Search results for: stationary satellite

Authors: Joy Ghosh, Debasmita Biswas

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The road network of any area is the most important indicator of regional planning. For proper utilization of urban road networks, the structural parameters such as connectivity and accessibility should be analyzed and evaluated. This paper aims to explain the application of GIS on urban road network connectivity and accessibility analysis with a case study of Chandannagar City. This paper has been made to analyze the road network connectivity through various connectivity measurements like the total number of nodes and links, Cyclomatic Number, Alpha Index, Beta Index, Gamma index, Eta index, Pi index, Theta Index, and Aggregated Transport Score, Road Density based on existing road network in Chandannagar city in India. Accessibility is measured through the shortest Path Matrix, associate Number, and Shimbel Index. Various urban services, such as schools, banks, Hospitals, petrol pumps, ATMs, police stations, theatres, parks, etc., are considered for the accessibility analysis for each ward. This paper also highlights the relationship between urban land use/ land cover (LULC) and urban road network and population density using various spatial and statistical measurements. The datasets were collected through a field survey of 33 wards of the Chandannagar Municipal Corporation area, and the secondary data were collected through an open street map and satellite image of LANDSAT8 OLI & TIRS from USGS. Chandannagar was actually once a French colony, and at that time, various sort of planning was applied, but now Chandannagar city continues to grow haphazardly because that city is facing some problems; the knowledge gained from this paper helps to create a more efficient and accessible road network. Therefore, it would be suggested that some wards need to improve their connectivity and accessibility for the future growth and development of Chandannagar.

Keywords: accessibility, connectivity, transport, road network

Procedia PDF Downloads 72

Authors: Ronald Collins, Jonathon Coleman, Joel Dasari, George Holt, Carl Metelko, Matthew Murdoch, Alexander Morgan, Yan-Jie Schnellbach, Robert Mills, Gareth Edwards, Alexander Roberts

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At the Wylfa Magnox Power Plant between 2014–2016, the VIDARR prototype anti-neutrino detector was deployed. It is comprised of extruded plastic scintillating bars measuring 4 cm × 1 cm × 152 cm and utilised wavelength shifting fibres (WLS) and multi-pixel photon counters (MPPCs) to detect and quantify radiation. During deployment, it took cosmic muon data in accidental coincidence with the anti-neutrino measurements with the power plant site buildings obscuring the muon sky. Cosmic muons have a significantly higher probability of being attenuated and/or absorbed by denser objects, and so one-sided cosmic muon tomography was utilised to image the reactor site buildings. In order to achieve clear building outlines, a control data set was taken at the University of Liverpool from 2016 – 2018, which had minimal occlusion of the cosmic muon flux by dense objects. By taking the ratio of these two data sets and using GEANT4 simulations, it is possible to perform a one-sided cosmic muon tomography analysis. This analysis can be used to discern specific buildings, building heights, and features at the Wylfa reactor site, including the reactor core/reactor core shielding using ∼ 3 hours worth of cosmic-ray detector live time. This result demonstrates the feasibility of using cosmic muon analysis to determine a segmented detector’s location with respect to surrounding buildings, assisted by aerial photography or satellite imagery.

Keywords: anti-neutrino, GEANT4, muon, tomography, occlusion

Procedia PDF Downloads 186

Authors: Mayowa Saheed Sanusi A, Musiliu Olushola Sunmonua, Abdulquadri Alakab Owolabi Raheema, Adeyemi Ikimot Adejokea

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The development of healthy cookies for health-conscious consumers cannot be overemphasized in the present global health crisis. This study was aimed to evaluate and model the influence of ripeness levels of papaya puree (unripe, ripe and overripe), oven temperature (130°C, 150°C and 170°C) and oven rack speed (stationary, 10 and 20 rpm) on physicochemical properties of papaya-based cookies using Response Surface Methodology (RSM). The physicochemical properties (baking time, cookies mass, cookies thickness, spread ratio, proximate composition, Calcium, Vitamin C and Total Phenolic Content) were determined using standard procedures. The data obtained were statistically analysed at p≤0.05 using ANOVA. The polynomial regression model of response surface methodology was used to model the physicochemical properties. The adequacy of the models was determined using the coefficient of determination (R²) and the response optimizer of RSM was used to determine the optimum physicochemical properties for the papaya-based cookies. Cookies produced from overripe papaya puree were observed to have the shortest baking time; ripe papaya puree favors cookies spread ratio, while the unripe papaya puree gives cookies with the highest mass and thickness. The highest crude protein content, fiber content, calcium content, Vitamin C and Total Phenolic Content (TPC) were observed in papaya based-cookies produced from overripe puree. The models for baking time, cookies mass, cookies thickness, spread ratio, moisture content, crude protein and TPC were significant, with R2 ranging from 0.73 – 0.95. The optimum condition for producing papaya based-cookies with desirable physicochemical properties was obtained at 149°C oven temperature, 17 rpm oven rack speed and with the use of overripe papaya puree. The Information on the use of puree from unripe, ripe and overripe papaya can help to increase the use of underutilized unripe or overripe papaya and also serve as a strategic means of obtaining a fat substitute to produce new products with lower production cost and health benefit.

