Environmental modelling of Omerli catchment area in Istanbul, Turkey using remote sensing and GIS techniques

Omerli Reservoir is one of the major drinking water reservoirs of Greater Metropolis Istanbul, providing 40% of the overall water demand. Istanbul where is one of the greatest metropolitan areas of the world with a population over 10 million and a rate of population increase about twice that of Turkey. As a result of population growth and industrial development, Omerli watershed is highly affected by the wastewater discharges from the residential areas and industrial plants. The main objective of this study is to investigate the temporal assessment of the land-use/cover of the Omerli Watershed and the water quality changes in the Reservoir. It is not possible to adequately control urbanization and other pollution sources affecting the water quality. Responses of these detrimental effects are due to rapidly increasing population, unplanned and illegal housing, and irrelevant industries at the protection zones of the watershed, together with insufficient infrastructure. The study is focused on the assessment of urbanization in relation to land use and water quality using Remote Sensing (RS) and Geographic Information Systems (GIS) techniques for all the four protection zones of the Reservoir and a time variant analyzing model is obtained. IRS-1C LISS and IRS-1C PAN, LANDSAT-5 TM satellite data of 1997, 1998, 2000, 2001 and 2006 are analyzed by confirmation through the ground truth data. RS data have been transferred into UTM coordinate system and image enhancement and classification techniques were used. Raster data were converted to vector data that belongs to study area to analyze in GIS for the purpose of planning and decision-making on protected watersheds.     

Spatial distribution of heavy metals content in soils of Amik Plain (Hatay, Turkey)

The purpose of the study was to investigate the total and bio-available contents of heavy metals (Cd, Co, Ni, and Pb) and to determine their spatial variability in the Amik Plain, Turkey. Samples of surface and subsurface soil were collected at 132 sites in the research area. All of the total metal concentrations except Ni were considerably lower than their maximum allowable concentrations. Mean available Pb concentrations at both depths were above the permissible limits, while the other metal concentrations were within the proposed limits. Semivariograms of all the total metal contents, pH, and available Ni and Pb content were best fitted to spherical models, while available Cd and Co contents were best fitted to exponential models. Block kriging was used to interpolate values at unmeasured locations, generating maps of spatial variation for each heavy metal and pH.     

Monitoring the urban green spaces and landscape fragmentation using remote sensing: a case study in Osmaniye,Turkey

Urban green spaces play a significant role in management of physical activity, psychological well-being, and public health of urban residents. With the expansion of urban areas in Turkey during the past decades, urban green spaces have been fragmented and dispersed causing impairment and environmental degradation. The purpose of this study is to model urban green space distribution by focusing on the landscape fragmentation in city of Osmaniye using remote sensing and geographic information system technology. Normalized difference vegetation index (NDVI) and urban landscape ratio (ULR) were used to assess the proximity and spatial arrangement of urban green spaces within the neighbor landscapes to quantify the urban land use effect. The geospatial analysis results showed that increase in total built-up area and population has significantly decreased the urban green space cover because of high levels of landscape fragmentation in urban city center. Also, due to high levels of landscape fragmentation, approximately 45% of the Osmaniye city is estimated to become urbanized by 2030. This study demonstrated the benefits of directional vegetation index application with geospatial analyses in characterizing the environmental quality for planning and management of urban green spaces. This approach could be used for determining the future urban land development scenarios correlating with regional planning procedures.     

Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey)

In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.     

Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS)

The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.     

Analysis of the changes of vegetation coverage of western Beijing mountainous areas using remote sensing and GIS

Mentougou District acts as a crucial component in the ecological buffer in western Beijing mountainous areas, Beijing, China. Using two Landsat MSS/TM images acquired on July 14, 1979 and July 23, 2005, the vegetation coverage of Mentougou District was calculated based on normalized difference vegetation index and spectral mixture analysis (NDVI-SMA) model. Its temporal and spatial changes were analyzed according to digital elevation model (DEM) image, social and economic data. The results showed that the vegetation coverage decreased from 76.4% in 1979 to 72.7% in 2005. Vegetation degradation was probably the result of human disturbance, such as outspreading of resident areas, and coal and stone mining activities, while vegetation restoration might be contributed by the combined effects of both natural processes and ecological construction effort. Vegetation changes were closely related to topographical characteristics. Plants at high altitude were more stable and less degraded than the plants at low altitude, while the plants on steep slope or northwest aspect were more vulnerable to degradation. During the period of 26 years, landscape appeared to become more fragmental, and ecological quality of the land seemed deteriorated sharply in that highly-covered vegetation area has been decreased by 24%.     

