參考文獻 |
Adiyasuren, Ts. (1998). Environment and Development issues in Mongolia. Ulaanbaatar,
Mongolia: S.N press.
Ali, A.T., & Suresh, C. R. (2010). Land Cover Classification and Forest Change Analysis, Using
Satellite Imagery - A Case Study in Dehdez Area of Zagros Mountain in Iran. Journal of
Geographic Information system, 3, 1-11.
Amarsaikhan, D., Saandar, M., Battsengel, V. & Amarjargal, Sh. (2012). Forest resources study in
Mongolia using advanced spatial technologies. International Archives of the Photogrammetry,
RS and Spatial Information Sciences, 7, XXII ISPRS Congress, Melbourne, Australia.
Austin, M., (2002). Spatial prediction of species distribution: an interface between ecological
theory and statistical modelling. Ecological Modeling, 157, 101–118.
Banzragch, N., Scott, G., & Clyde, E.G. (2006). Trends in extreme daily precipitation and
temperature near lake Hövsgöl, Mongolia. International Journal of Climatology, 27, 341-347.
Breiman, L. (2001). Random forests. Machine Learning, 45, 5–32.
Carleer, A., & Wolff, E. (2004). Exploitation of Very High Resolution Satellite Data for Tree
Species Identification. Photogrammetric Engineering and Remote Sensing, 70(1), 135-140.
Charles, T. S & Jeffrey, H. G. (2002). Encyclopedia of Environmetrics, volume 2. Ed by Abdel, H.
E., &Walter, W. P. Forest inventory 2, 814-820.
Chimidnyam, D. (2010). Global Forest Resources Assessment, Mongolia, Country progress report:
Recommendation for harmonization and standardization of MAR terms. Ulaanbaatar,
Mongolia.
Congalton, R.G. (1995). A Review of Assessing the Accuracy of Classifications of
Remotely Sensed Data. Remote Sensing of Environment, 37, 35-46.
Congalton, R.G. & Green, K. (1999). Assessing the Accuracy of Remotely Sensed Data:
Principles and Practices, Lewis Publishers, Florida.
Congalton, R.G., Oderwald, R.G., & Mead, R.A., (1983). Assessing Landsat Classification
Accuracy Using Discrete Multivariate Analysis Statistical Techniques. Photogrammetric
Engineering and Remote Sensing, 49, 1671-1678.
Corsi, F., De Leeuw, J., Skidmore, A. (2000). Modeling species distribution with GIS. In: Boitani,
L., Fuller, T. (Eds.). Research Techniques in Animal Ecology: Controversies and
consequences, 389–434. New York, Columbia University Press.
65
Duda, R.O., Hart, P.E., & Stork, D.G. (2000). Pattern Classification (2nd ed). New York, USA.
Dud´ık, M., Phillips, S.J., Schapire, R.E. (2004). Performance guarantees for regularized maximum
entropy density estimation. In: Proceedings of the 17th Annual Conference on Computational
Learning Theory, 655– 662. New York, ACM Press.
Engler, R., Guisan, A., & Rechsteiner, L. (2004). An improved approach for predicting the
distribution of rare and endangered species from occurrence and pseudo-absence data. Journal
of Applied Ecology, 41, 263–274.
Fallah, A., Kalbi, S., & Shataee, S. (2013). Forest Stand Types Classification Using Tree-Based
Algorithms and SPOT-HRG Data. International Journal of Environmental Resources
Research, 1, 263-278.
Forest Law of Mongolia (FLM). (1995). Ulaanbaatar, Mongolia.
Frank, T.D. (1988). Mapping dominant vegetation communities in the Colorado Rocky Mountain
Front Range with Landsat Thematic Mapper and digital terrain data. Photogrammetric
Engineering and Remote Sensing, 54, 1727–1734.
Franklin, J. (1995). Predicting the distribution of shrub species in southern California from climate
and terrain-derived variables. Journal of vegetation Science, 9, 733- 748.
Ganbold, D., & Haliun D. (2000). Facts about Mongolia. Ulaanbaatar, Mongolia: Admon press.
Giles, M.F, Peter, M.A, Peter, W.G, Neil, A.R, & Colleen, K.K. (2004). Identification of specific
tree species in ancient semi-natural woodland from digital aerial sensor imagery. Ecological
Applications, 15, 1233–1244.
Guo, L., Chehata, N., Mallet, C., & Boukir, S. (2011). Relevance of airborne lidar and multispectral
image data for urban scene classification using Random Forests. ISPRS Journal of
Photogrammetry and Remote Sensing, 66, 56–66.
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data
Mining, Inference, and Prediction (2nd ed). New York, USA: Springer.
Hopkins, P.F., Maclean, A.L., & Lillesand, T.M. (1988). Assessment of Thematic Mapper imagery
for forestry applications under Lake States conditions. Photogrammetric Engineering and
Remote Sensing, 54(1), 61-68.
Hudak, A.T., Strand, E.K., Vierling, L.A., Byrne, J.C., Eitel, J.U.H., Martinuzzi, S., &
Falkowski, M.J. (2012). Quantifying aboveground forest carbon pools and fluxes from repeat
LiDARSurveys. Remote Sensing of Environment, 123, 25–40.