Keywords: papaya based-cookies, modeling, response surface methodology, physicochemical properties

Procedia PDF Downloads 167

Authors: Arya Farjand

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The Nihewan Basin is a critical region in order to understand the Plio-Pleistocene paleoenvironment and its fauna in Northern China. The rich fossiliferous, fluvial-lacustrine sediments around the Nihewan Village hosted the specimens known as the Classic Nihewan Fauna. The primary excavations in the early 1920-30s produced more than 2000 specimens housed in Tianjin and Paris Museum. Nevertheless, the exact locality of excavations, fossil beds, and the reliable ages remained ambiguous until recent paleomagnetic studies and extensive work in conjunction sites. In this study, for the first time, we successfully relocated some of the original excavation sites. We reexamined more than 1500 specimens held in Tianjin Museum and cited their locality numbers and properties. During the field-season of 2017-2019, we visited the Xiashagou Valley. By reading the descriptions of the original site, utilization of satellite pictures, and comparing them with the current geomorphology of the area, we ensured the exact location of 26 of these sites and 17 fossil layers. Furthermore, by applying the latest technologies, such as GPS, Compass, digital barometers, laser measurer, and Abney level, we ensured the accuracy of the measurement. We surveyed 133-meter thickness of the deposits. Ultimately by applying the available Paleomagnetic data for this section, we estimated the ages of different horizons. The combination of our new data and previously published researches present a unique age control for the Classic Nihewan Fauna. These findings prove the hypothesis in which the Classic Nihewan Fauna belongs to different horizons, ranging from before Reunion up to after Olduvai earth geomagnetic field excursion (2.2-1.7 Mya).

Keywords: classic Nihewan basin fauna, Olduvai excursion, Pleistocene, stratigraphy

Procedia PDF Downloads 141

Authors: Renato Morbidelli, Carla Saltalippi, Alessia Flammini, Marco Cifrodelli, Corrado Corradini

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The trend of magnitude and frequency of extreme rainfalls seems to be different depending on the investigated area of the world. In this work, the impact of climate change on extreme rainfalls in Umbria, an inland region of central Italy, is examined using data recorded during the period 1921-2015 by 10 representative rain gauge stations. The study area is characterized by a complex orography, with altitude ranging from 200 to more than 2000 m asl. The climate is very different from zone to zone, with mean annual rainfall ranging from 650 to 1450 mm and mean annual air temperature from 3.3 to 14.2°C. Over the past 15 years, this region has been affected by four significant droughts as well as by six dangerous flood events, all with very large impact in economic terms. A least-squares linear trend analysis of annual maximums over 60 time series selected considering 6 different durations (1 h, 3 h, 6 h, 12 h, 24 h, 48 h) showed about 50% of positive and 50% of negative cases. For the same time series the non-parametrical Mann-Kendall test with a significance level 0.05 evidenced only 3% of cases characterized by a negative trend and no positive case. Further investigations have also demonstrated that the variance and covariance of each time series can be considered almost stationary. Therefore, the analysis on the magnitude of extreme rainfalls supplies the indication that an evident trend in the change of values in the Umbria region does not exist. However, also the frequency of rainfall events, with particularly high rainfall depths values, occurred during a fixed period has also to be considered. For all selected stations the 2-day rainfall events that exceed 50 mm were counted for each year, starting from the first monitored year to the end of 2015. Also, this analysis did not show predominant trends. Specifically, for all selected rain gauge stations the annual number of 2-day rainfall events that exceed the threshold value (50 mm) was slowly decreasing in time, while the annual cumulated rainfall depths corresponding to the same events evidenced trends that were not statistically significant. Overall, by using a wide available dataset and adopting simple methods, the influence of climate change on the heavy rainfalls in the Umbria region is not detected.

Keywords: climate changes, rainfall extremes, rainfall magnitude and frequency, central Italy

Procedia PDF Downloads 236

Authors: Ima Rahmawati, Nur Hafizul Kalam

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Development of industrial and economic sectors in various countries very rapidly caused raising the greenhouse gas (GHG) emissions. Greenhouse gases are dominated by carbon dioxide (CO2) and methane (CH4) in the atmosphere that make the surface temperature of the earth always increase. The increasing gases caused by incomplete combustion of fossil fuels such as petroleum and coals and also high rate of deforestation. Yogyakarta Special Province which every year always become tourist destination, has a great potency in increasing of greenhouse gas emissions mainly from the incomplete combustion. One of effort to reduce the concentration of gases in the atmosphere is keeping and empowering the existing forests in the Province of Yogyakarta, especially forest in Kulonprogro is to be maintained the greenness so that it can absorb and store carbon maximally. Remote sensing technology can be used to determine the ability of forests to absorb carbon and it is connected to the density of vegetation. The purpose of this study is to determine the density of the biomass of forest vegetation and determine the ability of forests to store carbon through Photo-interpretation and Geographic Information System approach. Remote sensing imagery that used in this study is LANDSAT 8 OLI year 2015 recording. LANDSAT 8 OLI imagery has 30 meters spatial resolution for multispectral bands and it can give general overview the condition of the carbon stored from every density of existing vegetation. The method is the transformation of vegetation index combined with allometric calculation of field data then doing regression analysis. The results are model maps of density and capability level of forest vegetation in Kulonprogro, Yogyakarta in storing carbon.

