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Energy stands as an indispensable global need, yet the finite nature of rapidly depleting fossil fuel reserves poses environmental challenges. To address this, numerous nations are shifting toward sustainable energy sources to foster environmental well-being while satisfying their energy requirements. Among these alternatives, wind energy emerges as a particularly efficient option. This study focuses on identifying optimal sites for installing wind power plants in Adana province through the integration of the analytic hierarchy process (AHP) and geographic information system (GIS). Within this framework, a comprehensive set of 15 criteria was delineated along with their respective sub-criteria. It is thought that the criteria used in the study will be useful not only for Adana province but also for other provinces that are suitable for wind turbine placement and planned to be built. The outcome of this investigation delineates potential areas in Adana province deemed suitable for establishing wind power plants. As a result, analysis reveals that 9.94% of the study area is conducive to establishing a wind farm (WF), while 51.66% is deemed moderately suitable. Notably, the districts of Feke, Tufanbeyli, Saimbeyli, and Pozantı emerge as particularly well-suited for this purpose. This study aims to contribute to the existing literature by identifying precise and suitable areas by combining GIS and AHP in the WF site selection process. In the study, a new research perspective is presented by taking into account the uncertainty in the site selection process and the concept of sustainability in three different dimensions: technical, economic, and environmental, thus aiming to guide decision-makers for future WF projects. In addition, it is thought that the methods and criteria used in the study will also be guiding for future WF site selection studies. [ABSTRACT FROM AUTHOR]

Sustainable transportation is vital to climate justice and social equity. Despite the efforts to achieve sustainability, there is still a lack of adequate measurement that integrates land use and transportation systems, which can be barriers to planning implementation. With methodological improvements in fuzzy theory application, this study develops an integrated index to measure the sustainability of multimodal accessibility. We do so by defining a fuzziness degree based on the different trip purposes and modes of transportation with a case study in Isfahan, Iran. Sustainable accessibility indicators were developed for walking, biking, and public transportation to represent the performance of each transportation system, considering the integration with land-use patterns. We analyze transportation modes and the accessibility to five main urban activities, including employment opportunities, education, healthcare, shopping, and recreation services, based on the travel distances, followed by a statistical integration method with Principal Components Analysis (PCA) for each travel mode. The outcome provides insights for urban planners and transportation planners to effectively evaluate the degree of integration between transportation and land-use systems and contribute to enhancing sustainable accessibility. [ABSTRACT FROM AUTHOR]

Soil moisture plays a critical role in agricultural productivity and water resource management, especially in a diverse and populous country like India. Understanding variations in soil moisture across different regions and seasons is essential for adapting agricultural practices and water management strategies to local conditions. This study examines changes in soil moisture levels across India, comparing contemporary data from 2023 with historical averages from 2000 to 2005 using advanced remote sensing and GIS technologies. The primary objective of this study is to identify Soil Moisture Anomalies (SMA) across India, quantify their impacts on agriculture and water resources, and provide recommendations for targeted management strategies. By comparing recent soil moisture data against historical averages, the study aims to highlight trends and changes that could influence future water resource planning and agricultural practices. The research utilizes data from the Famine Early Warning Systems Network's (FEWS NET) i.e. Land Data Assimilation System (FLDAS), obtained from NASA's data archives. The study employs a systematic approach to analyze seasonal variations in soil moisture across different Indian states. Soil moisture levels were analyzed using zonal statistics in GIS to classify regions into categories based on the degree of anomaly observed. This classification helped in understanding the spatial distribution of soil moisture during the pre-monsoon, monsoon, and post-monsoon seasons. The study found significant regional and seasonal variations in soil moisture across India. During the monsoon period, areas such as Bihar and Jharkhand consistently showed significant moisture deficits, indicative of drought conditions, affecting agricultural output and necessitating urgent water conservation measures. Conversely, regions like Punjab benefited from positive soil moisture anomalies, enhancing agricultural productivity. The pre-monsoon and post-monsoon seasons also showed variations, with some areas experiencing deficits requiring careful water management while others had surpluses that increased the risk of flooding. The analysis of SMA in India underscores the need for region-specific agricultural and water management strategies that consider significant variability in soil moisture conditions. The study highlights the importance of integrating soil moisture monitoring into national policy frameworks to enhance climate resilience and sustainable agricultural practices. Future research should focus on updating soil moisture assessments with more recent data and refining predictive models to improve the accuracy and effectiveness of water management and agricultural interventions. [ABSTRACT FROM AUTHOR]

Within the global architecture, engineering, and construction industry, the use of Building Information Modeling (BIM) technology has significantly expanded. However, given the unique characteristics of road infrastructure, the application of BIM technology is still being explored. This article focuses on the Yuanchen Expressway, exploring innovative applications of BIM technology in comprehensive construction management. The project employs advanced technologies, including BIM, Geographic Information Systems (GIS), and the Internet of Things (IoT), to precisely identify critical nodes and breakthroughs. Supported by a detailed BIM model and a multi-level, diversified digital management platform, the project effectively addresses construction challenges in multiple tunnels, bridges, and complex interchanges, achieving intelligent construction innovation throughout the Yuanchen Expressway with BIM technology. By guiding construction through BIM models, utilizing a BIM+GIS-based management cloud platform system, and employing VR safety briefings, the project effectively reduces the difficulty of communication and coordination in project management, shortens the project measurement cycle, improves on-site work efficiency, and ensures comprehensive control and safety management. This article provides an exemplary case for the application of full-line construction management using BIM technology in the highway sector both in China and globally, offering new perspectives and strategies for highway construction management. [ABSTRACT FROM AUTHOR]

Flash flood is the most recurrent natural threat in northeastern India, especially during the peak of the monsoon season. In recent decades, the frequency of flash floods has considerably increased in the Himalayan watersheds, causing enormous human suffering, infrastructure damage, ecosystem disruption, and economic losses. Considering the exponential rise in the frequency of flash flood events, identifying the Flash Flood Vulnerable Zones (FFVZs) is one of the most crucial findings to limit their negative consequences. In this study, grey fuzzy analytic hierarchy process-based model integrated with the geographic information system is implemented to assess the flash flood vulnerability in the Ranikhola watershed, East Sikkim, India. Additionally, a novel Flash Flood Vulnerability Index (FFVI) is proposed to determine the flash flood vulnerability that takes into account twelve natural and anthropogenic parameters. Further, the FFVI map is classified into three FFVZs: low, moderate, and high. The effectiveness of the methodology implemented is judged by the high EV value (6.4286) and the comparison parameter. The harshest conclusion of this analysis, the major cities, such as Gangtok, Ranipool, and Singtam, are designated high FFVZ. The sensitivity analysis results show the LULC has the maximum positive influence on high FFVZ. [ABSTRACT FROM AUTHOR]

