar

Sodtke, R., Schmidt, M., Fabrika, M., Nagel, J., Ďurský, J., Pretzsch, H., 2004: Anwendung und Einsatz von Einzelbaummodellen als Komponenten von entscheidungsunterstützenden Systemen für die strategische Forstbetriebsplannung. Forstarchiv, 75:51–64.Search in Google Scholar

Sterba, H., 1995: PROGNAUS – ein absandsunabhängiger Wachstumssimulator für ungleichaltrige Mischbestände. DVFF – Sektion Ertragskunde, Joachimstahl, p. 173–183.Search in Google Scholar

Surový, P., Ribeiro, N., Oliveira, A. C., Scheer, Ľ., 2004: Discrimination of vegetation from the background in high resolution colour remote sensed imagery. Journal of Forest Science, 50:161–170.10.17221/4611-JFSSearch in Google Scholar

Suzuki, T., 1971: Forest transition as a stochastic process. Mitt. der Forstlichen Bundesversuchsanstalt Wien, 91:137–150.Search in Google Scholar

Svensson, M., Jansson, P.-E., Kleja, D. B., 2008. Modelling Soil C Sequestration in Spruce Forest Ecosystems along a Swedish Transect Based on Current Conditions. Biogeochemistry, 89:95–119.10.1007/s10533-007-9134-ySearch in Google Scholar

Thornton, P., Running, S. W., Hunt, E. R., 2005: Biome-BGC: Terrestrial Ecosystem Process Model, Version 4.1.1.Search in Google Scholar

Urban, D. L., 2005: Modeling ecological processes across scales. Ecology, 86:1996–2006.10.1890/04-0918Search in Google Scholar

Van Oijen, M., Rougier, J., Smith, R., 2005: Bayesian calibration of process-based forest models: bridging the gap between models and data. Tree Physiology, 25:915–927.10.1093/treephys/25.7.91515870058Search in Google Scholar

Vanclay, J. K., 1994: Modelling forest growth and yield (Application to mixed tropical forests). CAB International, Wallingford, UK, 312 p.Search in Google Scholar

Vicon Bonita, 2014: Vicon Motion Systems Ltd - Optical motion capture systems – webpage. Avaiable at: http://www.vicon.com/system/bonita 2014, [accessed November 9, 2014].Search in Google Scholar

Virtuix, 2017: Virtuix OmniTM webpage—product description. Available at: http://virtuix.com/ 2017, [accessed March 8, 2017].Search in Google Scholar

Virtusphere, 2017: ©Virtusphere, Inc. webpage. Virtusphere product description. Available at: http://www.virtusphere.com/index.html 2017, [accessed March 8, 2017].Search in Google Scholar

VRAC, 2008: Webpage of C-6 CAVE system at Virtual Reality Application Center (Iowa State University). Available at: http://www.vrac.iastate.edu/c6.php 2008, [accessed March 8, 2017].Search in Google Scholar

Vuokila, Y., 1966: Functions for variable density yield tables of pine based on temporary sample plots. Communicationes Instituti Forestalis Fenniae, 60: 86.Search in Google Scholar

Warnant, P., FrançOis, L., Strivay, D., GéRard, J.-C., 1994. CARAIB: A global model of terrestrial biological productivity. Global Biogeochemical Cycles 8: 255–270.10.1029/94GB00850Search in Google Scholar

Weiskittel, A. R., Hann, D. W., Kershaw, Jr., J. A., Van-clay, J. K., 2011: Forest Growth and Yield Modeling. Wiley-Blackwell, 415 p.10.1002/9781119998518Search in Google Scholar

Woodward, F. I., Smith, T. M., 1994: Predictions and Measurements of the Maximum Photosynthetic Rate at the Global Scale, In: Schulze, E. D., Caldwell, M. M. (eds.): Ecological Studies 100, Springer-Verlag, New York, p. 491–509.10.1007/978-3-642-79354-7_23Search in Google Scholar

Wykoff, W. R., Crookston, N. L., Stage, A. R., 1982: User’s Guide to the stand prognosis model. U. S. For. Serv., Gen. Techn. Rep. INT-133, Ogden, Utah, 112 p.10.5962/bhl.title.109367Search in Google Scholar

eISSN:
0323-1046
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Life Sciences, Plant Science, Ecology, other