Keywords: remote sensing, carbon, kulonprogo, forest vegetation, vegetation index

Procedia PDF Downloads 397

Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

Procedia PDF Downloads 116

Authors: Mahesh Kumar Jat, Manisha Choudhary

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Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

Procedia PDF Downloads 130

Authors: Magdy Roman, Mostafa Shoeib, Mostafa Rostom

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Global vision, whether provided by overhead fixed cameras, on-board aerial vehicle cameras, or satellite images can always provide detailed information on the environment around mobile robots. In this paper, an intelligent vision-based method of path planning and obstacle avoidance for mobile robots is presented. The method integrates visual perception with a new proposed field-based path-planning method to overcome common path-planning problems such as local minima, unreachable destination and unnecessary lengthy paths around obstacles. The method proposes an exponential angle deviation field around each obstacle that affects the orientation of a close robot. As the robot directs toward, the goal point obstacles are classified into right and left groups, and a deviation angle is exponentially added or subtracted to the orientation of the robot. Exponential field parameters are chosen based on Lyapunov stability criterion to guarantee robot convergence to the destination. The proposed method uses obstacles' shape and location, extracted from global vision system, through a collision prediction mechanism to decide whether to activate or deactivate obstacles field. In addition, a search mechanism is developed in case of robot or goal point is trapped among obstacles to find suitable exit or entrance. The proposed algorithm is validated both in simulation and through experiments. The algorithm shows effectiveness in obstacles' avoidance and destination convergence, overcoming common path planning problems found in classical methods.

Keywords: path planning, collision avoidance, convergence, computer vision, mobile robots

Procedia PDF Downloads 194

Authors: Vishnu Nagendra, Marten Van Der Veen, Stefania Giodini

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Effective humanitarian logistics operations are a cornerstone in the success of disaster relief operations. However, for effectiveness, they need to be demand driven and supported by adequate data for prioritization. Without this data operations are carried out in an ad hoc manner and eventually become chaotic. The current availability of geospatial data helps in creating models for predictive damage and vulnerability assessment, which can be of great advantage to logisticians to gain an understanding on the nature and extent of the disaster damage. This translates into actionable information on the demand for relief goods, the state of the transport infrastructure and subsequently the priority areas for relief delivery. However, due to the unpredictable nature of disasters, the accuracy in the models need improvement which can be done using remote sensing data from UAVs (Unmanned Aerial Vehicles) or satellite imagery, which again come with certain limitations. This research addresses the need for a framework to combine data from different sources to support humanitarian logistic operations and prediction models. The focus is on developing a workflow to combine data from satellites and UAVs post a disaster strike. A three-step approach is followed: first, the data requirements for logistics activities are made explicit, which is done by carrying out semi-structured interviews with on field logistics workers. Second, the limitations in current data collection tools are analyzed to develop workaround solutions by following a systems design approach. Third, the data requirements and the developed workaround solutions are fit together towards a coherent workflow. The outcome of this research will provide a new method for logisticians to have immediately accurate and reliable data to support data-driven decision making.

Keywords: unmanned aerial vehicles, damage prediction models, remote sensing, data driven decision making

Procedia PDF Downloads 378

Authors: Lican Guzmán, José Manuel Lattus, Mariana Cervetto, Mauricio Calderón

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Today the estimation of effects produced by climate change in high Andean wetland environments is confronted by big challenges. This study provides a way to an analysis by remote sensing how some Ambiental aspects have evolved on the Maricunga salt flat in the last 30 years, divided into the summer and winter seasons, and if global warming is conditioning these changes. The first step to achieve this goal was the recompilation of geological, hydrological, and morphometric antecedents to ensure an adequate contextualization of its environmental parameters. After this, software processing and analysis of Landsat 5,7 and 8 satellite imagery was required to get the vegetation, water, surface temperature, and soil moisture indexes (NDVI, NDWI, LST, and SMI) in order to see how their spatial-temporal conditions have evolved in the area of study during recent decades. Results show a tendency of regular increase in surface temperature and disponibility of water during both seasons but with slight drought periods during summer. Soil moisture factor behaves as a constant during the dry season and with a tendency to increase during wintertime. Vegetation analysis shows an areal and quality increase of its surface sustained through time that is consistent with the increase of water supply and temperature in the basin mentioned before. Roughly, the effects of climate change can be described as positive for the Maricunga salt flat; however, the lack of exact correlation in dates of the imagery available to remote sensing analysis could be a factor for misleading in the interpretation of results.