Water resource management relies heavily on the utilization of decision-making systems to guide the strategic rehabilitation and renovation of infrastructure within water distribution networks (WDNs). This study aims to develop and apply a scripting tool in ArcGIS for decision-making in WDN. It combines a collection of decision support systems, including Geographic Information Systems (GIS) and multi-criteria analysis, for infrastructure renovation and rehabilitation. The research is divided into two main sections. The first focuses on creating and implementing the analytic hierarchy process tool in ArcGIS, while the second discusses its application in the study area, which is the drinking water distribution network of an urban area in Tlemcen, located in the Northwest of Algeria. The study's results reveal that 25% of the network is in critical condition and require immediate rehabilitation. Sixty-two percentage of the network is classified as moderately urgent, indicating a pressing but less immediate need for intervention. Finally, the remaining 13% of the network requires attention over a longer timeframe for rehabilitation. The main criteria influencing pipe prioritization are material (26% of total weight), laying date (26% of total weight), and pressure (20% of total weight). This developed tool can be easily adapted and applied by engineers and water management officers. It serves as a guide for decision-makers and planners in urban water management in Tlemcen and can be replicated and applied to other areas worldwide. [ABSTRACT FROM AUTHOR]

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In this paper, we analysed the temporal and spatial distributions of ancient archaeological sites in China as well as their influencing factors. Our aim was to reveal the developmental trajectory of Chinese civilisation and to explore the natural and cultural factors affecting human distribution, with the goal of providing insights for the conservation and development of ancient relics. We employed spatial analysis methods using ArcGIS 10.8 software, such as kernel density analysis and trend surface analysis, to analyse 1194 historical ancient sites listed in the National Cultural Relics Protection Units of China. The research findings are as follows: (1) the distribution of ancient sites demonstrates an agglomerative spatial pattern. The nearest neighbour index (R < 1) for sites from various historical periods indicates an agglomerative spatial distribution of ancient sites across historical periods, with the clustering degree being relatively poor for sites from the Wei-Jin, Northern and Southern Dynasties and in the Ming and Qing periods. The regions with a concentration of ancient sites are the middle and lower reaches of the Yangtze River and Yellow River Basins. Furthermore, there is a higher abundance of ancient sites in the southeastern region than in the northwestern region. (2) The distribution of ancient sites in different historical periods also exhibits an imbalance, with an overall decreasing trend in the number of ancient sites in China. Notably, more ancient sites were found for the prehistoric and pre-Qin periods. The temporal trend of ancient sites during historical periods follows a trajectory from northeast to northwest, northeast to southwest, etc. (3) The temporal and spatial distributions of ancient sites are influenced by multiple factors, including social development, the natural environment, geographical elements, and socioeconomic and political factors. Finally, based on an understanding of the spatiotemporal distribution pattern of ancient sites and the factors that influence this pattern, recommendations for conservation and development can be proposed and supported by modern technological methods, with the aim of offering insights for the protection and sustainable development of heritage sites. [ABSTRACT FROM AUTHOR]

Electric grids with buses that are mapped to geographic latitude and longitude are useful for a growing number of applications, such as data visualization, geomagnetically induced current calculations, and multi-energy coupled infrastructure simulations. This paper presents a methodology for validating the quality of geographic coordinates for a power system model, and to assign coordinates to buses with missing or low-quality coordinates. This method takes advantage of geographic indicators already intrinsic to a grid model, such as branch length as implied by impedance and susceptance parameters. The coordinate assignment process uses an approach inspired by graph drawing, that lays out the vertices (buses) and edges (transmission lines), formulated as a nonlinear programming problem with soft edge length constraints. The layout method is very computationally fast and scalable to large power system cases. The method is demonstrated in this paper using a 37-bus test case and a 6717-bus test case, both publicly available, along with a large actual grid model. The results show that, for cases with only a few errors in the coordinates, cases with no coordinates known beforehand, and others in between, this method is able to assign reasonable geographic coordinates to best match known data about the grid. [ABSTRACT FROM AUTHOR]

The sustainability of maritime activities is increasingly gaining interest, with the shipping sector actively focusing on decarbonization efforts. Throughout the years, researchers have considered slow steaming for improving the environmental footprint of maritime networks. In order to assess such strategies' effectiveness on existing emissions, research also focuses on the accurate estimation of emission inventories. However, there is a significant gap concerning both fields when considering short-sea shipping, especially passenger shipping. Furthermore, while emissions are characterized by spatial aspects in several studies, there is an apparent gap in considering such aspects for detailed analysis purposes rather than only for visualization purposes. In this study, the Greek Coastal Shipping Network (GCSN) is considered, with its emissions estimated using a top-down method, creating a spatial emission inventory used for further spatial analysis for accurate identification of highly polluted areas. Results indicate that ship emissions do not spread homogeneously throughout the GCSN and that targeted interventions are necessary in several areas of the network. The effectiveness of spatially related slow steaming implementations is evaluated and compared with their implementation on the whole network. The study highlights the need for additional future emission mitigation strategies, such as service optimization, network restructuring, continuous emission monitoring, and fleet renewal with more environmentally efficient ships. The study's aim is to fill the research gap regarding the environmental assessment of passenger shipping and the effects of slow steaming on such networks while presenting an adaptable GIS-based decision support system for enhanced decision-making regarding the environmental efficiency of maritime networks. [ABSTRACT FROM AUTHOR]

The present study implements a methodology to estimate water quality values using statistical tools and remote sensing techniques in a tropical water body Sanalona. Linear regression models developed by Box-Cox transformations and processed data from LANDSAT-8 imagery (bands) were used to estimate TOC, TDS, and Chl-a of the Sanalona reservoir from 2013 to 2020 at five sampling sites measured every 6 months. A band discriminant analysis was carried out to statistically fit and optimize the proposed algorithms. Coefficients of determination beyond 0.9 were obtained for these water quality parameters (r2TOC = 0.90, r2TDS = 0.95, and r2Chl-a = 0.96). A comparison between the estimated and observed water quality was carried out using different data for validation. The validation of the models showed favorable results with R2TOC = 0.8525, R2TDS = 0.8172, and R2Chl-a = 0.9256. The present study implemented, validated, and compared the results obtained by using an ordered and standardized methodology proposed for the estimation of TOC, TDS, and Chl-a values based on water quality parameters measured in the field and using satellite images. [ABSTRACT FROM AUTHOR]

Expressway construction has caused a significant threat to the ecological environment in developing countries, and therefore the variation characteristics of ecological resilience along the expressway in developing countries are of major importance. This empirical study focuses on a typical area within a 2-km range of the Phnom Penh-Sihanoukville Expressway in Cambodia and uses remote sensing and geographic information systems (GIS) technology to analyze the variation characteristics of ecological resilience along the expressway. The results of the study reveal that due to the construction of expressways, the land use types transferred into or out of the land use types increase and furthermore the land use types show a trend of decreasing natural attributes and increasing human attributes. It is found that expressway construction has an observed effect on the transfer rate of the center of gravity of land use type, and the direction of the center of gravity shifts in the direction of expressway construction. The impact of construction on the ecological resilience of the western region with higher vegetation coverage was higher than that of the eastern region with higher urbanization. The research develops a theoretical evaluation model based on land use type of the variation characteristics of ecological resilience along the expressway, which can be used to enable the sustainability of expressway construction and maintain the regional ecological environment. [ABSTRACT FROM AUTHOR]

Over the past decade, geospatial technologies have emerged as a tool for developing spatial reasoning and cognitive processes. While the foundational Learning to Think Spatially report from the National Research Center (2006) launched research into the use of geospatial technologies in isolation, more recently, cloud-based simulation software have begun to partner with geographic information system (GIS) databases to aid instructional designers in creating simulations in fields such as geology and geography. Both of these use cases - traditional geography instruction and immersive simulations - undervalue the potential of GIS to address larger issues within the Instructional Design and Technology (IDT) field. This conceptual paper seeks to present the potential of GIS systems as a designerly tool which can be used to reduce the cognitive load of communicating with very complex data sets and effectively show how information dynamically changes over time. Provisioning contextual analysis as a central skill of the designer may lead to more inclusive designs than a focus on adding steps to process-based models or focusing only on tools. [ABSTRACT FROM AUTHOR]