Analyzing landscape changes in the Bafa Lake Nature Park of Turkey using remote sensing and landscape structure metrics

Bafa Lake Nature Park is one of Turkey’s most important legally protected areas. This study aimed at analyzing spatial change in the park environment by using object-based classification technique and landscape structure metrics. SPOT 2X (1994) and ASTER (2005) images are the primary research materials. Results show that artificial surfaces, low maqui, garrigue, and moderately high maqui covers have increased and coniferous forests, arable lands, permanent crop, and high maqui covers have decreased; coniferous forest, high maqui, grassland, and saline areas are in a disappearance stage of the land transformation; and the landscape pattern is more fragmented outside the park boundaries. The management actions should support ongoing vegetation regeneration, mitigate transformation of vegetation structure to less dense and discontinuous cover, control the dynamics at the agricultural–natural landscape interface, and concentrate on relatively low but steady increase of artificial surfaces.     

Modeling land use/land cover change using remote sensing and geographic information systems: case study of the Seyhan Basin,Turkey

Land use and land cover (LULC) changes affect several natural environmental factors, including soil erosion, hydrological balance, biodiversity, and the climate, which ultimately impact societal well-being. Therefore, LULC changes are an important aspect of land management. One method used to analyze LULC changes is the mathematical modeling approach. In this study, Cellular Automata and Markov Chain (CA-MC) models were used to predict the LULC changes in the Seyhan Basin in Turkey that are likely to occur by 2036. Satellite multispectral imagery acquired in the years 1995, 2006, and 2016 were classified using the object-based classification method and used as the input data for the CA-MC model. Subsequently, the post-classification comparison technique was used to determine the parameters of the model to be simulated. The Markov Chain analyses and the multi-criteria evaluation (MCE) method were used to produce a transition probability matrix and land suitability maps, respectively. The model was validated using the Kappa index, which reached an overall level of 77%. Finally, the LULC changes were mapped for the year 2036 based on transition rules and a transition area matrix. The LULC prediction for the year 2036 showed a 50% increase in the built-up area class and a 7% decrease in the open spaces class compared to the LULC status of the reference year 2016. About an 8% increase in agricultural land is also likely to occur in 2036. About a 4% increase in shrub land and a 5% decrease in forest areas are also predicted.     

Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+

The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO?-N), silicate (SiO?), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO?-N (P?=?0.008) to 0.79 for S (depth) (P?相似文献   

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.     

Assessing impact of industrialization in terms of LULC in a dry tropical region (Chhattisgarh), India using remote sensing data and GIS over a period of 30 years

The main focus of the paper is to assess the land use/ land cover (LULC) change in northern Chhattisgarh due to industrialization using remote sensing and Geographical Information System (GIS). The impact was assessed using an information extraction method applied to temporal satellite data (LANDSAT and IRS scenes) in GIS domain. For assessing the impact on natural resources, the classification scheme was restricted to (1) Forest patches ((a) completely cleared, (b) partially cleared, (c) least affected), (2) Non-Forest ((d) completely changed, (e) least changed), (3) Industrial/Mining area, and (4) River. Over the three decades 22.22% of forests have been completely cleared and converted to industrial setup. Another 25% is completely cleared and 10% is degraded. Around 4% of agricultural area is totally affected due to industrial activity. Random assessment of plant distribution (Trees, Shrubs and Herbs) indicates significant changes in the herb distribution directly related to distance gradient form the industrial/mining setup. Visual recording, socio-economic survey and satellite data also helped in delineation of extent of environmental pollution in forest and non-forest areas. The paper presents methodology for the environmental impact assessment.     