Keywords: global warming, geology, SIG, Atacama Desert, Salar de Maricunga, environmental geology, NDVI, SMI, LST, NDWI, Landsat

Procedia PDF Downloads 78

Authors: Gurbanova Lamiya

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The Republic of Azerbaijan is considered a region with limited water resources, as up to 70% of surface water is formed outside the country's borders, and most of its territory is an arid (dry) climate zone. It is located at the lower limit of transboundary flows, which is the weakest source of natural water resources in the South Caucasus. It is essential to correctly assess the quality of natural, collector-drainage and groundwater of the area and their suitability for irrigation in order to properly carry out land reclamation measures, provide the normal water-salt regime, and prevent repeated salinization. Through the 141-km-long main Mil-Mugan collector, groundwater, household waste, and floodwaters generated during floods and landslides are poured into the Caspian Sea. The hydrochemical composition of the samples taken from the Sabir irrigation canal passing through the center of the Kura-Araz plain, the Main Mil-Mugan Collector, and the groundwater of the region, which we chose as our research object, were studied and the obtained results were compared by periods. A model is proposed that allows for a complete visualization of the primary materials collected for the study area. The practical use of the established digital model provides all possibilities. The practical use of the established digital model provides all possibilities. An extensive database was created with the ArcGis 10.8 package, using publicly available LandSat satellite images as primary data in addition to ground surveys to build the model. The principles of the construction of the geographic information system of modern GIS technology were developed, the boundary and initial condition of the research area were evaluated, and forecasts and recommendations were given.

Keywords: irrigation channel, groundwater, collector, meliorative measures

Procedia PDF Downloads 71

Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

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Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

Procedia PDF Downloads 113

Authors: Fatemeh Parhizkar, Mojtaba Yamani, Abdolla Behboodi, Masoomeh Hashemi

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The mangrove forests are natural and valuable gifts that exist in some parts of the world, including Iran. Regarding the threats faced by these forests and the declining area of them all over the world, as well as in Iran, it is very necessary to manage and monitor them. The current study aimed to investigate the changes in mangrove forests and the relationship between these changes and the marine hydrodynamics and coastal morphology in the area between qeshm island and the west coast of the Hormozgan province (i.e. the coastline between Mehran river and Bandar-e Pol port) in the 49-year period. After preprocessing and classifying satellite images using the SVM, MLC, and ANN classifiers and evaluating the accuracy of the maps, the SVM approach with the highest accuracy (the Kappa coefficient of 0.97 and overall accuracy of 98) was selected for preparing the classification map of all images. The results indicate that from 1972 to 1987, the area of these forests have had experienced a declining trend, and in the next years, their expansion was initiated. These forests include the mangrove forests of Khurkhuran wetland, Muriz Deraz Estuary, Haft Baram Estuary, the mangrove forest in the south of the Laft Port, and the mangrove forests between the Tabl Pier, Maleki Village, and Gevarzin Village. The marine hydrodynamic and geomorphological characteristics of the region, such as average intertidal zone, sediment data, the freshwater inlet of Mehran river, wave stability and calmness, topography and slope, as well as mangrove conservation projects make the further expansion of mangrove forests in this area possible. By providing significant and up-to-date information on the development and decline of mangrove forests in different parts of the coast, this study can significantly contribute to taking measures for the conservation and restoration of mangrove forests.

Keywords: mangrove forests, marine hydrodynamics, coastal morphology, west of strait of Hormuz, Iran

Procedia PDF Downloads 95

Authors: Nowbuth Manta Devi, Rasmally Mohammed Hussein

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Flood is one of the most devastating climate impacts that many countries are facing. Many different causes have been associated with the intensity of floods being recorded over time. Unplanned development, low carrying capacity of drains, clogged drains, construction in flood plains or increasing intensity of rainfall events. While a combination of these causes can certainly aggravate the flood conditions, in many cases, increasing drainage capacity has not reduced flood risk to the level that was expected. The present study analyzed the extent to which land use is contributing to aggravating impacts of flooding in a city. Satellite images have been analyzed over a period of 20 years at intervals of 5 years. Both unsupervised and supervised classification methods have been used with the image processing module of ArcGIS. The unsupervised classification was first compared to the basemap available in ArcGIS to get a first overview of the results. These results also aided in guiding data collection on-site for the supervised classification. The island of Mauritius is small, and there are large variations in land use over small areas, both within the built areas and in agricultural zones involving food crops. Larger plots of agricultural land under sugar cane plantations are relatively more easily identified. However, the growth stage and health of plants vary and this had to be verified during ground truthing. The results show that although there have been changes in land use as expected over a span of 20 years, this was not significant enough to cause a major increase in flood risk levels. A digital elevation model was analyzed for further understanding. It could not be noted that overtime, development tampered with natural flow paths in addition to increasing the impermeable areas. This situation results in backwater flows, hence increasing flood risks.

