Vulnerability analyses in forests using AHP in a GIS environment

Year 2020, Volume: 8 Issue: 1, 40 - 48, 06.03.2020

Ceren Erdin Gündoğdu

https://doi.org/10.31195/ejejfs.653535

Abstract

Vulnerability, which is one of the criteria used in the preparation of the World Risk Index, is the measure of the damage and loss that a community or structure can suffer when a hazard occurs. In this research, a region with a high fire hazard was selected, and a model was created to determine the extent to which spatial objects (assets) could be damaged when the expected danger occurs in the selected region, using AHP in a GIS environment. Since GIS-based AHP analysis is based on the comparison of different layers with each other and determining the weight values of the layers, the Terrestrial Measurement, Photogrammetry and Remote Sensing techniques, which are used as data sources in the evaluation of spatial data, are also discussed in the study.

Keywords

GIS, QGIS, AHP, photogrammetry, forestry, remote sensing

References

• Campbell, J. B., Wynne, R. H. (2012). Introduction to Remote Sensing (5th ed.). New York, NY: Guilford Press. Ersoy, Ş., Nurlu, M., Gökçe, O., Özmen, B. (2017). 2016 Yılında Dünyada ve Türkiye’de Meydana Gelen Doğa Kaynaklı Afet Kayıplarının İstatistiksel Değerlendirmesi [Statistical Review of Natural Disaster Losses Occurred in the World and Turkey in 2016]. Mavi Gezegen, 22, 13-27.
• Ghilani, C. D., Wolf, P. R. (2011). Elementary Surveying: An Introduction to Geomatics (13th ed.). New Jersey: Prentice Hall.
• Kang, H., Xuxiang, L., Jingjing, W., Jing, Z. (2016). Evaluating Ecological Vulnerability Using the GIS and Analytic Hierarchy Process (AHP) Method in Yan’an, China. Polish Journal of Environmental Studies, 25(2), 599-605. doi: 10.15244/pjoes/61312
• Kennedy, M. D., Dangermond, J. (Foreword by) & Goodchild, M. F. (Afterword by) (2013). Introducing Geographic Information Systems with ArcGIS: A Workbook Approach to Learning GIS (3rd ed.). ‎Hoboken, NJ: Wiley.
• Lillesand, T., Kiefer, R. W., Chipman J. (2015). Remote Sensing and Image Interpretation (7th ed.). Hoboken, NJ: Wiley.
• Marin-Ferrer, M., Vernaccini, L., Poljansek, K. (2017). Index for Risk Management INFORM Concept and Methodology Report (Version 2017). Retrieved from https://op.europa.eu/en/publication-detail/-/publication/b1ef756c-5fbc-11e7-954d-01aa75ed71a1/language-en DOI: 10.2760/094023
• Nghiem, Q. H. (2015). GIS-based Spatial Multi-criteria Analysis: A vulnerability Assessment Model for the Protected Areas of Vietnam. GI_Forum 2015 - Journal for Geographic Information Science, 1(2015), 103-112. doi: 10.1553/giscience2015s103.
• Roach, C. (2017, November 7). How healthy is your GIS environment? [Blog post]. Retrieved from https://www.gaiaresources.com.au/how-healthy-is-your-gis-environment/
• Saaty, T. L. (1990). How to Make a Decision: The Analytic Hierarchy Process. European Journal of Operational Research, 48(1), 9-26. doi: 10.1016/0377-2217(90)90057-I
• Showalter, P. S., Lu, Y. (Eds.) (2009). Geospatial Techniques in Urban Hazard and Disaster Analysis (Geotechnologies and the Environment - Volume 2). Dordrecht, Netherlands: Springer Netherlands. doi: 10.1007/978-90-481-2238-7 Standards Australia (1999). AS/NZS 4360:1999 Risk Management. Sydney: Standards Australia.
• Van Oosterom P., Zlatanova S., Fendel, E. (Eds.) (2005). Geo-information for Disaster Management. Heidelberg, Berlin: Springer.
• Yurtseven, H., Akgul, M., Coban S., Gulci, S. (2019). Determination and Accuracy Analysis of Individual Tree Crown Parameters Using UAV Based Imagery and OBIA Techniques. Measurement, 145, 651-664. doi: 10.1016/j.measurement.2019.05.092