DIGITALNA ARHIVA ŠUMARSKOG LISTA
prilagoğeno pretraživanje po punom tekstu




ŠUMARSKI LIST 3-4/2022 str. 52     <-- 52 -->        PDF

Change, 25(1), 69-100. https://doi.org/10.1111/j.1467-7660.1994.tb00510.x
Demir, M. 2007: Impacts, management and functional planning criterion of forest road network system in Turkey. Transportation Research Part A: Policy and Practice, 41(1), 56-68. https://doi.org/10.1016/j.tra.2006.05.006
Demir, G. 2018: Landslide susceptibility mapping by using statistical analysis in the North Anatolian Fault Zone (NAFZ) on the northern part of Suºehri Town, Turkey. Natural hazards, 92(1), 133-154. https://doi.org/10.1007/s11069-018-3195-1
Dorren, L. K., Berger, F., Imeson, A. C., Maier, B., Rey, F. 2004: Integrity, stability and management of protection forests in the European Alps. Forest ecology and management, 195(1-2), 165-176. https://doi.org/10.1016/j.foreco.2004.02.057
Dou, J., Yunus, A. P., Bui, D. T., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.W., Khosravi, K., Yang, Y. Pham, B. T. 2019: Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan. Science of the total environment, 662, 332-346. https://doi.org/10.1016/j.scitotenv.2019.01.221
Du, G. L., Zhang, Y. S., Iqbal, J., Yang, Z. H., Yao, X. 2017: Landslide susceptibility mapping using an integrated model of information value method and logistic regression in the Bailongjiang watershed, Gansu Province, China. Journal of Mountain Science, 14(2), 249-268. https://doi.org/10.1007/s11629-016-4126-9
Duman, T.Y., T. Çan ve Ö. Emre. 2011. 1/1.500.000 Türkiye Heyelan Envanteri Haritası, Maden Tetkik ve Arama Genel Müdürlüğü Özel Yayınlar Serisi -27, Ankara, Türkiye. ISBN:978-605-4075-85-3.
Eiras, C. G. S., de Souza, J. R. G., de Freitas, R. D. A., Barella, C. F., Pereira, T. M. 2021: Discriminant analysis as an efficient method for landslide susceptibility assessment in cities with the scarcity of predisposition data. Natural Hazards, 1-16. https://doi.org/10.1007/s11069-021-04638-4
Erdaº, O. 1997: Orman Yolları–Cilt I. KTÜ Orman Fakültesi Yayınları, 187, 25. (in Turkish)
ESRI. 2016: Cost Path. https://desktop.arcgis.com/en/arcmap/10.3/tools /spatial-analyst-toolbox/cost-path.htm. (02/06/2021)
Fallahchai, M. M., Haghverdi, K., Mojaddam, M. S. 2018: Ecological effects of forest roads on plant species diversity in Caspian forests of Iran. Acta Ecologica Sinica, 38(3), 255-261
GDF. 1984: Muhafaza Ormanlarının Ayrılması ve İdaresi Hakkında Yönetmelik. Türkiye Cumhuriyeti, Tarım ve Orman Bakanlığı, Orman Genel Müdürlüğü (General Directorate of Turkey) Tertip no:5 Resmi Gazete tarihi: 13.08.1984, Sayı: 18942. Ankara (in Turkish).
Gheshlaghi, H. A., Feizizadeh, B. 2021: GIS-based ensemble modelling of fuzzy system and bivariate statistics as a tool to improve the accuracy of landslide susceptibility mapping. Natural Hazards, 1-34. https://doi.org/10.1007/s11069-021-04673-1
Gumus, S., Acar, H. H., Toksoy, D. 2008: Functional forest road network planning by consideration of environmental impact assessment for wood harvesting. Environmental monitoring and assessment, 142(1), 109-116. https://doi.org/10.1007/s10661-007-9912-y
Haskell, D. G. 2000: Effects of forest roads on macroinvertebrate soil fauna of the southern Appalachian Mountains. Conservation Biology, 14(1), 57-63. https://doi.org/10.1046/j.1523-1739.2000.99232.x
Hayati, E., Majnounian, B., Abdi, E. 2012: Qualitative evaluation and optimization of forest road network to minimize total costs and environmental impacts. iForest-Biogeosciences and Forestry, 5(3), 121. https://doi.org/10.3832/ifor0610-009
Hong, H., Liu, J., Bui, D. T., Pradhan, B., Acharya, T. D., Pham, B. T., Zhu, A., Chen, W., Ahmad, B. B. 2018: Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China). Catena, 163, 399-413. https://doi.org/10.1016/j.catena.2018.01.005
Jenness, J. 2006: Topographic Position Index (TPI) v. 1.2. Jenness Enterprises. Retrieved May 7, 2021 from http://www.jennessent.com/downloads/tpi_documentation_online.pdf
Jesudasan, J. J., Saravanan, S. 2021: Artificial Neural Network and Sensitivity Analysis in the Landslide Susceptibility Mapping of Idukki District, India. Geocarto International, (just-accepted), 1-14. https://doi.org/10.1080/10106049.2021.1923831
Kadi, F., Yildirim, F., Saralioglu, E. 2019: Risk analysis of forest roads using landslide susceptibility maps and generation of the optimum forest road route: a case study in Macka, Turkey. Geocarto International, 1-18. https://doi.org/10.1080/10106049.2019.1659424
Kalantar, B., Pradhan, B., Naghibi, S. A., Motevalli, A., Mansor, S. 2018: Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN). Geomatics, Natural Hazards and Risk, 9(1), 49-69. https://doi.org/10.1080/19475705.2017.1407368
Kavzoglu, T., Colkesen, I., Sahin, E. K. 2019: Machine learning techniques in landslide susceptibility mapping: A survey and a case study. Landslides: Theory, practice and modelling, 283-301. https://doi.org/10.1007/978-3-319-77377-3_13
Kavzoglu, T., Sahin, E. K., Colkesen, I. 2015: An assessment of multivariate and bivariate approaches in landslide susceptibility mapping: a case study of Duzkoy district. Natural Hazards, 76(1), 471-496. https://doi.org/10.1007/s11069-014-1506-8
Lamsal, P. 2011: Protection forest: a new dimension for biodiversity conservation, sustainable forest management and livelihood improvement. The initiation, 4, 111-114. https://doi.org/10.3126/init.v4i0.5543
Laschi, A., Neri, F., Brachetti Montorselli, N., Marchi, E. 2016: A methodological approach exploiting modern techniques for forest road network planning. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering, 37(2), 319-331.
Li, Y., Chen, W. 2020: Landslide susceptibility evaluation using hybrid integration of evidential belief function and machine learning techniques. Water, 12(1), 113. https://doi.org/10.3390/w12010113
Liampas, S. A., Stamatiou, C., Drosos, V. 2019: Forest road network planning for biomass exploitation and fire preventions: a least cost path analysis. Agricultural Engineering International: CIGR Journal, 21(4), 33-42.
Massey, C. I., Townsend, D. T., Lukovic, B., Morgenstern, R., Jones, K., Rosser, B., de Vilder, S. 2020: Landslides triggered by