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Öğe Coastal flood risk analysis using landsat-7 ETM+ imagery and SRTM DEM: A case study of Izmir, turkey(Springer, 2007) Demirkesen, A. C.; Evrendilek, F.; Berberoglu, S.; Kilic, S.The Intergovernmental Panel on Climate Change (IPCC) reports an acceleration of the global mean sea-level rise (MSLR) in the twentieth century in response to global climate change. If this acceleration remains constant, then some coastal areas are most likely to be inundated by the year 2100. The ability to identify the differential vulnerability of coastlines to future inundation hazards as result of global climate change is necessary for timely actions to be taken. Yildiz et al. (Journal of Mapping, 17, 1 75, 2003) reported that the local MSLR in the city of Izmir rose at a rate of 6.8 +/- 0.9 mm year(-1) between 1984 and 2002. In this study, the spatial distribution of the coastal inundation hazards of Izmir region was determined using not only land-use and land-cover (LULC) types derived from the maximum likelihood classification of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) multi-spectral image set but also the classification of the digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM). Coastal areas with elevations of 2 and 5 m above mean sea-level vulnerable to inundation were found to cover 2.1 and 3.7% of the study region (6,107 km(2)), respectively. Our findings revealed that Menemen plain along Gediz river, and the settlements of Karsiyaka, Alacati, Aliaga, Candarli and Selcuk are at high risk in order of decreasing vulnerability to permanent and episodic inundation by 2100 under the high MSLR scenarios of 20 to 50 mm year(-1).Öğe Data-driven simulations of flank wear of coated cutting tools in hard turning(Kaunas Univ Technol, 2015) Cakan, A.; Evrendilek, F.; Ozkaner, V.Insurance of surface quality and dimensional tolerances in finish hard turning necessitates the development of accurate predictive models. This study aimed at modeling flank wear of multilayer-coated carbide inserts in finish dry hard turning of AISI 4340 and AISI 52100 hardened steels based on 28 artificial neural networks (ANNs) and the best-fit multiple non-linear regression (MNLR) model. Online-monitored flank wear of multilayer-coated carbide inserts was modeled as a function of the three cutting speeds of 70, 98 and 142 m min(-1), and the two workpieces under the constant feed rate and cutting depth of 0.027 mm min(-1) and 0.2 mm, respectively. Out of the 28 ANNs, 18 ANNs appeared to be capable of better predictions for tool flank wear than the best-fit MNLR model. Probabilistic neural network (PNN) outperformed all the remaining models based on all the training, cross-validation and testing dataset-related performance metrics.Öğe Effects of strip intercropping and organic farming systems on quantity and quality of maize yield in a Mediterranean region of Turkey(Haworth Press Inc, 2007) Sermenh, T.; Evrendilek, F.; Mavi, K.Cowpea (Vigna sinensis L.) and okra (Abelmoschus esculentus L.) are traditionally intercropped with maize (Zea mays L.) by small-scale farmers in the Mediterranean region of Turkey. In this experiment, the performances of monoculture-organic (MO), strip intercropping-organic (10), monoculture-conventional (MC), and strip intercropping-conventional (IC) farming systems were compared with respect to yield quantity and quality properties of sweet maize, and local cowpea and okra varieties for 2 years. The land equivalent ratios (LERs) calculated based on mean maximum and minimum yields of cowpeas and okras ranged between 0.94 and 1.25 for strip intercropping with sweet maize. There appeared to be no difference in mean yields of maize, cowpeas, and okras between the 10 and IC systems and in mean maize yields between the MO and MC systems (P > 0.05). The LER value (0.99) of the 10 farming system was higher than that (0.95) of IC farming system. The LER values close to one indicated that there were no significant differences in yield quantity and quality of the crops among the four farming systems. The findings revealed that strip intercropping alone or in combination with organic cropping may be equally profitable to monoculture and favored for sustainable farming if agricultural production costs including environmental externalities, such as environmental degradation and destruction were accounted for.Öğe Environmental monitoring of land-use and land-cover changes in amik plain, Turkey(International Society for Photogrammetry and Remote Sensing, 2004) Kilic, S.; Evrendilek, F.; Berberoglu, S.; Demirkesen, A.C.Unprecedented rates of changes in land use/cover (LULC) on the local and regional scales lead to alterations of global biogeochemical cycles, and loss of productive ecosystems and biodiversity. Driving forces behind LULC changes mainly include rapid growth rates of population and consumption, lack of valuation of ecological services, poverty, ignorance of biophysical limitations, and use of ecologically incompatible technologies. One of the major ecological tragedies of the commons in the province of Hatay is the case of the loss of the Amik Lake, which reveals the urgent need for adoption of sustainable and adaptive ecosystem management strategies if escalating land use conflicts are to be avoided and environmental degradation is to be reversed in the Amik plain of the southeastern Mediterranean region of Turkey. In the 1940s, the Amik lake was started to be discharged into the Orontes river by a large-scale campaign launched to increase the area of croplands. The study quantified LULC changes and explored constraints and opportunities for future LULCs in the study area. Land use/cover changes were detected from a time series of satellite images of Landsat-MSS in 1972, Landsat-5 TM in 1987, and Landsat-7 ETM+ in 2000 using remote sensing and geographic information systems (GIS). The study revealed that the increase in croplands between 1972 and 1987 took place at the expense of the irreversible losses of the Amik lake and its related wetlands of over 53 km2 used to provide vital ecosystem goods and services for the region. In the period of 1972 to 2000, croplands, settlements, and evergreen forests increased by 174%, 106%, and 14%, respectively, in parallel to the decreases in shrublands-orchards, and bareground. The increase in settlements occurred mostly to the detriment of croplands. The prospects for halting environmental degradation and destruction, rehabilitating damaged ecosystems, and developing sustainable ecosystem management practices need to be dealt with in light of the institutional and economic constraints facing Turkey.Öğe Integrating ATR-FTIR and data-driven models to predict total soil carbon and nitrogen towards sustainable watershed management(Dr Jyoti Garg, 2013) Aslan-Sungur, G.; Evrendilek, F.; Karakaya, N.; Gungor, K.; Kilic, S.The use of Attenuated Total Reflectance (ATR) is an alternative method in determining carbon (C), nitrogen (N) and other elemental contents of organic and inorganic soils for which diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy has been mostly utilized. In this study, the combined use of ATR-Fourier transform infrared (FTIR) spectroscopy and partial least square regression (PLSR) or artificial neural network (ANN) models in estimating total soil C and N have been explored which provide direct, rapid, economical and multiple in situ measurements. Total soil C and N data obtained from 153 soil samples across agricultural lands and analyzed using CNH elemental analyzer were used to build PLSR and ANN models as a function of ATR-FTIR spectrum ranges based on a training dataset with leave-one-out cross validation (LCV) and independent validation (IV) dataset that randomly constitute 67% and 33% of the entire dataset respectively. Wavenumber ranges of 650-2365 cm(-1) and 773-1726 cm(-1) in ATR-FTIR data were selected as predictors for PLSR and ANN models of soil C respectively. PLSR model of soil C led to r(2) = 0.86 for training and r(2) = 0.68 for validation, with PLSR model of soil N as a result of wavenumber range of 1300-1400 cm(-1) leading to r(2) = 0.81 for training and r(2) < 0.1 for validation. Multilayer perceptron model appeared to be the best-performing ANN for the emulations of both total soil C and N and outperformed PLSR model of total soil N.