Keywords: climate change, flood, natural flow paths, small islands

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Authors: Maryam Jaberi, Siavosh Shayan, Mojtaba Yamani

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Habble-Rud River basin (HR), up to 100 km length, one of the largest watersheds which drain into deserts to the north of Central Iran (Dasht-e Kavir). This stream is oblique with the NE-SW trending, flow in the southern range of central Alborz Mountains and the northern border of Central Iran. The end of the ~17 km suddenly change direction and with the southern trending to have a morphology which meanders passes through the Alborz Mountain ridge and flows into the Garmsar plain where it forms one of the largest alluvial fans in Iran, i.e. the vast Garmsar alluvial fan with an area of 476 km2. This study was carried out through morphometric analyses, longitudinal river profiles, and study of geomorpholic evidence such as fluvial terraces, gypsum-salt domes, seismic data, and satellite images. This study aimed to investigate the changes in the pattern of rivers in the southern part of the HR river basin. The southern part of HR river basin located at the southern foothills of the Central Alborz is characterized the thrust faults (Sorkheh-Kalut and Garmsar faults), folds,diapirs and arid climate. The activity of more than 10 salt domes that belong to the Oligocene-Miocene period has considerably influenced the pattern of streams in this region. Dissolution of these domes has not only reduced the quality of water and soil resources, but also has led to the formation of badlands and gullies.Our results indicated that the pattern of rivers in the southern part of HR river basin was influenced by discharge of the HR river in Quaternary, geological structure, subsidence of Central Iran and vertical uplift of Alborz mountain. These agents caused the formation meanders in the southern part of the HR River and evaluation of the seasonal rivers like Shoor-Darre and Garmabsar.

Keywords: geomorphologic evaluation, rivers pattern, Habble-Rud River basin, seasonal rivers

Procedia PDF Downloads 501

Authors: M. N. Kadir, M. M. H. Oliver, T. Naher

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The study assesses the areal extent of riverine flood in the flood-prone area of Faridpur District of Bangladesh using hydrological model and Geographic Information System (GIS). In the context of preparing the inundation map, flood frequency analysis was carried out to assess flooding for different flood magnitudes. Flood inundation maps were prepared based on DEM, and discharge at the river using Delft-3D model. LANDSAT satellite images have been used to develop a land cover map in the study area. The land cover map was used for mapping of cropland area. By incorporating the inundation maps on the land cover map, agricultural damage was assessed. Present monetary values of crop damage were collected through field survey from actual flood of the study area. Two different inundation maps were produced from the model for the year 2000 and 2016. In the year 2000, the floods began in the month of July, whereas in the case of the year 2016 is started in August. Under both cases, most of the areas were found to have been flooded in the month of September followed by flood recession. In order to prepare the land cover maps, four categories of LCs were considered viz., cropland, water body, trees, and rivers. Among the 755791 acres area of Faridpur District, the croplands were categorized to be 334,589 acres, followed by water bodies (279900 acres), trees (101930 acres) and rivers 39372 (acres). Damage assessment data revealed that 40% of the total cropland area had been affected by the flood in the year 2000, whereas only 19% area was affected by the 2016 flood. The study concluded that September is the critical month for cropland protection since the highest flood is expected at this time of the year in Faridpur. The northwestern and the southwestern part of the district was categorized as most vulnerable to flooding.

Keywords: agricultural damage, Delft-3d, flood management, land cover map

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Authors: Arragaw Alemayehu, Woldeamlak Bewket

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The aim of this study was to understand the influence of current climate variability on crop production in the central highlands of Ethiopia. We used monthly rainfall and temperature data from 132 points each representing a pixel of 10×10 km. The data are reconstructions based on station records and meteorological satellite observations. Production data of the five major crops in the area were collected from the Central Statistical Agency for the period 2004-2013 and for the main cropping season, locally known as Meher. The production data are at the Enumeration Area (EA ) level and hence the best available dataset on crop production. The results show statistically significant decreasing trends in March–May (Belg) rainfall in the area. However, June – September (Kiremt) rainfall showed increasing trends in Efratana Gidim and Menz Gera Meder which the latter is statistically significant. Annual rainfall also showed positive trends in the area except Basona Werana where significant negative trends were observed. On the other hand, maximum and minimum temperatures showed warming trends in the study area. Correlation results have shown that crop production and area of cultivation have positive correlation with rainfall, and negative with temperature. When the trends in crop production are investigated, most crops showed negative trends and below average production was observed. Regression results have shown that rainfall was the most important determinant of crop production in the area. It is concluded that current climate variability has a significant influence on crop production in the area and any unfavorable change in the local climate in the future will have serious implications for household level food security. Efforts to adapt to the ongoing climate change should begin from tackling the current climate variability and take a climate risk management approach.