Desertification assessment is vital to develop actions plans aimed to prevent desertification issues. Utilizing Geographic Information Systems (GIS) to manipulate and analyze data retrieved from various sources of data including satellite images and thematic maps, as well as the use of remote sensing through satellite images to retrieve environmental information on the earth's surface, are crucial tools to understand related environmental dangers, which is used to monitor desertification and investigate different desert conditions. In this study, different physical and environmental factors associated with land desertification including vegetation cover, water, drainage systems, geomorphology, and soil moisture, were extracted and evaluated using various remote sensing techniques. In addition, multi-temporal analysis of Landsat TM data is used in this study to examine the state of vegetation and growth of irrigated area between 1983 and 1997. A GIS tool is utilized to aggregate and analyze different factors including soil, land use, and climate. A decrease in vegetation cover was clearly observed based on these analysis results. A severe desertification of the natural vegetation cover is the primary cause of this predicament. Finally, many maps describing the actual situation of study area is obtained following the GIS layers examination, however, the most important maps are soil erosion, vegetation degradation, salinization and desertification. [ABSTRACT FROM AUTHOR]

Invasive Hieracium plant species are invading the Greater Yellowstone Ecosystem. The potential distribution of orange hawkweed (Hieracium aurantiacum) and meadow hawkweed (Hieracium caespitosum) were estimated using habitat susceptibility models to assist land managers' management of these invasive plants. The objectives of this study were to: (1) develop models describing susceptibility of ecosystems to hawkweed invasion, (2) identify indicator species of orange hawkweed and meadow hawkweed, (3) determine habitat types where these invasive hawkweeds might occur, and (4) create habitat susceptibility maps for management planning and ground surveys. Models were developed using a Mahalanobis distance similarity technique from remotely sensed biotic and abiotic variables, as well as known location data for orange and meadow hawkweed. Ground validation was conducted to assess model weaknesses and subsequent model modification. Indicator plant species were identified as surrogates to determine the likelihood of hawkweed presence during ground survey. Transect data collected from areas susceptible to invasion also were used to determine habitat types where hawkweed might occur. The best model included eight variables: north–south aspect, east–west aspect, slope, NDVI, NDWI, blue spectral band, green spectral band, and precipitation. High susceptibility (65 + % likelihood of suitable habitat) consisted of 66,000 ha for meadow hawkweed and 35,000 ha for orange hawkweed, 5.0% and 2.7% of the study area, respectively. Meadow hawkweed and orange hawkweed had seven and three indicator plant species, respectively. Predicted hawkweed habitat susceptibility encompassed nine habitat types, ranging from xeric sagebrush steppe to wet forests and they overlapped except at the xeric habitat type. Habitat susceptibility models save costs and allow survey prioritization to those areas most susceptible to invasion. [ABSTRACT FROM AUTHOR]

Since the last two decades, Pakistan has been often cited among the top ten countries most vulnerable to climate change and disasters, such as intense flooding, extreme heat, and droughts, among others. However, the unavailability of nationwide administrative-scale assessments from a space–time perspective hinders disaster resilience building in Pakistan. In this context, the key purpose of this study is to evaluate the spatial and temporal disparities in community disaster resilience (CDR) in Pakistan during 2004–2014—the period covering two of the most devastating disasters in Pakistan in recent history. Eventually, the dynamic nature of resilience is empirically demonstrated through the catastrophe progression method, and regions, where resilience increased/decreased, are identified using geo-information models, such as the Moran's Index and the local indicators of Spatial Association (LISA). It is evident that CDR in the earlier, middle and final periods during 2004–2014 vary significantly (95% confidence). With inconsistent resilience distribution across Pakistan during 2004–2014, some noteworthy regional disparities are also found. For instance, while the overall lowest resilience is found for the areas in Balochistan province, the regions that became less resilient during the studied period are spread across Pakistan with notable concentrations in southern districts. Such place-based information is a crucial stepping-stone to initiating and formulating effective plans and resilience enhancement strategies in Pakistan. Furthermore, based on the pioneering analysis presented here, this study acts as a baseline for disaster resilience in Pakistan in terms of spatial–temporal heterogeneities along with pinpointing the significant areas for gradual or immediate attention—facilitating priority intervention areas. [ABSTRACT FROM AUTHOR]

Solar energy is among the sustainable and renewable energy sources that has become an important and inevitable part of our lives today. It is of great importance to consider economic, environmental, and social factors in determining the installation locations of solar power plants (SPP). In this study, we aimed to determine suitable areas where SPP can be established in Safranbolu District by using the fuzzy analytical hierarchy process (FAHP), which is one of the multiple criteria decision making (MCDM) method together with Geographic Information Systems (GIS), to enable the decision-makers to express their preferences in approximate or adaptable ways. The criteria addressed in the technical analysis process were also determined by supporting the basic principles of impact assessment systems. Within the scope of the environmental analysis, the relevant national and international legal frameworks were also examined and the legal constraints were identified. Thus, in the process of determining the optimal areas for SPP, it has been attempted to produce sustainable solutions that are expected to have minimal impact on the integrity of the natural system. This study was carried on within a scientific, technical, and legal framework. According to the results obtained, the Safranbolu District had low, medium, and high sensitivity properties for SPP construction, and the areas suitable for SPP construction provided medium and high sensitivity of 10.86% and 27.26% correspondence detected according to the Chang (Eur J Oper Res 95(3): 649-655, 1996) and Buckley (Fuzzy Set Syst 17(3): 233-247, 1985) methods, respectively. There are very suitable areas for SPP installations in the central and western parts of Safranbolu District, and there are also areas suitable for SPP installation in the northern and southern parts of the district. Thanks to this study, suitable SPP establishment areas were determined for the under protection in a location in Safranbolu where clean energy is needed. It was also observed that these areas do not conflict with the basic principles of impact assessment systems. [ABSTRACT FROM AUTHOR]

Geospatial models can facilitate the delineation of food access patterns, which is particularly relevant for urban planning and health policymaking. Because community food environmental studies use different analysis units or study scales, the rigor and consistency of their evaluations cannot be ensured. This issue is known as the modifiable areal unit problem (MAUP). The paper provides a systematic review of past literature on place-based community food environmental research using different analysis units or geospatial models as they pertain to the MAUP. We identify these key findings: (1) the ZIP code zone is not recommended as an appropriate analysis unit for modeling community food access, as it did not have significant correlations with health indicators; (2) using a circular buffer of less than 0.5 km around household locations is most likely to reveal health correlations, compared with network buffers or container-based measures; (3) to reveal health effects of the community food environment, it is recommended to focus in selected regions or partitions of a study area with similar socioeconomic statuses, such as the central city or low socioeconomic status areas; (4) for studies utilizing a single statistical unit or distance measure, it is suggested to discuss the existence of the MAUP, such as evaluating the sensitivity of the model to the change of the unit or the distance measure. By highlighting the MAUP, this paper has policy implications—given that geospatial modeling of food accessibility provides support for health policy intervention, using different metrics may lead to different interpretations of health disparities and could thus misinform policy decisions. Therefore, any assessment of community food environments that may potentially lead to a policy change should consider the effects of the MAUP. [ABSTRACT FROM AUTHOR]

