Temporal soil erosion risk evaluation: a CORINE methodology application at Elmalı dam watershed, Istanbul

Aydın, Abdürrahim; Tecimen, Hüseyin Barış

doi:10.1007/s12665-010-0461-2

Cited by 19 publications

(19 citation statements)

References 18 publications

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“…US$ 80 million of property is lost each year in Turkey due to landslides (Yalcin 2011(Yalcin , 2007. Moreover, a considerable amount of fertile land is carried away yearly by rivers as a result of soil erosion, which leaves the remaining fertile land exposed to increased erosion and landslides (Irvem et al 2007;Aydin and Tecimen 2010). Such environmental hazards have been exacerbated by disorganised and traditional land use practices in rural areas, where planning and land management regulations are often disregarded (Demir et al 2015b).…”

Section: Introductionmentioning

confidence: 99%

Landslide susceptibility mapping of the Sera River Basin using logistic regression model

et al. 2016

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Of the natural hazards in Turkey, landslides are the second most devastating in terms of socioeconomic losses, with the majority of landslides occurring in the Eastern Black Sea Region. The aim of this study is to use a statistical approach to carry out a landslide susceptibility assessment in one area at great risk from landslides: the Sera River Basin located in the Eastern Black Sea Region. This paper applies a multivariate statistical approach in the form of a logistics regression model to explore the probability distribution of future landslides in the region. The model attempts to find the best fitting function to describe the relationship between the dependent variable, here the presence or absence of landslides in a region and a set of independent parameters contributing to the occurrence of landslides. The dependent variable (0 for the absence of landslides and 1 for the presence of landslides) was generated using landslide data retrieved from an existing database and expert opinion. The database has information on a few landslides in the region, but is not extensive or complete, and thus unlike those normally used for research. Slope, angle, relief, the natural drainage network (including distance to rivers and the watershed index) and lithology were used as independent parameters in this study. The effect of each parameter was assessed using the corresponding coefficient in the logistic regression function. The results showed that the natural drainage network plays a significant role in determining landslide occurrence and distribution. Landslide susceptibility was evaluated using a predicted map of probability. Zones with high and medium susceptibility to landslides make up 38.8 % of the study area and are located mostly south of the Sera River Basin and along streams.

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Section: Introductionmentioning

confidence: 99%

Landslide susceptibility mapping of the Sera River Basin using logistic regression model

et al. 2016

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“…The CORINE model correctly identified the areas of the Mediterranean, which have the highest risk of erosion (Gobin et al 2003). And then the CORINE model was widely applied by the European and Mediterranean countries for SER assessment (Husnjak et al 2008;Bayramin et al 2006;Parlak et al 2007;Yuksel et al 2008;Aydın and Tecimen 2010).…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, a combination of RS, GIS, and CORINE model provides the potential to assess soil erosion and its spatial distribution with reasonable costs and better accuracy in larger areas. For example, Yuksel et al (2008) and Aydın and Tecimen. (2010) have evaluated SER in Turkey by using RS and GIS-based CORINE methodology, respectively.…”

Section: Introductionmentioning

confidence: 99%

Soil erosion risk assessment with CORINE model: case study in the Danjiangkou Reservoir region, China

Zhu

2011

Stoch Environ Res Risk Assess

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Soil erosion is one of the major threats to the conservation of soil and water resources in the Danjiangkou Reservoir region (DRR), China. In order to describe the areas with high soil erosion risk (SER) and to develop adequate erosion prevention measures, SER in the DRR was assessed by integrating the CORINE model with GIS and RS. The main factors of soil erosion including erosivitiy, soil erodibility, topography and vegetation cover were determined from daily meteorological data, field survey soil profile data and soil sample analysis, digital elevation model (DEM), and land use and land cover (LULC), respectively. Landsat 5 TM imagery was used to generate a LULC classification. The results indicate that 59.1%, 31.2%, and 2.3% of the study area were under low, moderate, and high actual erosion risks, respectively. The results also indicate the study area is in low to moderate erosion risk level on the whole. The areas with moderate to high erosion risk continuously distributed in the southwest of the study area, and sporadically distributed in the north of the study area. Low erosion risk areas mainly located in the east. Up till now, most of the semi-quantitative models have not been applied extensively. The semi-quantitative CORINE model was mostly applied in the European and Mediterranean countries, while spatial comparison of actual SER map and field investigation in this study indicates that the CORINE model can be applicable in the monsoon region of China.

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“…Generally, in large-area forestry studies, standard topomap contour lines -based DEMs or the spaceborne SRTM (Shuttle Radar Topography Mission), ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) GDEM (Global Digital Elevation Model) data are used to obtain the topographic metrics (Aydın and Tecimen, 2010;Jing et al, 2014;Wong et al, 2014;De Meij et al, 2015;Mo et al, 2015;Rather et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Comparison of ASTER, contour lines and LiDAR based DEMs in terms of topographic differences in forested area

Yurtseven¹

2019

Eurasian Journal of Forest Science

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DEMs (Digital Elevation Model) generated with different remote sensing techniques and technologies. DEMs are used to determine the changes of vegetation in forests depending on topographical factors. The accuracy of DEMs has a major impact on the planning and management of forests. In this study, the accuracy of two different DEM data sources, which are frequently used in the modeling of topographic changes in large field studies in forestry, was compared with the LiDAR-based DEM dataset on a forest site. In this context, three different DEM source were used. One of them was the 10 m interval contour lines of 1:25,000 scale aerial photogrammetry based standard topographical maps which are produced by National General Directorate of Mapping. Topomap contour lines are transformed to grid based DEMs by using TIN and ANUDEM based approaches at 2.5, 5, 10 and 30 m resolutions. The other data was ASTER GDEM (1 arc-second ASTER GDEM Version 2, approximately 30 m resolution). The final and reference data is the LiDAR based, 0.25 m resolution DEM. In total, 33 DEM datasets are compared with the LiDAR-based DEM dataset. For these data sets, five difference metrics were calculated: pixel based difference models, the areal and volumetric difference of surface models, the areal difference of slope classes and the areal difference of aspect classes. According to the results of the analysis, the resolution, according to the topographic characteristics of the area and selected interpolation approaches has an effect on DEM modeling and DEM-derived metrics. In addition, the forest structure has a major impact on the accuracy of ASTER GDEM data.

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Temporal soil erosion risk evaluation: a CORINE methodology application at Elmalı dam watershed, Istanbul

Cited by 19 publications

References 18 publications

Landslide susceptibility mapping of the Sera River Basin using logistic regression model

Landslide susceptibility mapping of the Sera River Basin using logistic regression model

Soil erosion risk assessment with CORINE model: case study in the Danjiangkou Reservoir region, China

Comparison of ASTER, contour lines and LiDAR based DEMs in terms of topographic differences in forested area

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