Keywords: central highlands, climate variability, crop production, Ethiopia, regression, trend

Procedia PDF Downloads 438

Authors: Zbigniew Czyż, Adam Majczak, Lukasz Grabowski

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The paper presents a description of geometric models, computational algorithms, and results of numerical analyses of charge exchange in a two-stroke opposed-piston engine. The research engine was a newly designed internal Diesel engine. The unit is characterized by three cylinders in which three pairs of opposed-pistons operate. The engine will generate a power output equal to 100 kW at a crankshaft rotation speed of 3800-4000 rpm. The numerical investigations were carried out using ANSYS FLUENT solver. Numerical research, in contrast to experimental research, allows us to validate project assumptions and avoid costly prototype preparation for experimental tests. This makes it possible to optimize the geometrical model in countless variants with no production costs. The geometrical model includes an intake manifold, a cylinder, and an outlet manifold. The study was conducted for a series of modifications of manifolds and intake and exhaust ports to optimize the charge exchange process in the engine. The calculations specified a swirl coefficient obtained under stationary conditions for a full opening of intake and exhaust ports as well as a CA value of 280° for all cylinders. In addition, mass flow rates were identified separately in all of the intake and exhaust ports to achieve the best possible uniformity of flow in the individual cylinders. For the models under consideration, velocity, pressure and streamline contours were generated in important cross sections. The developed models are designed primarily to minimize the flow drag through the intake and exhaust ports while the mass flow rate increases. Firstly, in order to calculate the swirl ratio [-], tangential velocity v [m/s] and then angular velocity ω [rad / s] with respect to the charge as the mean of each element were calculated. The paper contains comparative analyses of all the intake and exhaust manifolds of the designed engine. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: computational fluid dynamics, engine swirl, fluid mechanics, mass flow rates, numerical analysis, opposed-piston engine

Procedia PDF Downloads 197

Authors: Angel Liduvino Vara-Vela, Dirceu Luis Herdies, Debora Souza Alvim, Eder Paulo Vendrasco, Silvio Nilo Figueroa, Jayant Pendharkar, Julio Pablo Reyes Fernandez

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Biomass-burning episodes are quite common in the central Amazon rainforest and represent a dominant source of aerosols during the dry season, between August and October. The increase in the occurrence of fires in 2019 in the world’s largest biomes has captured the attention of the international community. In particular, a rare and extreme smoke-related event occurred in the afternoon of Monday, August 19, 2019, in the most populous city in the Western Hemisphere, the São Paulo Metropolitan Area (SPMA), located in southeastern Brazil. The sky over the SPMA suddenly blackened, with the day turning into night, as reported by several news media around the world. In order to clarify whether or not the smoke that plunged the SPMA into sudden darkness was related to wildfires in the Amazon rainforest region, a set of 48-hour simulations over South America were performed using the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 20 km horizontal resolution, on a daily basis, during the period from August 16 to August 19, 2019. The model results were satisfactorily compared against satellite-based data products and in situ measurements collected from air quality monitoring sites. Although a very strong smoke transport coming from the Amazon rainforest was observed in the middle of the afternoon on August 19, its impact on air quality over the SPMA took place in upper levels far above the surface, where, conversely, low air pollutant concentrations were observed.

Keywords: Amazon rainforest, biomass burning aerosols, São Paulo metropolitan area, WRF-Chem model

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Authors: Binod C. Agrawal

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In modern history, industrial and media merchandising in South Asia from East Asia, Europe, United States and other countries of the West is over 200 years old. Hence, continued external technology and media exposure is not a new experience in multi-lingual and multi religious South Asia which evolved cultural means to withstand structural change. In the post-World War II phase, media exposure especially of telecommunication, film, Internet, radio, print media and television have increased manifold. South Asia did not lose any time in acquiring and adopting digital media accelerated by chip revolution, computer and satellite communication. The penetration of digital media and utilization are exceptionally high though the spread has an unequal intensity, use and effects. The author argues that industrial and media products are “cultural products” apart from being “technological products”; hence their influences are most felt in the cultural domain which may lead to blunting of unique cultural specifics in the multi-cultural, multi-lingual and multi religious South Asia. Social scientists, political leaders and parents have voiced concern of “Cultural domination”, “Digital media colonization” and “Westernization”. Increased digital media access has also opened up doors of pornography and other harmful information that have sparked fresh debates and discussions about serious negative, harmful, and undesirable social effects especially among youth. Within ‘techno-social’ perspective, based on recent research studies, the paper aims to describe and analyse possible socio-economic change due to digital media penetration. Further, analysis supports the view that the ancient multi-lingual and multi-religious cultures of South Asia due to inner cultural strength may sustain without setting in a process of irreversible structural changes in South Asia.

Keywords: cultural sustainability, digital media effects, digital media impact in South Asia, social change in South Asia

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Authors: Krima M. Rohela, Raja Sabarinath Sundaralingam

