Sinkhole Susceptibility Mapping Using a Frequency Ratio Method and GIS Technology Near Karapınar, Konya-Turkey

Özdemir, Adnan

doi:10.1016/j.proeps.2015.08.059

Cited by 15 publications

(12 citation statements)

References 9 publications

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“…Moreover, for more than 40 years, the existence of some sinkhole hazards is known by the local people, especially by farmers. Bayari et al (2009) andOzdemir (2015) has investigated the formation and spatial characteristics of these sinkholes (Turkish name obruk) using GIS tools within the area. Starting from 2006, the space based geodetic techniques such as GPS and InSAR have been used to monitor the deformation caused especially by extraction of groundwater in the study area.…”

Section: Introductionmentioning

confidence: 99%

Multi Band Insar Analysis of Subsidence Development Based on the Long Period Time Series

Comut

Ustun

Lázecký

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The SAR Interferometry (InSAR) application has shown great potential in monitoring of land terrain changes and in detection of land deformations such as subsidence. Longer time analysis can lead to understand longer trends and changes. Using different bands of SAR satellite (C-from ERS 1-2 and Envisat, L-from ALOS) over the study area, we achieve knowledge of movements in long-term and evaluation of its dynamic changes within observed period of time. Results from InSAR processing fit with the position changes in vertical direction based on GPS network established over the basin as an effective geodetic network. Time series (StaMPS PS+SB) of several points over Çumra County in eastern part of Konya City show a general trend of the deformation that is expected to be approximately between -13 to -17 mm/year. Northern part of Karaman is affected by faster subsidence, borders of the subsidence trough were identified from Envisat. Presenting InSAR results together with GIS information about locations and time of occurrence of sudden subsidence, urban/industrial growth in time and climate changes helps in better understanding of the situation. This way, the impact of natural and man-made changes will be shown for urban planning thanks to InSAR and GIS comparisons with hydrogeological modeling. In this study we present results of differential and multitemporal InSAR series using different bands and GIS conjunction associated with seasonal and temporal groundwater level changes in Konya Closed Basin.

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Section: Introductionmentioning

confidence: 99%

Multi Band Insar Analysis of Subsidence Development Based on the Long Period Time Series

Comut

Ustun

Lázecký

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Reliable evaluations of models on sinkhole susceptibility are scarce in the international literature (Table 1), and most of the papers do not present information about the reliability of the presented maps, models or methods. Only Galve et al (2008Galve et al ( , 2009bGalve et al ( , 2011, Oh & Lee (2010), Pradhan et al (2014), D'Angella et al (2015), Perrin et al (2015), Ozdemir (2015) and Ciotoli et al (2016) show reliable validation results. However, the evaluation of models is a common practice in the susceptibility modeling of landslides and earthquakes.…”

Section: Introductionmentioning

confidence: 96%

Integration of multi-criteria and nearest neighbour analysis with kernel density functions for improving sinkhole susceptibility models: the case study of Enemonzo (NE Italy)

Calligaris¹,

Devoto²,

Galvé³

et al. 2017

IJS

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Abstract:The significance of intra-mountain valleys to infrastructure and human settlements and the need to mitigate the geo-hazard affecting these assets are fundamental to the economy of Italian alpine regions. Therefore, there is a real need to recognize and assess possible geohazards affecting them. This study proposes the use of GIS-based analyses to construct a sinkhole susceptibility model based on conditioning factors such as land use, geomorphology, thickness of shallow deposits, distance to drainage network and distance to faults. Thirtytwo models, applied to a test site (Enemonzo municipality, NE Italy), were produced using a method based on the Likelihood Ratio (λ) function, nine with only one variable and 23 applying different combinations. The sinkhole susceptibility model with the best forecast performance, with an Area Under the Prediction Rate Curve (AUPRC) of 0.88, was that combining the following parameters: Nearest Sinkhole Distance (NSD), land use and thickness of the surficial deposits. The introduction of NSD as a continuous variable in the computation represents an important upgrade in the prediction capability of the model. Additionally, the model was refined using a kernel density estimation that produced a significant improvement in the forecast performance.evaporite karst, sinkhole, susceptibility, nearest neighbour, prediction-rate curves Calligaris C., Devoto S., Galve J.P., Zini L. and Pérez-Peña, J.V., 2017. Integration of multicriteria and nearest neighbour analysis with kernel density functions for improving sinkhole susceptibility models: the case study of Enemonzo (NE Italy).

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“…In this probabilistic technique, the method that is used is frequency ratio. Frequency ratio method is one of the methods that are widely used in many studies [19].…”

Section: Introductionmentioning

confidence: 99%

GIS based probabilistic method in sinkhole susceptibility hazard zones

Rosdi

Othman

Latif

et al. 2019

IJEECS

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In this era of globalization, natural phenomena often invade the human population. Natural phenomena such as sinkholes often occur in countries whose topology lies in active limestone areas. Malaysia is one of the countries with active limestone areas, especially in the Klang Valley and its surrounding areas. Since 1968, the increase in sinkhole cases in Malaysia has been reported frequently. This has caused many building infrastructures to be destroyed, loss of life and destruction of property. So, one of the steps to overcome this problem is to do an in-depth study of the sinkhole. Therefore, Sinkhole Hazard Model (SHM) has been created with a combination of GIS integration by using probability techniques. There are five criteria suitable for Malaysian topography namely Lithology (LT), Soil Types (ST), Landuse (LU), Groundwater Level Decline (GLD) and Proximity to Groundwater Wells (PGW). Based on probability calculations, GLD and LU have shown a high impact on sinkhole formation. A hazard zonation map has been produced where it has been classified into five parts namely none, low, medium, high and very high. The results were validated with previous inventory data comprising 33 data. Based on the results obtained, 36.37% and 39.39% of the sinkhole formation has fallen into high and very high areas respectively. Based on these final results, the integration between GIS and probability techniques is useful in natural phenomena such as sinkhole formation.

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Sinkhole Susceptibility Mapping Using a Frequency Ratio Method and GIS Technology Near Karapınar, Konya-Turkey

Cited by 15 publications

References 9 publications

Multi Band Insar Analysis of Subsidence Development Based on the Long Period Time Series

Multi Band Insar Analysis of Subsidence Development Based on the Long Period Time Series

Integration of multi-criteria and nearest neighbour analysis with kernel density functions for improving sinkhole susceptibility models: the case study of Enemonzo (NE Italy)

GIS based probabilistic method in sinkhole susceptibility hazard zones

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