The aim of this study was to improve our understanding of factors that affect the spatial distribution of wildfire occurrences at the regional scale. We employed the random forest, boosted regression tree, and genetic algorithm rule-set production models to assess the spatial interplay between fire events and climate, topography, and anthropogenic factors in order to characterize wildfire occurrence in the Zagros eco-region of western Iran. We constructed a geospatial database using the historical fires from the period 2007–2020 and topography, climate, and human related factors. The results demonstrated that human activities (i.e., land use and distance from the settlements and roads) contributed 45% to the probability model of wildfire occurrence in the study region. The models ranked the climate factors (rainfall, temperature, and wind effect) as the second most influential drivers of fire occurrences, whereas topographic features (slope, elevation, and aspect) did not significantly influence fire probability in the landscape. Overall model performance was assessed with the area under the receiver operating characteristic (AUROC) method that showed the superior performance of the RF model in the training phase (AUROC = 0.92) and in its ability to predict upcoming fires (AUROC = 0.90). The insights obtained from this research can bring into focus both the locations and the types of suppression policies that are required to alleviate the effects of the upcoming wildfires in the early twenty-first century. [ABSTRACT FROM AUTHOR]

The archaeological study of "the West" and "the frontier" provides a bounty of research questions. However, as researchers delve into issues of culture contact, colonization, and conflict, they must consider the power embedded in the ideologies of the West and the frontier. As metaphors, these terms allow for the reflexive examination of one's research questions. Using the Paoli Battlefield, a Revolutionary War site in southeastern Pennsylvania, as a case study, this analysis aims to challenge current notions of the West and the frontier. Specifically, by examining the cultural landscape in conjunction with a landscape of conflict, the study challenges the frontier metaphor. Moreover, by using geographic information systems (GIS) to map and model the cultural landscape, researchers glean interpretations of the Paoli Battlefield in an innovative manner that promotes new considerations for conflict archaeology. [ABSTRACT FROM AUTHOR]

In the present study, we aimed to understand the current condition of land suitability and how climate change will affect its suitability for rice paddy cultivation in the Edirne Province of Turkey in the future. We used RS and the GIS-supported FAO Maximum Limitation Approach to perform land suitability analysis for the current conditions and 20-year periodic times from 2020 to 2100. The results of the current land suitability assessment indicated that 81.39% of the study area is suitable for rice paddy cultivation. Two climate change models (HadGEM2-ES and MPI-ESM-MR) and related scenarios RCP4.5 and RCP8.5 showed that the climate conditions in the region will change significantly, therefore, the suitable lands for rice paddy cultivation in the study area will increase. However, the amount of change varies across models and scenarios. Further land suitability for rice paddy cultivation in the study area will be positively affected by temperature and solar radiation changes and negatively affected by changes in humidity and precipitation. Lastly, the agricultural irrigation infrastructure is expected to be unfavorably affected by an increase in extreme climatic events. These findings can guide policymakers and stakeholders to select suitable land for future rice paddy cultivation. To adapt to climate change and reduce its effects, we recommend choosing an agricultural production model that is suitable for climate change scenarios. [ABSTRACT FROM AUTHOR]

Coastal plastic debris is a major problem affecting both sandy beaches and nearshore environments. Over several decades, plastic debris has become a global threat to the natural environment due in part to single-use culture, pervasiveness and accumulation following years of improper disposal. Despite the global research effort, in the Caribbean region, only a few studies attempt to quantify the amount and sources of debris. This paper combines coastal geomorphology and plastic debris collection with GIS spatial analysis at Maracas Beach, Trinidad between 2015 and 2016. Overall, 567 separate plastic items were captured and classified from within two 30 m wide zones at the central and eastern portions of the microtidal sandy beach. Macro- and meso-plastic debris associated with beach activity (n=233) and single use waste (n=215) were the most abundant debris. Microplastic debris (n=94) consists mainly of polystyrene granules and unidentifiable fragments from larger recreational debris that are readily lost to the environment. Using manufacturer’s information, polystyrene (n=206) was the most dominant debris. Regression models were also conducted using the average beach size and average beach angles where a weak positive linear relationship was found. Kernel density estimation was used to geovisualize the distribution of plastic items per square metre to develop a plastic debris signature. Despite current beach management activities, a large proportion of macro- and meso-sized debris can enter the environment. Studies such as these are invaluable for the Caribbean region where attempts to manage the pollution caused by plastic are limited by data. [ABSTRACT FROM AUTHOR]

Water depths and flow velocities decisively influence the damage caused by flash floods. Geographic Information System (GIS) is a powerful and useful tool, allowing the spatial analysis of results obtained by hydraulic modelling, namely from the HEC-RAS/HEC-GeoRAS software. The GIS spatial analysis performed in this study seeks to explain and quantify the spatial relationships between the stream channel features and flow components during flash flood events. Despite these relationships are generically known, there are few studies exploring this subject in different geographic contexts. A 1D hydraulic model was applied in a small watershed in Portugal, providing good results in the definition of floodable areas, water depths and longitudinal velocities. No direct relationship was found between water depths and velocities in the floodable areas; however, negative strong correlations were found between the two flow components along the stream centerlines. Bed slope, channel and flood width, and roughness prove to be highly relevant on the longitudinal variations of water depths and velocities and on the location of maximum values. Increasing peak discharges and return periods (RT) can change the relationships between water depths and velocities at the same location. Results can be improved with more accurate elevation data for stream channels and floodplains. [ABSTRACT FROM AUTHOR]

We present efficient algorithms to compute simple and complex map algebra operations over raster data stored in main memory, using the k2-acc compact data structure. Raster data correspond to numerical data that represent attributes of spatial objects, such as temperature or elevation measures. Compact data structures allow efficient data storage in main memory and query them in their compressed form. A k2-acc is a set of k2-trees, one for every distinct numeric value in the raster matrix. We demonstrate that map algebra operations can be computed efficiently using this compact data structure. In fact, some map algebra operations perform over five orders of magnitude faster compared with algorithms working over uncompressed datasets. [ABSTRACT FROM AUTHOR]

The current study aimed to simulate the rainfall–runoff events in two catchments (Daraja and Al-Ghar) of Palestine using HEC-HMS model during 1990‒2010 data period. Main inputs to the model included soil properties, land use land cover, stream network, slope in addition to rainfall data, and physical catchment characteristics. The model was calibrated and validated on total of 20 rainfall–runoff events from both catchments. Model efficiency was estimated through accuracy percentage, Nash–Sutcliffe (NS), and coefficient of determination (R2). Simulation indicated acceptable model efficiency with NS (R2) value ranged between 0.78‒0.96 (0.79‒0.98) and 0.88‒0.94 (0.91‒0.98) for Daraja and Al-Ghar catchments, respectively, over entire data period. Outcomes of the study suggested that HEC-HMS model calibrated during this study may be used for forecasting the flows on short time-step with future climatic scenario in the similar environments and may be helpful for water resources manager to predict and mitigate the flood risk. [ABSTRACT FROM AUTHOR]