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Humans have been launching rockets since the beginning of the space age in the late 1950s. We have come a long way since then, and the success rate for the launch of rockets has increased considerably. With every successful launch, there is a large amount of junk or debris which is released into the upper layers of the atmosphere. Space debris has been a huge concern for a very long time now. This includes the rocket shells released from the launch and the parts of defunct satellites. Some of this junk will come to fall towards the Earth and burn in the atmosphere. But most of the junk goes into orbit around the Earth, and they remain in orbits for at least 100 years. This can cause a lot of problems to other functioning satellites and may affect the future manned missions to space. The main concern of the space-debris is the increase in space activities, which leads to risks of collisions if not taken care of soon. These collisions may result in what is known as Kessler Syndrome. This debris can be removed by a space-based laser targeting system. Hence, the matter is investigated and discussed. The first step in this involves launching a satellite with a high-power laser device into space, above the debris belt. Then the target material is ablated with a focussed laser beam. This step of the process is highly dependent on the attitude and orientation of the debris with respect to the Earth and the device. The laser beam will cause a jet of vapour and plasma to be expelled from the material. Hence, the force is applied in the opposite direction, and in accordance with Newton’s third law of motion, this will cause the material to move towards the Earth and get pulled down due to gravity, where it will get disintegrated in the upper layers of the atmosphere. The larger pieces of the debris can be directed towards the oceans. This method of removal of the orbital debris will enable safer passage for future human-crewed missions into space.

Keywords: altitude, Kessler syndrome, laser ablation, Newton’s third law of motion, satellites, Space debris

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Authors: Jakob Krause

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Past Financial Crisis has shown that contemporary risk management models provide an unjustified sense of security and fail miserably in situations in which they are needed the most. In this paper, we start from the assumption that risk is a notion that changes over time and therefore past data points only have limited explanatory power for the current situation. Our objective is to derive the optimal amount of representative information by optimizing between the two adverse forces of estimator convergence, incentivizing us to use as much data as possible, and the aforementioned non-representativeness doing the opposite. In this endeavor, the cornerstone assumption of having access to identically distributed random variables is weakened and substituted by the assumption that the law of the data generating process changes over time. Hence, in this paper, we give a quantitative theory on how to perform statistical analysis in non-ergodic systems. As an application, we discuss the impact of a paragraph in the last iteration of proposals by the Basel Committee on Banking Regulation. We start from the premise that the severity of assumptions should correspond to the robustness of the system they describe. Hence, in the formal description of physical systems, the level of assumptions can be much higher. It follows that every concept that is carried over from the natural sciences to economics must be checked for its plausibility in the new surroundings. Most of the probability theory has been developed for the analysis of physical systems and is based on the independent and identically distributed (i.i.d.) assumption. In Economics both parts of the i.i.d. assumption are inappropriate. However, only dependence has, so far, been weakened to a sufficient degree. In this paper, an appropriate class of non-stationary processes is used, and their law is tied to a formal object measuring representativeness. Subsequently, that data set is identified that on average minimizes the estimation error stemming from both, insufficient and non-representative, data. Applications are far reaching in a variety of fields. In the paper itself, we apply the results in order to analyze a paragraph in the Basel 3 framework on banking regulation with severe implications on financial stability. Beyond the realm of finance, other potential applications include the reproducibility crisis in the social sciences (but not in the natural sciences) and modeling limited understanding and learning behavior in economics.

Keywords: banking regulation, non-ergodicity, risk management, semimartingale modeling

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Authors: Maulita Sari Hani, Abraham B. Sianipar, Jamaluddin Jompa, Natsir Nessa, Alan T. White

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Manta ray is an icon for tourism in Raja Ampat. The tourist volume has been increased for the past ten years which up to approximately 23,000 tourists in 2017. Since 2013, Conservation International Indonesia deployed satellite and acoustic tags on manta ray in Dampier strait to track the species and identify the aggregation areas. These findings encourage the government and the local community to boost conservation through the management of marine protected areas for tourism purposes. Community in Dampier strait including the village of Arborek, Kurkapa, Kapisawar, and Sawingray involved in variety of small scale tourism business including homestay, dive shop, tour operator, and crafts. Working groups of related local businesses were established to support the local community and to ensure the sustainability of the economic viability and environmental sustainability. In order to analyze the economic benefits of manta ray tourism, this study was conducted to identify the number of local business in Dampier Strait and the economic impacts in terms of local finance security, social, humanity, individual, and physical assets. The results of this study identify 30 homestays, 2 dive shops, 10 tour operators, 30 women involved in crafts, and about 50 villagers worked for dive resorts. In addition to community assets, we confirmed the welfare of community has been improved in terms of food security, households, education for children, savings, and health insurance.

Keywords: marine wildlife tourism, elasmobranch, conservation, ecotourism, co-management, economic viability, environmental sustainability

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Hyelim Park, Juan Martin Zorrilla

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Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Jae-Hyun Choi, Sung-Soo Bae, Sangyoung Yoon, Hong-Ku Yun, Jiyoung Kwahk

