1 |
Center for Global Environmental Research. 2011. National greenhouse gas inventory report of JAPAN. Ministry of the Environmental, Japan. pp. 41.
|
2 |
Dagpunar, J.S. 2007. Simulation and monte carlo. John Wiley and Sons. pp. 75.
|
3 |
Dieck, R.H. 2007. Measurement uncertainty methods and application. The instrumentation, systems, and automation society. pp. 39-62.
|
4 |
Fan, X., Felsovalyi, Á., Sivo, S.A., and Keenan, S.C. 2001. SAS for monte carlo studies: A guide for quantitative researchers. Cary, North Carolina: SAS Institute Incorporation. pp. 26-41.
|
5 |
Fujiwara. T., Yamashita, K., and Kuroda, K. 2007. Basic densities as a parameter for estimating the amount of carbon removal by forests and their variation. Bulletin of the Forestry and Forest Products Research Institute 6(4): 215-226.
|
6 |
Gertner, G. 1987. Approximating precision in simulation projections: An efficient alternative to monte carlo methods. Forest Science 33(1): 230-239.
|
7 |
Intergovernmental panel on climate change. 2000. Good practice guidance and uncertainty management in national greenhouse gas inventories. IPCC National Greenhouse Gas Inventory Programme. Institute for Global Environmental Strategies. pp. 6.1-6.23.
|
8 |
Intergovernmental panel on climate change. 2003. Good practice guidance for land use, land-use change and forestry. IPCC National Greenhouse Gas Inventory Programme. Institute for Global Environmental Strategies. pp. 5.8-5.9.
|
9 |
Intergovernmental panel on climate change. 2006a. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Volume 1. General Guidance and Reporting. IPCC National Greenhouse Gas Inventory Programme. Institute for Global Environmental Strategies. pp. 3.6-3.78.
|
10 |
Intergovernmental panel on climate change. 2006b. 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Volume 4. Agriculture, Forestry and Other Land Use. IPCC National Greenhouse Gas Inventory Programme. Institute for Global Environmental Strategies. pp. 4.73.
|
11 |
Jung, H.J. 2011. Sensitivity and uncertainty analysis of forest carbon stock changes in Korea. M.D. thesis, Graduate School of Public Health, Seoul National University. pp. 59.
|
12 |
Kalos, M.H. and Whitlock, P.A. 2008. Monte carlo methods, second, revised and enlarged edition. WILEY-VCH Verlag GmbH and Corporation, KGaA, Weinheim. pp. 9.
|
13 |
Kangas, A.S. and Kangas, J. 2004. Probability, possibility and evidence : approaches to consider risk and uncertainty in forestry decision analysis. Forest Policy and Economics 6: 169-188.
DOI
ScienceOn
|
14 |
Korea Forest Research Institute. 2010. The carbon emission factor of major species for national inventory by forestry in Korea. Korea Forest Research Institute. pp. 7.
|
15 |
Levy, P.E., Hale, S.E., and Nicoll, B.C. 2004. Biomass expansion factors and root:shoot ratios for coniferous tree species in Great Britain. Forestry 77(5): 421-430.
DOI
ScienceOn
|
16 |
Lehtonen, A., R. Makipaa, J. Heikkinen, R. Sievanen, and J. Liski. 2004. Biomass Expansion factor (BEFs) for Scotes pine, Norway spruce and birch according to stand age for boreal forests. Forest Ecology and Management 188: 211-224.
DOI
ScienceOn
|
17 |
Monte, L., Lars, H., Ulla, B., John, B., and Rudie, H. 1996. Uncertainty analysis and validation of environmental models : The empirically based uncertainty analysis. Ecological Modelling 91: 139-152.
DOI
ScienceOn
|
18 |
Ramirez, A., Keizer, C., Sluijs, J.P., and Olivier, J. 2008. Monte carlo analysis of uncertainties in the Netherlands greenhouse gas emission inventory for 1990-2004. Atmospheric Environment 42: 8263-8272.
DOI
ScienceOn
|
19 |
Monni, S., Peltoniemi, M., Palosuo, T., Lehtonen, A., Makipaa, R., and Savolainen, I. 2007. Uncertainty of forest carbon stock changes-implications to the total uncertainty of GHG inventory of Finland. Climate Change 81: 391-413.
DOI
|
20 |
Monni, S., Syri, S., and Savolainen, I. 2004. Uncertainties in the Finnish greenhouse gas emission inventory. Environmental Science and Policy 7: 87-98.
DOI
ScienceOn
|
21 |
Refsgaard, J.C., Jeroen, P.V.D.S., Anker, L.H., and Peter, A.V. 2007. Uncertainty in the environmental modelling process-A framework and guidance. Environmental Modelling and Software 22: 1543-1556.
DOI
ScienceOn
|
22 |
SAS Institute, Incorporation. 2012. SAS/STAT 9.3 User's Guide. SAS Institute, Incorporation. Cary. North Carolina. pp. 439.
|
23 |
Winiwarter, W. and Rypdal, K. 2001. Assessing the uncertainty associated with national greenhouse gas emission inventories: a case study for Austria. Atmospheric Environment 35: 5425-5440.
DOI
ScienceOn
|
24 |
Yanai, R.D., John, J.B., Andrew, D.R., Corrie, A.B., Dustin, M.W., and Edward, B.R. 2010. Estimating uncertainty in ecosystem stock calculations. Ecosystem 13: 239-248.
DOI
|