Liquefaction is one of the seismic-based disasters that has devastating economic and human life consequences. Artificial neural networks (ANN) are one of the computational methods used in liquefaction assessments. A wide range of optimization methods were used to gain the best prediction capability for ANN models. Although response surface methodology (RSM) is a widely used optimization method, a limited number of studies use RSM to optimize ANN models. This study was intended to suggest a computational model for liquefaction potential assessments. Within this scope, an ANN model was coded and optimized using the RSM. Erzurum is one of the seismically active provinces of Turkey as it is located in the East Anatolian Tectonic Structure. However, the liquefaction potential of the city has not been thoroughly examined so far. The geotechnical investigation was performed for Erzurum City Center. The specific objectives of this study are to (1) suggest a new ANN-based cyclic stress ratio (CSR) estimation method, (2) examine the usability of RSM in optimization of ANN models, and (3) perform liquefaction assessments for Erzurum City Center using the suggested method. In this context, 55 boreholes were drilled in various points of the city center. Groundwater level, soil type, and SPT-N values were determined for various depths of the boreholes. Liquefaction assessments were carried out for various earthquake scenarios (M = 6.0, 6.5, 7.0, and 7.5), considering the liquefaction severity index. Locations susceptible to liquefaction were summarized with tables and liquefaction potential maps. Liquefaction assessment maps were drawn using geographic information systems (GIS). As a result of the study, it was seen that the suggested ANN-based algorithm gives accurate results, and RSM can be used to optimize artificial neural nets efficiently. [ABSTRACT FROM AUTHOR]

Cultivation-based land suitability has become an essential research topic because of increased interest in agricultural sustainability and negative environmental effects due to rapid population growth and a decrease in arable lands due to urbanization. Therefore, this study investigates land suitability for the olive plant, which has a high economic value in the Mediterranean city of Mersin, Turkey. First, areas that cannot be cultivated were excluded from the study using exclusion analysis so that only agricultural areas were included in the analyses. Afterward, the weightage of the meteorological, topographic, soil, and infrastructural and economical criteria were determined using the analytic hierarchy process (AHP), and a land suitability map for olive cultivation was created using Geographic Information Systems (GIS). The resulting map showed that 2.72% (438.12 km2) of the study area is very suitable for olive cultivation and 0.99% (159.28 km2) is very unsuitable. It was determined that the Tarsus region, located in the east of the study area, and the Mut region, located in the northwest, have very suitable land for olive cultivation. [ABSTRACT FROM AUTHOR]

Global warming has become the center of worldwide environmental concerns, especially in recent years. One of the ways to deal with global warming that causes climate change is to adopt the renewable energy power technique. Different renewable energy sources such as solar, wind, hydro, ocean, geothermal, and bioenergy are currently the backbone of green and sustainable economic growth. However, renewable energy sites are directly or indirectly dependent on environmental, social, and technical criteria.The main objective of this paper is to identify potential best renewable energy site alternatives using the maximum entropy model (MaxEnt) and Geographical Information systems (GIS). Thus, the framework formed by the findings will guide investors in the renewable energy sector. The results showed that suitable areas for solar and wind were mainly located in the Hatay and Mersin of the Eastern Mediterranean Region in Turkey. The energy suitability site maps indicate that 8% (3.42 km2) and 3.39% (1554 km2) of the total study area have suitability and very suitability for solar and wind energy respectively. Moreover, it is seen that 44.82% (20,689km2) of the regions are the same when suitable and very suitable regions are overlaid for the installation of solar and wind energy sites. The receiver operating characteristic (ROC) curve was used to evaluate model performance. The area under the curve (AUC) values are calculated 0.87 and 0.95 for solar and wind energy, respectively. Relying on realistic data, this paper proposes an innovative method to identify suitable areas for solar and wind power plants. The maps obtained to contribute to renewable energy production will be useful for creating future strategies in the Mediterranean region. [ABSTRACT FROM AUTHOR]

An emerging priority in marine noise pollution research is identifying marine "acoustic refugia" where noise levels are relatively low and good-quality habitat is available to acoustically sensitive species. The endangered Southern Resident population of killer whales (Orcinus orca) that inhabits the transboundary Salish Sea in Canada and the USA are affected by noise pollution. Geographic Information Systems (GIS) and spatial multicriteria evaluation (MCE) methods have been used to operationalize suitability analysis in ecology and conservation for site selection problems. However, commonly used methods lack the ability to represent complex logical relationships between input criteria. Therefore, the objective of this study is to apply a more advanced MCE method, known as Logic Scoring of Preference (LSP), to identify acoustic refugia for killer whales in the Salish Sea. This GIS-based LSP-MCE approach considers multiple input criteria by combining input data representing killer whale habitat requirements with noise pollution and other factors to identify suitable acoustic refugia. The results indicate the locations of suitable acoustic refugia and how they are affected by noise pollution from marine vessels in three scenarios developed to represent different levels of vessel traffic. Identifying acoustic refugia can contribute to efforts to reduce the effect of marine noise pollution on killer whale populations by highlighting high-priority areas in which to implement policies such as traffic-limiting measures or marine protected areas. Moreover, the proposed LSP-MCE procedure combines criteria in a stepwise manner that can support environmental management decision-making processes and can be applied to other marine suitability analysis contexts. [ABSTRACT FROM AUTHOR]

A geographic information system (GIS) approach systematically assessed whether population density and distribution of community resources contributed to caregiver reported community participation outcomes for 124 adults with autism spectrum disorder (ASD). Regression analyses examined whether GIS measures predicted community participation in areas of social activities and use of services, while also accounting for adult age, conversation ability, and daily living skills (DLS). Results indicated that in addition to person factors of greater DLS and better conversation ability, access to specific community features, such as bus stops, contributed to improved participation. Unexpectedly, population density where one lived made minimal contribution to participation outcomes, except in getting together with friends outside of organized activities. [ABSTRACT FROM AUTHOR]

This study investigated the possibility of using an intelligent transport system (ITS) and geographic information system (GIS) to increase the efficiency of the campus transportation at King Saud University in Riyadh, Saudi Arabia. The study yielded several findings, prior to the implementation of the GIS-based ITS, the time spent waiting for the university bus amounted to less than 5 min (19% of responses), 5–10 min (48%), 10–20 min (30%), and more than 30 min (3%). Regarding the bus arrival time at home, 62% of the female students did not know the bus arrival time, and 38% knew the bus arrival time. However, after the creation of an intelligent transportation system that sent an alert prior to the arrival of the bus in front of their houses, the time the female students spent waiting for the bus decreased significantly, reaching 14 min, in addition to the 10 min spent for the bus to move between houses. The constant factor before and after the ITS intervention was the total time required to pick up the female students, reaching 24 min, and the new system saved 43 min of daily trip time. [ABSTRACT FROM AUTHOR]