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This study was conducted to investigate the effect of ocular dominance on recognition performance using a single-lens smart display designed for cycling. A total of 36 bicycle riders who have been cycling consistently were recruited and participated in the experiment. The participants were asked to perform tasks riding a bicycle on a stationary stand for safety reasons. Independent variables of interest include ocular dominance, bike usage, age group, and information layout. Recognition time (i.e., the time required to identify specific information measured with an eye-tracker), error rate (i.e. false answer or failure to identify the information in 5 seconds), and user preference scores were measured and statistical tests were conducted to identify significant results. Recognition time and error ratio showed significant difference by ocular dominance factor, while the preference score did not. Recognition time was faster when the single-lens see-through display on the dominant eye (average 1.12sec) than on the non-dominant eye (average 1.38sec). Error ratio of the information recognition task was significantly lower when the see-through display was worn on the dominant eye (average 4.86%) than on the non-dominant eye (average 14.04%). The interaction effect of ocular dominance and age group was significant with respect to recognition time and error ratio. The recognition time of the users in their 40s was significantly longer than the other age groups when the display was placed on the non-dominant eye, while no difference was observed on the dominant eye. Error ratio also showed the same pattern. Although no difference was observed for the main effect of ocular dominance and bike usage, the interaction effect between the two variables was significant with respect to preference score. Preference score of daily bike users was higher when the display was placed on the dominant eye, whereas participants who use bikes for leisure purposes showed the opposite preference patterns. It was found more effective and efficient to wear a see-through display on the dominant eye than on the non-dominant eye, although user preference was not affected by ocular dominance. It is recommended to wear a see-through display on the dominant eye since it is safer by helping the user recognize the presented information faster and more accurately, even if the user may not notice the difference.

Keywords: eye tracking, information recognition, ocular dominance, smart headware, wearable device

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Authors: Nicolas Bae, Theodore L. Karavasilis

Abstract:

Increasingly, a large number of new and existing tall buildings are required to improve their resilient performance against strong winds and earthquakes to minimize direct, as well as indirect damages to society. Those advent stationary functions of tall building structures in metropolitan regions can be severely hazardous, in socio-economic terms, which also increase the requirement of advanced seismic performance. To achieve these progressive requirements, the seismic reinforcement for some old, conventional buildings have become enormously costly. The methods of increasing the buildings’ resilience against wind or earthquake loads have also become more advanced. Up to now, vibration control devices, such as the passive damper system, is still regarded as an effective and an easy-to-install option, in improving the seismic resilience of buildings at affordable prices. The main purpose of this paper is to examine 1) the optimization of the shape of visco plastic brace damper (VPBD) system which is one of hybrid damper system so that it can maximize its energy dissipation capacity in tall buildings against wind and earthquake. 2) the verification of the seismic performance of the visco plastic brace damper system in tall buildings; up to forty-storey high steel frame buildings, by comparing the results of Non-Linear Response History Analysis (NLRHA), with and without a damper system. The most significant contribution of this research is to introduce the optimized hybrid damper system that is adequate for high rise buildings. The efficiency of this visco plastic brace damper system and the advantages of its use in tall buildings can be verified since tall buildings tend to be affected by wind load at its normal state and also by earthquake load after yielding of steel plates. The modeling of the prototype tall building will be conducted using the Opensees software. Three types of modeling were used to verify the performance of the damper (MRF, MRF with visco-elastic, MRF with visco-plastic model) 22-set seismic records used and the scaling procedure was followed according to the FEMA code. It is shown that MRF with viscous, visco-elastic damper, it is superior effective to reduce inelastic deformation such as roof displacement, maximum story drift, roof velocity compared to the MRF only.

Keywords: tall steel building, seismic retrofit, viscous, viscoelastic damper, performance based design, resilience based design

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Authors: Zongyao Sha

Abstract:

Green vegetation plays a vital role in energy flows and matter cycles in terrestrial ecosystems, and vegetation phenology may not only be influenced by but also impose active feedback on climate changes. The phenological events of vegetation, such as the start of the season (SOS), end of the season (EOS), and length of the season (LOS), can respond to climate changes and affect gross primary productivity (GPP). Here we coupled satellite remote sensing imagery with FLUXNET observations to systematically map the shift of SOS, EOS, and LOS in global vegetated areas and explored their response to climate fluctuations and feedback on GPP during the last two decades. Results indicated that SOS advanced significantly, at an average rate of 0.19 days/year at a global scale, particularly in the northern hemisphere above the middle latitude (≥30°N) and that EOS was slightly delayed during the past two decades, resulting in prolonged LOS in 72.5% of the vegetated area. The climate factors, including seasonal temperature and precipitation, are attributed to the shifts in vegetation phenology but with a high spatial and temporal difference. The study revealed interactions between vegetation phenology and climate changes. Both temperature and precipitation affect vegetation phenology. Higher temperature as a direct consequence of global warming advanced vegetation green-up date. On the other hand, 75.9% and 20.2% of the vegetated area showed a positive correlation and significant positive correlation between annual GPP and length of vegetation growing season (LOS), likely indicating an enhancing effect on vegetation productivity and thus increased carbon uptake from the shifted vegetation phenology. Our study highlights a comprehensive view of the vegetation phenology changes of the global terrestrial ecosystems during the last two decades. The interactions between the shifted vegetation phenology and climate changes may provide useful information for better understanding the future trajectory of global climate changes. The feedback on GPP from the shifted vegetation phenology may serve as an adaptation mechanism for terrestrial ecosystems to mitigate global warming through improved carbon uptake from the atmosphere.

Keywords: vegetation phenology, growing season, NPP, correlation analysis

Procedia PDF Downloads 102