Change detection and visualization of acid mine lakes using time series satellite image data in geographic information systems (GIS): Can (Canakkale) County,NW Turkey

Can, a county in the province of Canakkale, is one of the most prominent coal mining districts in Turkey. Many mining companies have been operating coal deposits for power generation and district heating in this region since 1980. Generally, small and medium-scale mining companies operate for short periods and abandon the operational land without providing any rehabilitation. Human intervention in the natural structure and topography of the earth surface causes large holes and deterioration in these areas. Artificial lakes occur because of surface discharge and underground leakage into abandoned open pit mines with high lignite sulfur content (0.21–14.36 wt %). Furthermore, these lakes gain acidic character due to acid generation from pyrite oxidation. Acid mine lakes are highly acidic (pH < 3.05) and have elevated concentrations of \({\text{SO}}_{4}^{2 - }\) , Fe and some metals. The main objective of this study is to evaluate the environmental conditions and demonstrate the development of a monitoring system for their possible changes in the acid mine lakes of the open cast lignite mining area on a regional scale. For this purpose, the data received from remote sensing satellites were used. Areal change detection and perimeter changes of nine acid mine lakes caused by coal mining companies in Can from 1977 to 2011, were determined using Landsat, Quickbird and Worldview satellite images. As a case study, an area of 9 km² was chosen for the variety of acid mine lakes. Using GIS software, satellite images were analyzed in time series, borders of acid mine lakes were digitized and converted into vector data format. At this stage, prior to the digitization, in order to create contrast on the satellite images, “stretch type” and “stretch values” were changed. The areal and perimeter changes were computed and presented via tables and graphics. In addition, thematic maps of the acid mine lakes were created and visualized. The results show that the number of acid mine lakes increased and these caused environmental risks due to their hydrochemical properties and areal increments.     

Review of water and soil contamination in and around Salihli geothermal field (Manisa,Turkey)

The town of Salihli is situated in Gediz Graben in the western Anatolia. This region is important in terms of industry, mining, geothermal energy, water sources, and agricultural production. Geothermal flow and anthropogenic activities in Salihli threaten the surrounding environment due to the contamination of cold groundwater, surface water, and soil. The goal of the present study is to determine the environmental effects of the geothermal and anthropogenic activities in Salihli on soil, stream sediments, and water. Stream sediments and farm soil have been contaminated by substances derived from geothermal and industrial effluents. To this end, the quality review of the water was completed and the heavy metal levels in stream sediment samples were measured to determine the extent of contamination. The elements As, B, Br, Fe, and Ni are the major contaminants present in surface water and groundwater in the study area. The concentrations of these elements excess tolerance limits of international water standards. Gibbsite, K-mica, kaolinite, sepiolite, halite, sulfur, willemite, and Pb(OH)₂ might be precipitated as scales at low temperatures on the soil; this could be interpreted as a resultant from soil contamination. The concentrations of 17 elements (As, Ba, B, Cd, Co, Cr, Cu, Fe, Hg, Li, Mo, Mn, Ni, Pb, Sb, Sr, and Zn) were measured in samples from stream sediments and surface soils. In the study area, especially geothermal and anthropogenic activities give rise to environmental pollution.     

Synsedimentary deformations in member 2 of the Mila Formation in the Central Alborz Mountains,Northern Iran

In Alborz Mountains, the thickness of sediments in Member 2 of the Mila Formation (Middle Cambrian) underwent dramatic and abrupt deformations, which were accompanied by normal and reverse faults and asymmetrical folds. These deformed sediments are covered by parallel beds both in the upper and lower sides. The existence of such extension and compression structures adjacent to each other indicates the influence of non-tectonic factors in their evolution. These deformations induced by downslope gliding of sediment packages are fully compatible with the dislocation model of Farrell (J Struct Geol 6:727–736, 1984) and Farrell and Eaton (1987). Moreover, the occurrence of synsedimentary deformations in a vast area in Alborz Mountains reinforces the probability of the impact of seismic shocks in their formation. In fact, incessant seismic events in the Middle Cambrian led to numerous submarine slumpings in the sediments of Member 2 of the Mila Formation.     

Geochemical modeling,fate distribution,and risk exposure of potentially toxic metals in the surface sediment of the Shyok suture zone,northern Pakistan

The objective of the current study was to assess the contamination of potentially toxic metals (PTMs) in weathered surface sediment, along stream tributaries, and surrounding area of the river Chitral, Shyok suture zone district Chitral, Pakistan. To understand the geochemical features of 113 sediment, samples were collected from the Mirkhani and Drosh area. Then, different statistical tools including the geo-accumulation index (Igeo), cluster analysis (CA), principal component analysis (PCA), and ecological risk assessment (ERA) were used to unravel the origin, intensity, and exposure level of PTMs to control risk and restore the ecosystem within the study area. The results for the PTMs namely nickle (Ni), chromium (Cr), copper (Cu), cadmium (Cd), lead (Pb), zinc (Zn), and cobalt (Co) in Mirkhani and Drosh were in the following ranges: 10–150, 15–210, 15–250, 0.08–1.00, 10–70, 76–240 and 14–51; and 13–240, 17–210, 15–150, 0.08–0.60, 7–140, 47–150 and 13–36 mg/kg, respectively. In consequence, the potential ecological risk caused by Pb, Ni, Cu, Co, Cr, and Zn is reflected by the percentages of samples with an ecological risk index (ERI) greater than one which were 100%, 91%, 100%, 100%, 92%, and 100%, respectively. However, the overall mean decreasing order of ecological risk of PTMs in the district Chitral was Pb > Ni > Cu > Co > Cr > Zn > Cd. Moreover, the PCA yielded 78% variability which indicated that mineral prospects play an important role in the contamination of sediment. Furthermore, the mineral phases of Pb and Zn suggested supersaturation, while that for Cd revealed unsaturation. The results of Igeo, ERI, and CA indicated contamination of PTMs in the study area. The ERI value of Pb, Ni, Cu, Co, Cr, and Zn was higher than 1 suggesting an ecological risk in the study area. Moreover, the current study showed the dominance of geogenic contamination with major contributions from ultramafic rock and known mineral prospects. Therefore, contaminated sediment of the Shyok suture zone is extremely detrimental to the aquatic ecosystem of the study area.     