The need for renewable energy is continually increasing in developing countries. In Turkey, that need has been felt strongly for a long time. Due to various state's laws, regulations, and incentives, interest in renewable energies, especially solar energy, has been increasing rapidly since the 2000s. The annual amount of sun and therefore the solar potential in Turkey is quite high. In this context, it is crucial to identify suitable locations for solar farms in order to make maximum use of solar energy. The main objective of this study is to identify suitable potential sites for solar farms in the province of Antalya, which contains Turkey's fifth-largest city in terms of population. The geographic information system and analytical hierarchy process (AHP) were used to assess sites based on various logistical, geographic, and solar criteria. The map data used in the study were open access, and other data were obtained from local administrations. The sites in the study area were classified into four classes according to the results of the suitability index calculation: very suitable, suitable, less suitable, and not suitable. In total, 484,795 hectares, 24.02% of the study area were deemed suitable for solar farms, while 731,094 hectares (36.31%) were less suitable. Currently, very little of the suitable area is used for solar energy generation. The results of the study indicate that the province has a high potential in terms of solar energy. This is the most comprehensive study conducted in Antalya Province by using the widely preferred site selection criteria for solar farms together with AHP. [ABSTRACT FROM AUTHOR]

Flooding is one of the major issues in the low lying area of Indo-Gangetic Plain. The Ghaghara basin witnesses the floods every year in Indian sub-continent and has caused loss of numerous lives and land for several decades. It may not be stopped but can be preventive. The present study is an attempt to initiate the flood risk zonation by defining multiple criteria for evaluating this major issue in Ghaghara basin, Uttar Pradesh, India. The work was done using Geographic Information Systems (GIS), Remote sensing (RS) data of (Linear Imaging Self Scanning) LISS III, SRTM (Shuttle Radar Topography Mission) data, and Survey of India (SOI) toposheet. The yearly average interpolated rainfall and multiple themes like slope, micro-watersheds, drainage density, land use/land cover (LULC), soil moisture, and soil surface texture were used to delineate the flood hazard risk zonation map. The study identified promising results for the establishment and categorization of flood risk zones into very low hazard risk zone (4%), low hazard risk zone (8.5%), moderate hazard risk zone (23.6%), high hazard risk zone (42%), and very high risk zones (21.9%). It is estimated on the basis of the study that ~27,490 localities were influenced by floods along the major channels, i.e., Ghaghara, Sarda, and Rapti. The results of this study could allow better relief operations and reduce the risk of flooding. [ABSTRACT FROM AUTHOR]

As landfill site selection is complicated action and needs attention to various local and non-local conditions such as social, economic, technical and environmental issues; it will require an applicable method, which is able to make proper connection between aforementioned conditions to help engineers in making the most appropriate decision about landfill site. The present study has used a mixture of GIS and multi criteria decision making system in context of the AHP method. So that site selection and prioritization of areas prone to construction of landfill were carried on at 3 stages according to violent morphological and often mountainous (Rudbar County) conditions. At the first stage, after collation of maps based on restriction criteria, improper areas for constructing the landfill were removed. At the second stage, by considering the dominant wind direction and proper area for landfill in a 20-year-old interval, those zones that their areas were more than 35 ha and were not located in the dominant wind direction, were identified as prone areas for constructing the landfill. At the last stage, among the selected areas, they were evaluated and compared by using hierarchical analysis, common standards and experts' comments. Eventually, the prioritization of prone areas was done based on qualitative classification: excellent, very good, good, average, and weak were different ranks in terms of suitability for constructing landfill. Based on obtained results, 0.41% of understudied regions were classified as weak areas, 0.89% was average, 1.07% was good, 0.70% was very good, and 0.76% was grouped in excellent class. [ABSTRACT FROM AUTHOR]

This is an introduction to the special issue entitled "Beyond (within, through) the Grid: Mapping and Historical Archaeology." The papers in this issue emerge from a 2017 Society for American Archaeology session, in which archaeologists considered the intersections of mapping and historical archaeology. In this volume, the papers expand upon these discussions and explore the ways in which mapping can generate new archaeological data and contribute to methodological and theoretical problems in historical archaeology. Together, they consider the interplay between visibility and invisibility, the visualization of embodied experience, mapping power and resistance, and the use of mapping in heritage practices. [ABSTRACT FROM AUTHOR]

In this study, we present a novel methodology that may be used to analyze tsunami risk along coastal regions. The application of the proposed methodology is demonstrated for the Eastern Mediterranean coast. Economic, social and environmental dimensions of risk are calculated and aggregated to obtain the overall risk maps for a number of elements at risk (EaR) that are identified from seven countries located along the Eastern Mediterranean coastline. Historical earthquakes that are recorded in the region during the period 1900–2013 are used as data, and probabilistic tsunami modeling is carried out using Monte Carlo analysis. Based on historical data, randomly generated earthquakes are simulated, and wave propagation analysis is performed using NAMI-DANCE software. Inundation depth–damage analysis and exceedance probabilities of tsunami inundations are used to evaluate social and economic risks while the environmental risk is calculated using a binary approach. The overall risk map is constructed in the geographic information system environment. Cairo Agricultural Area in Egypt and Fethiye City in Turkey are identified as high-risk EaR in the Eastern Mediterranean coastline. The new risk assessment methodology may be utilized in coastal regions of the world, and the results obtained for the Eastern Mediterranean may be effectively used in developing preventive measures and disaster management strategies for tsunamis that may develop the region. [ABSTRACT FROM AUTHOR]

Purpose: Epidemiological data on acromegaly therapeutic outcomes in real-life conditions are scarce in Brazil. Information on the geographical accessibility to the dispensation of medicines and its impact on biochemical control is also poorly known. We aimed to describe the clinical outcomes of long-term therapy in patients with acromegaly at a referral medical centre in Brazil and to perform a spatial analysis of patients according to the distance from home to the drug-dispensing pharmacies aiming to evaluate its impact on biochemical control. Methods: Global retrospective data analysis of 111 patients followed at the University Hospital of Brasília from January 1980 to March 2015 was performed, as well as a separate review of 17 new cases operated on from April 2015 to June 2019 according to surgery results. Spatial analysis of patients under pharmacological treatment applying Geographic Information System (GIS) software (ArcGIS, ESRI, Redlands, CA) was performed. Results: Considering surgery alone, the cure rate was 23% from 1980 to 2015 and 29.4% from 2015 to 2019. In the long-term follow-up of the 111 patients from 1980 to 2015, 25.2% (n = 29) were cured, 40.6% (n = 44) presented controlled disease and 34.2% (n = 38) were biochemically uncontrolled after a period of follow-up of 8.9 ± 6.4 years. Biochemical control obtained in patients on pharmacological treatment (n = 76) was 58% (n = 44) after 5.8 ± 3.8 years. The distance from home to the drug-dispensing pharmacy did not influence biochemical control (p = 0.7616). Conclusions: Most patients presented with disease under control. No evidence on the effect of the distance between home and drug-dispensing pharmacies on biochemical control was obtained. [ABSTRACT FROM AUTHOR]

Determining alternative water sources to meet municipal water demands is important when availability is limited. The purpose of this study was to demonstrate a means for water planners to estimate the amount of combined sanitary wastewater and storm water that they might already be capturing through open air oxidation ponds. Increased understanding of the quantity of water that is already available could help water planners to better envision optimal water reuse scenarios. Using water and climate data on oxidation ponds in these three cities within the Texas Panhandle from 2010 to 2014, we evaluated water quantities which would be available for potential reuse. From the net monthly wastewater volumes values, the study also considered if per capita demand could have been met by reusing the wastewater. The study found wastewater volumes were lower in fall and winter months and much higher in spring and summer months. If a city considers reusing wastewater, blue water (groundwater) extraction could be reduced by as low as 45–50% in one city to as high as 100% in another. Water planners in similar environments and wastewater treatment systems may find this demonstration of potential reuse water quantity encouraging for better meeting their own water demands and enhancing water supply resiliency. [ABSTRACT FROM AUTHOR]