66
Gerelmaa, B. (2011). Community Forest Development in Mongolia. Country Reports for APFNet’s
Workshop on Community Forestry Development in the Context of Climate Change, Kunming
China, 24-48.
Hughes, G. (1968). On the mean accuracy of statistical pattern recognizers. IEEE Transaction on
Information Theory, 14, 55–63.
Jaynes, E.T. (1957). Information theory and statistical mechanics. The Physical Review, 106, 620–
630.
Irons, J.R., Markham, B.L., Nelson, R.F., Toll, D.L., & Williams, D.L. (1985). The effects of
spatial resolution on the classification of Thematic Mapper data. International Journal of
Remote Sensing, 6(8), 1385-1403.
Juwairia, M., Umar, K., & Mahboob, R. (2002). Forest tree species classification using
multispectral satellite imageries. International Journal of Remote Sensing, 26, 217–222.
Law of Mongolia on Land /Revised version/. (2002) Ulaanbaatar, Mongolia.
Lawrence, R.L., Wood, S.D., & Sheley, R.L. (2006). Mapping invasive plants using hyperspectral
imagery and Breiman Cutler classifications Remote Sensing of Environment, 100, 356–362.
Lennartz, S.P., & Congalton, R.G. (2004). Classifying and mapping forest cover types using Ikonos
imagery in the Northeastern United State. Proceedings of the Annual Meeting of American
Society of Photogrammetry and Remote Sensing, Denver.
Marco, P. (2007). Brief on National forest inventory, Mongolia. Forest Resources Development
Service.
Markus, I., Clement, A., & Tatjana, K. (2012). Tree Species Classification with Random Forest
Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data. Remote Sensing, 4,
2661-2693.
Martin, M. E., Newman, S.D., Aber, J.D., & Congalton, R.G. (1998). Determining Forest Species
Composition Using High Spectral Resolution Remote Sensing Data. Remote Sensing of
Environment, 65, 249–254.
Moore, M.M., & Bauer, M.E. (1990). Classification of forest vegetation in North-Central
Minnesota using Landsat Multispectral Scanner and Thematic Mapper data. Forest Science,
36(2), 330-342.
67
Mühlenberg, M., Appelfelder, J., Hoffmann, H., Ayush, E., & Wilson, K.J. (2012). Structure of the
montane taiga forests of West Khentii, Northern Mongolia. Journal of forest science, 58, 45-
56.
Nicholas, C., John, D., & Michael, M. (2004). Mongolia Forestry Sector Review. World Bank,
http://siteresources.worldbank.org/INTMONGOLIA/Resources/eng_version.pdf.
Nyamaa, M. (2001). Khövsgöl province guidebook, 219. Ulaanbaatar, Mongolia.
Nyamjav, B. (2007). The Forest Fire Situation in Mongolia. International Forest Fire News, 36,
46-66.
Phillips, S.J., Robert, P. A., & Robert, E. S. (2006). Maximum entropy modeling of species
geographic distributions. Ecological Modelling, 190, 231-259.
Punsalmaa, B. (2006). Climate Change Vulnerability and Adaptation in the Livestock sector of
Mongolia, A Final Report Submitted to Assessments of Impacts and Adaptations to Climate
Change (AIACC), Project No. AS 06.
Schriever, J.R., & Congalton, R.G. (1995). Evaluating seasonal variability as an aid to cover-type
mapping from Landsat Thematic Mapper data in the Northeast. Photogrammetric
Engineering and Remote Sensing, 61(3), 321- 327.
Shannon, C.E. (1948). A mathematical theory of communication. The Bell System Technical
Journal, 27, 379–423, 623–656.
Skidmore, A. K. (1989). An expert system classifies eucalypt types using Thematic Mapper data
and a digital terrain model. Photogrammetric Engineering and Remote Sensing, 55, 1449–
1464.
Stumpf, A., & Kerle, N. (2011). Object-oriented mapping of landslides using Random Forests.
Remote Sensing of Environment, 115, 2564–2577.
Suvdantsetseg, B., Tsolmon, R., & Fukui, H. (2012). Saxaul forest area determination by remote
sensing in Mongolia’s gobi desert. International Archives of the Photogrammetry, Remote
Sensing and Spatial Information Sciences, 37, 1081-1086.
Tsogtbaatar, J. (2007). Forest Policy Development in Mongolia. Geoecology Institute, Mongolian
Academy Sciences, Ulaanbaatar, Mongolia.
Tu, C. H., Lo, N. J., Chang, W., & Haung, K. Y. (2012). Evaluating the novel method on species
distribution modeling in complex forest. International Archives of the Photogrammetry, Remote
68
Sensing and Spatial Information Sciences, Volume XXXIX-B2, 2012 XXII ISPRS Congress,
Melbourne, Australia.
World Population Review. (2015). Mongolia Population 2015.
http://worldpopulationreview.com/countries/mongolia-population/
Ykhanbai, H. (2004). Final Technical Report of study project on: “Sustainable
Management of Common Natural Resources in Mongolia”. Ulaanbaatar, Mongolia.
Zhang, Z., & Liu, X. (2012). Terrain and canopy surface modelling from LiDAR data for tree
species classification. In: Symposium GIS Ostrava 2012: Surface Models for Geosciences,
Ostrava, Czech Republic.
Zhang, Z., Liu, X., & Wendy, W. (2012) Object-based image analysis for forest species |