Analysis of terrains suitable for tourism and recreation by using geographic information system (GIS)

The use and utilization areas of geographic information system (GIS) increase every day due to both enabling easiness in storing, updating, grouping, analyzing, correlating, and mapping of data about evaluation factors in planning studies and having quite low error margin depending on the accuracy of data stored. In fact, GIS is also used both in visualization and in various analyses in planning tourism terrains. In this study, the effectiveness of GIS on holistic evaluation of natural and cultural resources in planning tourism terrains was analyzed. Natural and cultural resources in Kayseri Yahyal? were quantified by using ArcGIS 9.3 software from GIS software; data were analyzed and potential tourism and recreation terrains, level of suitability, and rate of coverage were determined. As a result of the analyses, it was determined that 11.847 ha area (6,53 %) was quite suitable for such kind of activities, 103.010 ha (56,77 %) was suitable, 39.278 ha (21,65 %) was less suitable, and 27.314 ha area (15,05 %) was not suitable. In the next stage, landscape properties which are suitable for tourism and recreation were evaluated and landscape types were classified in the sense of their tourist attraction. It was determined that the water resources and valley landscapes were the basic sources of the tourism and recreation activities of Yahyal?, and it was determined that the landscape of the forest and mountain was important for variety of the tourism and recreation activities of Yahyal?.     

Assessment of groundwater vulnerability using remote sensing,susceptibility index,and WetSpass model in an arid region (Biskra,SE Algeria)

Environmental Monitoring and Assessment - Downstream water pollution resulting from anthropogenic pressures on upstream water can cause conflicts, especially in transboundary rivers basins. This...     

Water quality monitoring using remote sensing in support of the EU water framework directive (WFD): A case study in the Gulf of Finland

Water quality monitoring using remote sensing has been studied in Finland for many years. But there are still few discussions on water quality monitoring using remote sensing technology in support of water policy and legislation in Finland under the WFD. In this study, we present water quality monitoring using remote sensing in the Gulf of Finland, and focus on the spatial distribution of water quality information from satellite-based observations in support of water policy by a case study of nitrate concentrations in surface waters. In addition, we briefly describe instruments using a system of river basin districts (RBD), highlighting the importance of integrated water resources and river-basin management in the WFD, and discuss the role of water quality monitoring using remote sensing in the implementation of water policy in Finland under the WFD.     

Impact of intensive agricultural practices on drinking water quality in the EVROS Region (NE GREECE) by GIS analysis

Chemical fertilizers are used extensively in modern agriculture, in order to improve yield and productivity of agricultural products. However, nutrient leaching from agricultural soil into groundwater resources poses a major environmental and public health concern. The Evros region is one of the largest agricultural areas in Northern Greece, extending over 1.5 million acres of cultivated land. Many of its drinking water resources are of groundwater origin and lie within agricultural areas. In order to assess the impact of agricultural fertilizers on drinking water quality in this region, tap-water samples from 64 different locations were collected and analyzed for the presence of nitrates [Formula: see text], nitrites [Formula: see text], ammonium [Formula: see text], sulfate [Formula: see text] and phosphate [Formula: see text]. These chemicals were selected based on the information that ammonium nitrate, ammonium sulfate and inorganic phosphate were the primary fertilizers used in local crop production. [Formula: see text], [Formula: see text] and [Formula: see text] levels exceeding accepted values were recorded in 6.25, 4.70 and 9.38% of all sampling points, respectively. [Formula: see text] and [Formula: see text] concentrations, on the other hand, were inside the permitted range. The data generated were introduced into a geographic information system (GIS) program for computer analysis and projection maps representing afflicted areas were created. Our results indicate a profound geographic correlation in the surface distribution of primary contaminants in areas of intensified agricultural production. Thus, drinking water pollution in these areas can be attributed to excessive fertilizer use from agricultural sources.     

