Search results for: satellite data

Authors: Michael Gidey Gebru

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Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

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Authors: Remus Pravalie, Georgeta Bandoc

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Forests are crucial for humanity and biodiversity, through the various ecosystem services and functions they provide all over the world. Forest ecosystems are vital in Romania as well, through their various benefits, known as provisioning (food, wood, or fresh water), regulating (water purification, soil protection, carbon sequestration or control of climate change, floods, and other hazards), cultural (aesthetic, spiritual, inspirational, recreational or educational benefits) and supporting (primary production, nutrient cycling, and soil formation processes, with direct or indirect importance for human well-being) ecosystem services. These ecological benefits are of great importance in Romania, especially given the fact that forests cover extensive areas countrywide, i.e. ~6.5 million ha or ~27.5% of the national territory. However, the diversity and functionality of these ecosystem services fundamentally depend on certain key attributes of forests, such as biomass, which has so far not been studied nationally in terms of potential changes due to climate change and other driving forces. This study investigates, for the first time, changes in forest biomass in Romania in recent decades, based on a high volume of satellite data (Landsat images at high spatial resolutions), downloaded from the Google Earth Engine platform and processed (using specialized software and methods) across Romanian forestland boundaries from 1987 to 2018. A complex climate database was also investigated across Romanian forests over the same 32-year period, in order to detect potential similarities and statistical relationships between the dynamics of biomass and climate data. The results obtained indicated considerable changes in forest biomass in Romania in recent decades, largely triggered by the climate change that affected the country after 1987. Findings on the complex pattern of recent forest changes in Romania, which will be presented in detail in this study, can be useful to national policymakers in the fields of forestry, climate, and sustainable development.

Keywords: forests, biomass, climate change, trends, romania

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Authors: Sri E. Wati, D. Roswidyatmoko, N. Maslahatun, Gunawan, Andhika B. Taji

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Natural resource is the main sources to fulfill human needs. Its utilization must consider not only human prosperity but also sustainability. Balance of natural resources is a tool to manage natural wealth and to control land use change. This tool is needed to organize land use planning as stated on spatial plan in a certain region. Balance of natural resources can be calculated by comparing two-series of natural resource data obtained at different year. In this case, four years data period of land and forest were used (2010 and 2014). Land use data were acquired through satellite image interpretation and field checking. By means of GIS analysis, its result was then assessed with land use plan. It is intended to evaluate whether existing land use is suitable with land use plan. If it is improper, what kind of efforts and policies must be done to overcome the situation. Subosukawonosraten is rapid developed areas in Central Java Province. This region consists of seven regencies/cities which are Sukoharjo Regency, Boyolali Regency, Surakarta City, Karanganyar Regency, Wonogiri Regency, Sragen Regency, and Klaten Regency. This region is regarding to several former areas under Karasidenan Surakarta and their location is adjacent to Surakarta. Balance of forest resources show that width of forest area is not significantly changed. Some land uses within the area are slightly changed. Some rice field areas are converted into settlement (0.03%) whereas water bodies become vacant areas (0.09%). On the other hand, balance of land resources state that there are many land use changes in this region. Width area of rice field decreases 428 hectares and more than 50% of them have been transformed into settlement area and 11.21% is converted into buildings such as factories, hotels, and other infrastructures. It occurs mostly in Sragen, Sukoharjo, and Karanganyar Regency. The results illustrate that land use change in this region is mostly influenced by increasing of population number. Some agricultural lands have been converted into built-up area since demand of settlement, industrial area, and other infrastructures also increases. Unfortunately, recent utilization of more than a half of total area is not appropriate with land use plan declared in spatial planning document. It means, local government shall develop a strict regulation and law enforcement related to any violation in land use management.

Keywords: balance, forest, land, spatial plan

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Authors: Nato Kutaladze, George Mikuchadze, Giorgi Sokhadze

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Precipitation forecasts are one of the most demanding applications in numerical weather prediction (NWP). Georgia, as the whole Caucasian region, is characterized by very complex topography. The country territory is prone to flash floods and mudflows, quantitative precipitation estimation (QPE) and quantitative precipitation forecast (QPF) at any leading time are very important for Georgia. In this study, advanced research weather forecasting model’s skill in QPF is investigated over Georgia’s territory. We have analyzed several convection parameterization and microphysical scheme combinations for different rainy episodes and heavy rainy phenomena. We estimate errors and biases in accumulated 6 h precipitation using different spatial resolution during model performance verification for 12-hour and 24-hour lead time against corresponding rain gouge observations and satellite data. Various statistical parameters have been calculated for the 8-month comparison period, and some skills of model simulation have been evaluated. Our focus is on the formation and organization of convective precipitation systems in a low-mountain region. Several problems in connection with QPF have been identified for mountain regions, which include the overestimation and underestimation of precipitation on the windward and lee side of the mountains, respectively, and a phase error in the diurnal cycle of precipitation leading to the onset of convective precipitation in model forecasts several hours too early.

