Assessment of visual landscape quality using IKONOS imagery

The assessment of visual landscape quality is of importance to the management of urban woodlands. Satellite remote sensing may be used for this purpose as a substitute for traditional survey techniques that are both labour-intensive and time-consuming. This study examines the association between the quality of the perceived visual landscape in urban woodlands and texture measures extracted from IKONOS satellite data, which features 4-m spatial resolution and four spectral bands. The study was conducted in the woodlands of Istanbul (the most important element of urban mosaic) lying along both shores of the Bosporus Strait. The visual quality assessment applied in this study is based on the perceptual approach and was performed via a survey of expressed preferences. For this purpose, representative photographs of real scenery were used to elicit observers’ preferences. A slide show comprising 33 images was presented to a group of 153 volunteers (all undergraduate students), and they were asked to rate the visual quality of each on a 10-point scale (1 for very low visual quality, 10 for very high). Average visual quality scores were calculated for landscape. Texture measures were acquired using the two methods: pixel-based and object-based. Pixel-based texture measures were extracted from the first principle component (PC1) image. Object-based texture measures were extracted by using the original four bands. The association between image texture measures and perceived visual landscape quality was tested via Pearson’s correlation coefficient. The analysis found a strong linear association between image texture measures and visual quality. The highest correlation coefficient was calculated between standard deviation of gray levels (SDGL) (one of the pixel-based texture measures) and visual quality (r?=?0.82, P?<?0.05). The results showed that perceived visual quality of urban woodland landscapes can be estimated by using texture measures extracted from satellite data in combination with appropriate modelling techniques.     

Nutrient dynamics between sediment and overlying water in the inner part of Izmir Bay, Eastern Aegean

In this article a concept is described in order to predict and map the occurrence of benthic communities within and near the German Exclusive Economic Zone (EEZ) of the North Sea. The approach consists of two work steps: (1) geostatistical analysis of abiotic measurement data and (2) calculation of benthic provinces by means of Classification and Regression Trees (CART) and GIS-techniques. From bottom water measurements on salinity, temperature, silicate and nutrients as well as from punctual data on grain size ranges (0–20, 20–63, 63–2,000 μ) raster maps were calculated by use of geostatistical methods. At first the autocorrelation structure was examined and modelled with help of variogram analysis. The resulting variogram models were then used to calculate raster maps by applying ordinary kriging procedures. After intersecting these raster maps with punctual data on eight benthic communities a decision tree was derived to predict the occurrence of these communities within the study area. Since such a CART tree corresponds to a hierarchically ordered set of decision rules it was applied to the geostatistically estimated raster data to predict benthic habitats within and near the EEZ.     

Determination of heavy metals and metals levels in five fish species from I??kl? Dam Lake and Karaca?ren Dam Lake (Turkey)

The concentrations of heavy metals and metals (Zn, Pb, Bi, Cd, Ni, Co, Fe, Mn, Mg, Cu, Cr, Ca, Sr, Na, Li, K) were measured in muscle of five species Cyprinus carpio (from I??kl? dam), Scardinius erythrophthalmus (from I??kl? dam), Tinca tinca (from I??kl? dam), C. carpio (from Karaca?ren dam), Carassius carassius (from Karaca?ren dam) caught from I??kl? and Karaca?ren. The highest metal was Na (466.95 μg/g) in C. carassius, while the lowest levels were Fe (0.37 μg/g) and Cu (0.37 μg/g) in C. carpio from I??kl? dam. The mean concentrations μg/g d.w. some of heavy metals in muscle of C. carpio (from I??kl? dam), S. erythrophthalmus (from I??kl? dam), T. tinca (from I??kl? dam), C. carpio (from Karaca?ren dam), C. carassius (from Karaca?ren dam) were as follows: Cd 2.00-2.10-1.95-2.06-2.27, Zn 4.36-2.64-13.13-13.33-24.47, Pb 1.65-1.24-1.90-2.37-2.41, Co 2.46-2.37-2.48-2.58-2.80, Mg 138.51-154.35-218.59-204.58-202.16, Fe 0.37-2.62-3.17-3.01-12.33, respectively.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Biogeometallurgical pre-mining characterization of ore deposits: an approach to increase sustainability in the mining process