This study is based on an area in Hatay, Turkey, and involves examining all weather and climate-related data that can be used to determine its suitability for the bioclimatic comfort. It attempts to explain bioclimatic comfort and describes in detail all the variables that make this contemporary concept and why it is important from a landscape architecture planning point of view. According to Köppen climate classification, the general climate character of the study area is classified as medium-altitude, warm summer, and climate type with mild or winters with Csa-Csb letters. As the area is very large in terms of total area, the findings were different across the whole area; which means that some parts were bioclimatic-comfort-friendly and other parts were not to varying degrees. June is the month in which suitable areas cover the province's largest area. Because temperatures have reached a suitable level in terms of climatic comfort, humidity and wind speed have increased. In climatic map result, it shows that Hatay is the highest region area with high altitudes of regions in the center. The examination for thermal comfort took place for months. Hatay's results show that it serves as a helper in future planning of landscape: planning that brings the comfort of bioclimatic to the level of highest and that helps determine new region settlement in Hatay. The study finally proposes that it paves the way for future researches and studies to ultimately standardize bioclimatic comfort in landscape architecture and urban planning that allows achieving the optimal planning objectives in all aspects. [ABSTRACT FROM AUTHOR]

Slope stability management systems (SSMSs) have been developed by multiple state transportation agencies to assess landslides adjacent to highways and aide in the effective allocation of resources for slope and/or roadway repairs. SSMSs catalog and analyze slope failures through the use of three main components: a landslide data collection system, a geographic information systems (GIS) database, and a hazard prioritization system. The components form a landslide management system used for the identification or prediction of landslide risk areas and the determination of landslide hazards to motorists. The Alabama Department of Transportation (ALDOT) has not previously employed a SSMS, which limits the ability of ALDOT engineers and geologists to effectively manage landslide hazards along highways. This paper discusses the development of a landslide collection system and database developed to improve the ability of ALDOT to identify common causes and locations of slope failures along Alabama highways. The collected data were converted into a GIS database, which allows for correlations between landslides and additional spatial data, such as average precipitation and surface geology. This paper presents a brief review of similar SMSSs, reviews the proposed database, and discusses preliminary observations. The data collected from this study can be used to identify common causes of landslides along Alabama highways and select efficient remediation options. [ABSTRACT FROM AUTHOR]

Purpose: We know little about how community structures influence the risk of common mental illnesses. This study presents a new way to establish links between depression and social fragmentation, thereby identifying pathways to better target mental health services and prevention programs to the right people in the right place.Method: A principal components analysis (PCA) was conducted to develop the proposed Australian neighborhood social fragmentation index (ANSFI). General practice clinical data were used to identify cases of diagnosed depression. The association between ANSFI and depression was explored using multilevel logistic regression. Spatial hot spots (clusters) of depression prevalence and social fragmentation at the statistical area level 1 (SA1) were examined.Results: Two components of social fragmentation emerged, reflecting fragmentation related to family structure and mobility. Individuals treated for depression in primary care were more likely to live in neighborhoods with lower socioeconomic status and with higher social fragmentation related to family structure. A 1-SD increase in social fragmentation was associated with a 16% higher depression prevalence (95% CI 11%, 20%). However, the association attenuated with adjustment for neighborhood socio-economic status. Considerable spatial variation in social fragmentation and depression patterns across communities was observed.Conclusions: Developing a social fragmentation index for the first time in Australia at a small area level generates a new line of knowledge on the impact of community structures on health risks. Findings may extend our understanding of the mechanisms that drive geographical variation in the incidence of common mental disorders and mental health care. [ABSTRACT FROM AUTHOR]

Although sound barriers have been installed along the noise-sensitive areas of the Taiwan High-Speed Rail (THSR) network, many residents complain about the noise. Therefore, this study explored noise levels along the THSR network in central Taiwan through noise measurements, noise simulations, and questionnaire survey. In addition, noise exposure population and effectiveness of regulation standards for THSR were evaluated. The results show that the measured noises were lower than the regulatory standards and the maximum noise level (Lmax) exceeded the background noise level by more than 20 dB(A). But the questionnaire survey revealed that within 100 m of the THSR track, 69% residents were highly annoyed by the noise. Such results implied that Lmax was possibly the main affect on the residents. In other words, the effectiveness of the Taiwan noise standard should be further assessed. Noise simulation software, SoundPLAN, can precisely predict the Lmax at the locations of residents, and then a relationship between Lmax and feeling of highly annoyed could be created for policy-making reference. [ABSTRACT FROM AUTHOR]

Understanding inequalities in spatial accessibility to prenatal care over space and time is critical for policymakers to plan a more effective distribution of health resources, improve access to prenatal care, and promote maternal and infant health. However, urban–rural inequalities in spatial accessibility to prenatal care have not been well studied. Using geographic information systems and the two-transportation-mode two-step floating catchment area method, we first assess and compare the spatial variation and urban–rural inequalities of spatial accessibility to prenatal care in Georgia for years 2000 and 2010. Then we designate census-tract-based prenatal care shortage areas that have both poor spatial accessibility and high demand population in each year. The results show that, for both years 2000 and 2010, spatial accessibility to prenatal care was best in urban core areas and decreased as rurality increases. However, the differences among suburban, urban influence, and rural areas were reduced over the decade. A total of eight census tracts, most located on the fringe of metropolitan Atlanta, had a prenatal care shortage in both years. According to the results, we suggest that spatial accessibility to prenatal care in non-urban-core areas in Georgia needs more attention from policymakers. [ABSTRACT FROM AUTHOR]

The study aims to evaluate the enforcement, opinions, and effectiveness of the University of South Florida's tobacco free policy one year following implementation. By assessing readiness to change and using geographic information system (GIS) mapping this study sought to introduce a unique and effective way of evaluating college tobacco free policies. A cross-sectional survey was administered to students, faculty, and staff to assess knowledge of policy and resources, tobacco use observations, stage change regarding policy enforcement, self-efficacy to enforce, and policy impact on perceived campus tobacco use (n = 5242). Additionally, using ArcGIS Collector (in: ESRI, ArcGIS desktop: release 10, Environmental Systems Research Institute, Redlands, 2011) volunteers collected geospatial data on tobacco use continuing to occur on campus following policy implementation. Overall there was moderate knowledge of the current policy and low beliefs for policy enforcement. Majority of respondents were not approaching violators to remind them of the policy and did not plan to do so in the future. There were statistically significant differences between smokers and non-smokers as well as between students and faculty and staff. The mapping of observed violations revealed continued tobacco use on campus with 158 data points. From both the geospatial results as well as the survey findings, the current policy is ineffective in reducing tobacco use across campus. With rapidly increasing numbers of smoke and tobacco free universities, new and innovative evaluation tools are needed so institution leaders can efficiently evaluate their implementation. [ABSTRACT FROM AUTHOR]

