Abstract
Soil erosion is one of the most important environmental problems. In the case of small scale areas where soil properties and climate have relatively uniform characteristics, vegetation cover and topography (i.e. ground slope) are the main factors that affect the amount of soil erosion. Lack of vegetation cover on bare soil areas, including forest road side slopes, especially in mountainous regions with steep slopes, may significantly increase the erosion rate. Determining and classifying erosion risks in such areas can help preventing environmental impacts. In this study, remotely sensed data and elevation data were used to extract and classify bare soil erosion risk areas for a study area selected from Hatila Valley Natural Protected Area in northeastern Turkey. High resolution IKONOS imagery was used to apply land use classification in ERDAS Imagine 9.0. To generate erosion risk map of the bare soil areas, classified image was superimposed on top of slope map, generated based on a Digital Elevation Model (DEM) in ArcGIS 9.2. The results indicated that 1.43, 5.85, 34.62, 53.16, and 4.94% of the bare soil areas in the study area were under very low, low, medium, high, and very high erosion risks, respectively. The overall classification accuracy of 82.5% indicated the potential of the proposed methodology.
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References
Abrams M (2003) The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER):data products for the high spatial resolution imager on NASA’s Terra platform. Int J Remote Sens 21:847–859
Akay AE (2007) Minimizing total costs of forest roads with computer-aided design model. Acad Proc Eng Sci 31:621–633
Akay AE, Sessions J (2005) Applying the decision support system, TRACER, to forest road design. West J Appl For 20:184–191
Akay AE, Erdas O, Reis M, Yuksel A (2008) Estimating sediment yield from a forest road network by using a sediment prediction model and GIS techniques. Build Environ 43:687–695
Baskaya S (2005) Distribution and principal threats to Caucasian Black Grouse Tetrao mlokosiewiczi in the Eastern Karadeniz Mountains in Turkey. Wildl Biol 9:377–383
Bojie F, Xilin W, Gulinck H (1995) Soil erosion types in the Loess Hill and Gully area of China. J Environ Sci Eng 7:266–272
CORINE (1992) Soil erosion risk and important land resources in the southeastern regions of the European community. EUR 13233, Luxembourg, Belgium. pp 32–48
Dai X, Guo Z, Zhang L, Li D (2009) Spatio-temporal exploratory analysis of urban surface temperature field in Shanghai, China. Stoch Environ Res Risk Assess. doi:10.1007/s00477-009-0314-2
Fannin R J, Lorbach J (2007) Guide to forest raod engineering in mountainous terrain. Forest Harvesting and Engineering Working Paper 2, FAO, Rome
GDREC (2008) General Directorate of Reforestation and Erosion Control. http://www.agm.gov.tr. Accessed 8 Jan 2008
Gucinski H, Furniss MJ, Ziemer RR, Brookes MH (2000) Forest roads: a synthesis of scientific information. USDA Forest Service
Huang O, Cai Y (2007) Simulation of land use change using GIS-based stochastic model: the case study of Shiqian County, Southwestern China. Stoch Env Res Risk Assess 21:419–426
Jinren RN, Yingkui KL (2003) Approach to soil erosion assessment in terms of land-use structure changes. J Soil Water Conserv 58:158–169
Lal R (1994) Soil erosion research method, 2nd edn. Soil and Water Conservation Society, Ankeny, IA, USA, p 352
Lal R (1998) Soil erosion at multiple scales: principles and methods for assessing causes and impacts. CAB International Publishing, Wallingford
Masoudi M, Patwardhan AM, Gore SD (2006) Risk assessment of water erosion for the Qareh Aghaj subbasin, southern Iran. Stoch Env Res Risk Assess 21:15–24
Mitasova H, Hofierka J, Zlocha M, Iverson RL (1996) Modeling topographic potential for erosion and deposition using GIS. Int J Geogr Inf Sci 10:629–641
Nobrega RAA, O’Hara CG, Vijayaraj V, Olson G, Kim S, Quintanilha JA, Barros MTL (2006) Extracting and classifying bare soil erosion risk areas in a urban basin using object-oriented technologies, high resolution imagery and elevation data. Geographic information systems and water resources IV Awra spring specialty conference, Houston, Texas
Reid LM, Dunne T (1984) Sediment production from forest road surfaces. Water Resour Res 20:1753–1761
Sazbo J, Pasztor L, Suba Z, Varallyay G (1998) Integration of remote sensing and GIS techniques in land degradation mapping. In: Proceedings of the 16th international congress of soil science. Montpellier, France, pp 63–75
Varol O, Karaer F, Terzioğlu S, Kutbay HG (2003) Phytosociological investigation of Pinus pinea L. forest in Northeast Anatolia Region (Trabzon and Artvin-Turkey). Pak J Bot 35:587–595
Winkler N (1998) Environmentally sound road construction in mountainous terrain. FAO forest harvesting case study-10, Rome, p 55
WWF and IUCN (1994) Centres of plant diversity. A guide and strategy for their conservation, vol 1: Europe, Africa, South West Asia and the Middle East. IUCN Publication Unit. Cambridge, United Kingdom
Yuksel A, Akay AE, Gundogan R, Reis M, Cetiner M (2008a) Application of GeoWEPP for determining sediment yield and runoff in the Orcan creek watershed in Kahramanmaras, Turkey. Sensors 8:1222–1236
Yuksel A, Gundogan R, Akay AE (2008b) Using the remote sensing and GIS technology for erosion risk mapping of Kartalkaya dam watershed in Kahramanmaras, Turkey. Sensors 8:4851–4865
Yuksel A, Akay AE, Gundogan R (2008c) Using ASTER imagery in land use/cover classification of eastern Mediterranean landscapes according to CORINE land cover project. Sensors 8:1237–1251
Zhijun T, Jiquan Z, Xingpeng L (2009) GIS-based risk assessment of grassland fire disaster in western Jilin province, China. Stoch Env Res Risk Assess 23:463–471
Zhu G, Blumberg DG (2001) Classification using ASTER data and SVM algorithms; the case study of Beer Sheva, Israel. Remote Sens Environ 80:233–240
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This study is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) with the project number 106O054.
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Eroğlu, H., Çakır, G., Sivrikaya, F. et al. Using high resolution images and elevation data in classifying erosion risks of bare soil areas in the Hatila Valley Natural Protected Area, Turkey. Stoch Environ Res Risk Assess 24, 699–704 (2010). https://doi.org/10.1007/s00477-009-0356-5
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DOI: https://doi.org/10.1007/s00477-009-0356-5