The potential of remote sensing for monitoring land cover changes and effects on physical geography in the area of Kayisdagi Mountain and its surroundings (Istanbul)

The effect of land cover change, from natural to anthropogenic, on physical geography conditions has been studied in Kayisdagi Mountain. Land degradation is the most important environmental issue involved in this study. Most forms of land degradation are natural processes accelerated by human activity. Land degradation is a human induced or natural process that negatively affects the ability of land to function effectively within an ecosystem. Environmental degradation from human pressure and land use has become a major problem in the study area because of high population growth, urbanization rate, and the associated rapid depletion of natural resources. When studying the cost of land degradation, it is not possible to ignore the role of urbanization. In particular, a major cause of deforestation is conversion to urban land. The paper reviews the principles of current remote sensing techniques considered particularly suitable for monitoring Kayisdagi Mountain and its surrounding land cover changes and their effects on physical geography conditions. In addition, this paper addresses the problem of how spatially explicit information about degradation processes in the study area rangelands can be derived from different time series of satellite data. The monitoring approach comprises the time period between 1990 and 2005. Satellite remote sensing techniques have proven to be cost effective in widespread land cover changes. Physical geography and particularly natural geomorphologic processes like erosion, mass movement, physical weathering, and chemical weathering features etc. have faced significant unnatural variation.     

Assessment of the interactive effects of ambient O3 and NPK levels on two tropical mustard varieties (Brassica campestris L.) using open-top chambers

Rising O(3) concentrations in agricultural areas have been identified as a significant threat to crop production in Asia including India. The present work reports the results of a field study conducted to assess the usefulness of higher than recommended NPK dose in modifying the physiological, growth, yield, and seed quality responses of two mustard (Brassica campestris L. var. Vardan and Aashirwad) varieties under ambient ozone level at a rural site of India, using open-top chambers. Twelve hourly mean O(3) concentrations ranged between 27.7 and 59.04 ppb during the growth period. Plants in nonfiltered chambers (NFCs) showed reductions in photosynthetic rate, stomatal conductance, and growth parameters compared to the plants in filtered chambers (FCs), but reductions were of lower magnitude at 1.5 times recommended dose of NPK (1.5 RNPK) compared to recommended (RNPK). Yield and seed quality reduced significantly in plants of NFCs compared to FCs at RNPK, but no significant differences were recorded at 1.5 RNPK. There were higher N uptake and N uptake efficiency of plants in FCs compared to NFCs. Nitrogen utilization efficiency increased in Vardan, but decreased in Aashirwad in NFCs compared to FCs suggesting higher capability of N acquisition and utilization under ambient O(3), which led to a less pronounced reduction in the yield of the former than the latter variety. The differential nitrogen utilization efficiency in these varieties may be potentially used as measure of sensitivity characteristics in breeding programs for yield improvement in mustard under the present trend of increase in O(3) concentrations.     

Seasonal variation of the metal (Zn, Fe, Mn) and metallothionein concentrations in the liver cytosol of the European chub (Squalius cephalus L.)

Seasonal variations of biometric parameters as well as metal and protein concentrations were analyzed in the liver cytosol of indigenous European chub (Squalius cephalus L.). Fish sampling was carried out in the reproductive (spring) and non-reproductive period (autumn) in order to define parameters which are seasonally dependent. The specimens caught in the spring period had higher biometric (liver mass, condition and hepatosomatic indices) and some biochemical parameters (metallothionein (MT) and Mn) that are characteristic for the reproductive period. Contrary, Fe hepatic cytosolic concentrations were significantly lower in specimens from spring than in autumn period. Total cytosolic proteins, Cu and Cd concentrations were not seasonally dependent. Range of constitutive levels was determined for total cytosolic proteins (17.7 to 24.7 mg ml(-1)) from the whole set of data. Constitutive range of seasonally dependent parameters MT (207 to 337 microg ml(-1)) and Mn (0.11 to 0.19 microg ml(-1)) is based on the data from non-reproductive period. In order to avoid the interference of reproductive cycle on the level of selected biochemical parameters, it is recommended to perform chub sampling during non-reproductive period.