Complex hazards associated with climate change are increasing the vulnerability of urban coastal areas around the globe. This was particularly evident in the UK during the winter of 2013-14 when many coastal areas and infrastructure suffered from unprecedented storms, flooding and erosion. Given the value and importance of urban environments, there is a real need to assess the vulnerability of towns and cities on the United Kingdom (UK) coastline on the basis of the latest projected climate scenarios. Accordingly, a modified Physical Coastal Vulnerability Index (PCVI) was developed in which beach width and coastal slope are considered the most critical physical parameters. The PCVI can be used to rank spatial coastal cells into four classes of vulnerability (from extremely low to high) and to map coastal vulnerability using GIS. As a case study, this approach was applied to the city of Southampton; one of the key port and trade cities in the UK, with results indicating that 38% of the city's coastline is highly vulnerable, and more than 50% moderately vulnerable. The work demonstrates that the methodological framework can be used as a planning tool for coastal management and, based on the availability of suitable data, can be adapted for estuarine or coastal and port environments without any geographical limits. Newly developed coastal vulnerability maps can be used by coastal engineers, managers and other decision makers to implement rigorous shoreline management planning as well as supporting risk, and disaster management policy and procedures. [ABSTRACT FROM AUTHOR]

Living shorelines are a shoreline stabilization strategy encompassing a range of vegetative to structural materials and serve as an alternative approach to the use of structures like bulkheads, which are known to aggravate erosion. Living shorelines are often installed with little to no long-term monitoring for effectiveness; specifically, there is a lack of quantitative data regarding their performance as a shoreline stabilization strategy. This study sought to assess the performance of living shorelines with sills, with respect to shoreline protection, by determining shoreline change rates (SCR) using geospatial analysis. Shoreline surveys were conducted using a real-time kinematic (RTK)-GPS unit at a total of 17 living shoreline projects and nine control segments at 12 sites along the coast of North Carolina. Current shoreline position was compared to historic (pre-installation) shoreline positions obtained from aerial imagery, dating to 1993. The average SCR among northern sites before installation was − 0.45 ± 0.49 m year−1, and in southern sites, it was − 0.21 ± 0.52 m year−1. After installation, average SCR was significantly less erosive at northern and southern sites with living shorelines, 0.17 ± 0.47 and − 0.01 ± 0.51 m year−1, respectively. Of the 17 living shoreline project segments, 12 exhibited a reduction in the rate of erosion; of those 12, six were observed to be accreting. This study supports the convention that living shorelines can reduce the rate of erosion and potentially restore lost shore zone habitat. [ABSTRACT FROM AUTHOR]

In engineering studies, finding the best route from a start point to an end point on pixel-based weighted maps is a big problem for researchers. For this problem many methods and algorithms have been developed until now. The “cost distance” (CD) and “cost path” (CP) tools that are used by a modified Dijkstra’s algorithm and used by Environmental Systems Research Institute’s (ESRI) ArcGIS Desktop 10 software are very fast and most preferred solutions for route optimization problems. Despite the advantages of these tools, they have the disadvantage of making a lot of curves with big angles. Especially in some engineering studies like power transmission lines’ routing, the angle of the curves of the lines should not have big values. For overcoming this problem both genetic algorithm (GA) and artificial bee colony (ABC) algorithm that have been improved and adapted for the problem were used as powerful optimizers to find the best routes with fewer curves in those kinds of optimum route problems. New functions like smart direction sensing and improved random functions were developed for application of GA and ABC algorithms in power transmission lines routing studies. This study showed that the ABC algorithm’s performance is better than GA. The accuracy of the algorithms was proven by comparing the results with the CD-CP tools’ results. The experimental results showed that the improved algorithms gave better performance than Dijkstra’s algorithm. [ABSTRACT FROM AUTHOR]

Accessibility is essentially a dynamic concept. However, most studies on urban accessibility take a static approach, overlooking the fact that accessibility conditions change dramatically throughout the day. Due to their high spatial and temporal resolution, the new data sources (Big Data) offer new possibilities for the study of accessibility. The aim of this paper is to analyse urban accessibility considering its two components -the performance of the transport network and the attractiveness of the destinations- using a dynamic approach using data from TomTom and Twitter respectively. This allows us to obtain profiles that highlight the daily variations in accessibility in the city of Madrid, and identify the influence of congestion and the changes in location of the population. These profiles reveal significant variations according to transport zones. Each transport zone has its own accessibility profile, and thus its own specific problems, which require solutions that are also specific. [ABSTRACT FROM AUTHOR]

Earthquake disasters pose significant risks and remain a serious threat for millions of people causing a devastating loss of lives and damage to the infrastructure resulting in huge socio-economic and environmental losses in many regions worldwide. In the last decade, recent major and catastrophic earthquake occurrences have underscored the critical importance of the increasing need for effective disaster management in considering appropriate planning, responses and strategies, with time and complex decision-making, being vital across the four phases of the disaster and emergency management (DEM) life cycle-preparedness, mitigation, response and recovery. In this paper, selected spatial decision support systems (SDSSs) related to the geographic information system-based applications in earthquake DEM, ranging from scenario or simulation based, early warning and rapid response and loss estimation systems, have been analysed. These have been generalised into global systems to include HAZTURK, QLARM, SELENA, DBELA, CATS, PAGER and regional and local systems comprising of ELER, HAZUS-MH, KOERILoss, MAEviz, EQRM and LNECLOSS. From the analysis of SDSS usage worldwide, but especially in Turkey, HAZTURK has been recommended for implementation of earthquake risk and loss estimation studies in Turkey based on its significant comparative advantages over other SDSSs and the suitability and applicability to the local conditions of Turkey, which have been discussed in this research. Key challenges to be addressed, ranging from issues in spatial data acquisition, quality, interoperability, data exchange and lack of coordination among associated institutions involved in earthquake DEM and recommendations, as well as future functional improvements and developments of HAZTURK software, have been characterised for successful implementation in Turkey. [ABSTRACT FROM AUTHOR]

Among the coastal districts of mega city Istanbul, Bakirkoy is one of the most critical one with the importance of air and marine transportation and presence of many other coastal facilities and structures that are prone to suffer from marine hazards. In the history, the Sea of Marmara has experienced numerous earthquake and landslide events and associated tsunamis. Therefore, tsunami risk assessment is essential for all coastal districts of Istanbul, including Bakirkoy district. In this study, a further developed methodology for tsunami human vulnerability and risk assessment Metropolitan Tsunami Human Vulnerability Assessment (MeTHuVA) is applied for Bakirkoy district of Istanbul, considering earthquake generated tsunamis. High-resolution tsunami hazard analysis is performed with the integration of coastal inundation computation with tsunami numerical tool NAMI DANCE and tsunami human vulnerability assessment with GIS-based multi-criteria decision analysis methods (MCDA). Using analytical hierarchy process method of MCDA, a hierarchical structure is established, composed of two main elements of tsunami human vulnerability: Vulnerability at Location and Evacuation Resilience. Tsunami risk assessment for Bakirkoy district is calculated by integrating result of hazard and vulnerability assessments with a risk relation that includes a parameter ( n), which represents the preparedness and awareness level of the community. Tsunami simulations revealed that the maximum inundation distance is over 350 m on land and water penetrates almost 1700 m along Ayamama stream. Inundation is observed in eleven neighborhoods of Bakirkoy district. In the inundation zone, maximum flow depth is found to be over 5.7 m. The inundated area forms 4.2% of whole Bakirkoy district, and 62 buildings are located in the inundation zone. Hazard, vulnerability and risk assessment results for different neighborhoods of Bakirkoy district are presented and discussed. [ABSTRACT FROM AUTHOR]