Sea level variability at Antalya and Mente? tide gauges in Turkey: atmospheric, steric and land motion contributions

Sea level trends and interannual variability at Antalya and Menteş tide gauges are investigated during the 1985–2001 period, quantifying the roles of atmospheric, steric and local land motion contributions. Tide gauge sea level measurements, temperature/salinity climatologies and GPS data are used in the analyses and the results are compared with the output of a barotropic model forced by atmospheric pressure and wind. The overall sea level trends at two tide gauges collocated with GPS are in the range of 5.5 to 7.9 mm/yr during the study period, but showing different behaviour in the sub-periods 1985–1993 and 1993–2001 due to variations in the contributing factors both in space and time. After the removal of the atmospheric forcing and steric contribution from sea level records, the resulting trends vary between 1.9 to 4.5 mm/yr in Antalya and −1.2 to −11.6 mm/yr in Menteş depending on the period considered. Vertical land movement estimated from GPS data seems to explain the high positive residual trend in Antalya during the whole period. On the other hand, the source of the highly negative sea level trend of about −14 mm/yr in Menteş during 1985–1993 could not be resolved with the available datasets. Interannual variability of wind and atmospheric pressure appear to dominate the sea level at both tide gauges during the study period. Atmospheric and steric contributions together account for ∼50% of the total sea level variance at interannual time scales. Mass induced sea level variations which were not considered in this study may help to close the sea level trend budgets as well as to better explain the interannual sea level variance.     

Statistical analysis of surface urban heat island intensity variations: A case study of Babol city,Iran

The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.     

Context inference and prediction modeling in ubiquitous health GIS

The ever‐increasing population in cities intensifies environmental pollution that increases the number of asthmatic patients. Other factors that may influence the prevalence of asthma are atmospheric parameters, physiographic elements and personal characteristics. These parameters can be incorporated into a model to monitor and predict the health conditions of asthmatic patients in various contexts. Such a model is the base for any asthma early warning system. This article introduces a novel ubiquitous health system to monitor asthmatic patients. Ubiquitous systems can be effective in monitoring asthmatic patients through the use of intelligent frameworks. They can provide powerful reasoning and prediction engines for analyzing various situations. Our proposed model encapsulates several tools for preprocessing, reasoning and prediction of asthma conditions. In the preprocessing phase, outliers in the atmospheric datasets were detected and missing sensor data were estimated using a Kalman filter, while in the reasoning phase, the required information was inferred from the raw data using some rule‐based inference techniques. The asthmatic conditions of patients were predicted accurately by a Graph‐Based Support Vector Machine in a Context Space (GBSVMCS) which functions anywhere, anytime and with any status. GBSVMCS is an improved version of the common Support Vector Machine algorithm with the addition of unlabeled data and graph‐based rules in a context space. Based on the stored value for a patient's condition and his/her location/time, asthmatic patients can be monitored and appropriate alerts will be given. Our proposed model was assessed in Region 3 of Tehran, Iran for monitoring three different types of asthma: allergic, occupational and seasonal asthma. The input data to our system included air pollution data, the patients’ personal information, patients’ locations, weather data and geographical information for 270 different situations. Our results showed that 90% of the system's predictions were correct. The proposed model also improved the estimation accuracy by 15% in comparison to conventional methods.     

Vulnerability and adaptability of wheat production in different climatic zones of Pakistan under climate change scenarios

Ten wheat production sites of Pakistan were categorized into four climatic zones i.e. arid, semi-arid, sub-humid and humid to explore the vulnerability of wheat production in these zones to climate change using CSM-Cropsim-CERES-Wheat model. The analysis was based on multi-year (1971–2000) crop model simulation runs using daily weather series under scenarios of increased temperature and atmospheric carbon dioxide concentration (CO₂) along with two scenarios of water management. Apart from this, sowing date as an adaptation option to offset the likely impacts of climate change was also considered. Increase in temperature resulted in yield declines in arid, semi-arid and sub-humid zone. But the humid zone followed a positive trend of gain in yield with rise in temperature up to 4°C. Within a water regime, increase in CO₂ concentration from 375 to 550 and 700 ppm will exert positive effect on gain in wheat yield but this positive effect is significantly variable in different climatic zones under rainfed conditions than the full irrigation. The highest response was shown by arid zone followed by semi-arid, sub-humid and humid zones. But if the current baseline water regimes (i.e. full irrigation in arid and semi-arid zones and rainfed in sub-humid and humid zones) persist in future, the sub-humid zone will be most benefited in terms of significantly higher percent gain in yield by increasing CO₂ level, mainly because of its rainfed water regime. Within a CO₂ level the changes in water supply from rainfed to full irrigation shows an intense degree of responsiveness in terms of yield gain at 375 ppm CO₂ level compared to 550 and 700 ppm. Arid and semi-arid zones were more responsive compared to sub-humid and humid zones. Rise in temperature reduced the length of crop life cycle in all areas, though at an accelerated rate in the humid zone. These results revealed that the climatic zones have shown a variable intensity of vulnerability to different scenarios of climate change and water management due to their inherent specific and spatial climatic features. In order to cope with the negative effects of climate change, alteration in sowing date towards cooler months will be an appropriate response by the farmers.