Based on the knowledge obtained from acid mine drainage formation in mine waste environments (tailings impoundments and waste rock dumps), a new methodology is applied to characterize new ore deposits before exploitation starts. This gives the opportunity to design optimized processes for metal recovery of the different mineral assemblages in an ore deposit and at the same time to minimize the environmental impact and costs downstream for mine waste management. Additionally, the whole economic potential is evaluated including strategic elements. The methodology integrates high-resolution geochemistry by sequential extractions and quantitative mineralogy in combination with kinetic bioleach tests. The produced data set allows to define biogeometallurgical units in the ore deposit and to predict the behavior of each element, economically or environmentally relevant, along the mining process.     

Interactions between metals accumulated in the narrow-clawed crayfish Astacus leptodactylus (Eschscholtz, 1823) in Dikilitaş Lake,Turkey

The accumulations of Al, Cd, Cr, Cu, Fe, Ni, Pb and Zn in the exoskeleton, gills, hepatopancreas and abdominal muscles of crayfish Astacus leptodactylus (Eschscholtz, 1823) were determined. The strongest correlation observed was between Cr and Ni in the gills (r?=?0.904); moderate to strong correlations between Al, Cr, Fe, Ni and Cu were also observed in gill tissue. Disregarding the gills, the strongest correlation was found between Cu and Zn in the hepatopancreas (r?=?0.808); the correlation between these two metals might have been a result of metallothionein activity. The accumulation of Pb was found to correlate with that of Cd in the exoskeleton, Cd and Zn in the gills, Zn and Cu in the hepatopancreas and Cu in the abdominal muscle. None of these correlations were present in lakewater and sediment samples, suggesting that the crayfish metabolism may be responsible for the co-accumulation of metal–metal pairs. As all correlations in non-gill tissues are observed between divalent metals, a shared transporter such as divalent metal transporter 1 might be involved in the accumulation of these metals.     

Correction to: WEEE closed-loop supply chain network management considering the damage levels of returned products

Environmental Science and Pollution Research - A Correction to this paper has been published: https://doi.org/10.1007/s11356-020-11851-4     

Earthworm Aporrectodea molleri (oligochaeta)’s coelomic fluid-associated bacteria modify soil biochemical properties and improve maize (Zea mays L.) plant growth under abiotic stress conditions

Environmental Science and Pollution Research - This study evaluated the impact of Aporrectodea molleri's coelomic fluid-associated bacteria (CFB) on Zea mays L. growth and soil biochemical...     

Comparison of chemical composition of the essential oil of Laurus nobilis L. leaves and fruits from different regions of Hatay, Turkey

The essential oils of the leaves and fruits from bay (Laurus nobilis L.) grown in Antakya, Yayladagi and Samandagi were isolated by solvent extraction and analysed by capillary gas chromatography (GC), gas chromatography and mass spectrometry (GC/MS). In Antakya, Yayladagi and Samandagi the chemical compositions of the fruits and leaves were similar according to qualitative and quantitative analysis. Although in both fruits and leaves the major component was found to be 1.8-Cineole a concentration of about 50% compared with essential oils. The composition of the essential oil from the leaves has high content of 1.8-Cineole, Sabinene and alpha-Terpinyl acetate, but a low content of a-Pinene, alpha-Phellandrene and trans-/beta-osimen. 1.8-Cineole was found major component of the leaves essential oil collected from Samandagi (59.94%) which is sea coast of region. Interestingly alpha-Pinene, beta-Pinene, alpha-Phellandrene, 1.8-Cineole and trans-beta-osimen were found the major components of fruits of Laurus nobilis L. harvested from Antakya, Yayladagi and Samandagi Trans-beta-osimen was detected as the major component of fruits essential oil collected again from Samandagi (28.35%)