Keywords: extremal dependence index, false alarm, numerical weather prediction, quantitative precipitation forecasting

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Authors: K. Ismail, A. Ali, R. C. Hasan, I. Khalil, Z. Bachok, N. M. Said, A. M. Muslim, M. S. Che Din, W. S. Chong

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The marine ecosystem in Malaysia holds invaluable potential in terms of economics, food security, pharmaceuticals components and protection from natural hazards. Although exploration of oil and gas industry and fisheries are active within Malaysian waters, knowledge of the seascape and ecological functioning of benthic habitats is still extremely poor in the marine parks around Malaysia due to the lack of detailed seafloor information. Consequently, it is difficult to manage marine resources effectively, protect ecologically important areas and set legislation to safeguard the marine parks. The limited baseline data hinders scientific linkage to support effective marine spatial management in Malaysia. This became the main driver behind the first seabed mapping effort at the national level. Taman Laut Labuan (TLL) is located to the west coast of Sabah and to the east of South China Sea. The total area of TLL is approximately 158.15 km2, comprises of three islands namely Pulau Kuraman, Rusukan Besar and Rusukan Kecil and is characterised by shallow fringing reef with few submerged shallow reef. The unfamiliar rocky shorelines limit the survey of multibeam echosounder to area with depth more than 10 m. Whereas, singlebeam and side scan sonar systems were used to acquire the data for area with depth less than 10 m. By integrating data from multibeam bathymetry and backscatter with singlebeam bathymetry and side sonar images, we produce a substrate map and coral coverage map for the TLL using i) marine landscape mapping technique and ii) RSOBIA ArcGIS toolbar (developed by T. Le Bas). We take the initiative to explore the ability of aerial drone and satellite image (WorldView-3) to derive the depths and substrate type within the intertidal and subtidal zone where it is not accessible via acoustic mapping. Although the coverage was limited, the outcome showed a promising technique to be incorporated towards establishing a guideline to facilitate a standard practice for efficient marine spatial management in Malaysia.

Keywords: habitat mapping, marine spatial management, South China Sea, National seabed mapping

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Authors: Ahmad E. Aldousaria, Abdulla Al Kafy

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Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.

Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing

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Authors: Berhanu Keno Terfa

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Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: SHWETA SRIKUMAR

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Winter stratospheric dynamics is a highly variable and spectacular field of research in middle atmosphere. It is well believed that the interaction of energetic planetary waves with mean flow causes the temperature to increase in the stratosphere and associated circulation reversal. This wave driven sudden disturbances in the polar stratosphere is defined as Sudden Stratospheric Warming. The main objective of the present work is to investigate the mid-winter major stratospheric warming events on equatorial dynamics over Peninsular India. To explore the effect of mid-winter stratospheric warming on Indian region (60oE -100oE), we have selected the winters 2003/04, 2005/06, 2008/09, 2012/13 and 2018/19. This study utilized the data from ERA-Interim Reanalysis, Outgoing Longwave Radiation (OLR) from NOAA and TRMM satellite data from NASA mission. It is observed that a sudden drop in OLR (averaged over Indian Region) occurs during the course of warming for the winters 2005/06, 2008/09 and 2018/19. But in winters 2003/04 and 2012/13, drop in OLR happens prior to the onset of major warming. Significant amplitude of planetary wave activity is observed in equatorial lower stratosphere which indicates the propagation of extra-tropical planetary waves from high latitude to equator. During the course of warming, a strong downward propagation of EP flux convergence is observed from polar to equator region. The polar westward wind reaches upto 20oN and the weak eastward wind dominates the equator during the winters 2003/04, 2005/06 and 2018/19. But in 2012/13 winter, polar westward wind reaches upto equator. The equatorial wind at 2008/09 is dominated by strong westward wind. Further detailed results will be presented in the conference.

Keywords: Equatorial dynamics, Outgoing Longwave Radiation, Sudden Stratospheric Warming, Planetary Waves

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Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

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Authors: Vincent Schlageter, Maroua Mestiri, Florian Denzinger, Hugo Raetzo, Michel Demierre

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Precise landslide monitoring with differential global navigation satellite system (GNSS) is well known, but technical or economic reasons limit its application by geotechnical companies. This study demonstrates the reliability and the usefulness of Geomon (Infrasurvey Sàrl, Switzerland), a stand-alone and cost-effective rover network. The system permits deploying up to 15 rovers, plus one reference station for differential GNSS. A dedicated radio communication links all the modules to a base station, where an embedded computer automatically provides all the relative positions (L1 phase, open-source RTKLib software) and populates an Internet server. Each measure also contains information from an internal inclinometer, battery level, and position quality indices. Contrary to standard GNSS survey systems, which suffer from a limited number of beacons that must be placed in areas with good GSM signal, Geomon offers greater flexibility and permits a real overview of the whole landslide with good spatial resolution. Each module is powered with solar panels, ensuring autonomous long-term recordings. In this study, we have tested the system on several sites in the Swiss mountains, setting up to 7 rovers per site, for an 18 month-long survey. The aim was to assess the robustness and the accuracy of the system in different environmental conditions. In one case, we ran forced blind tests (vertical movements of a given amplitude) and compared various session parameters (duration from 10 to 90 minutes). Then the other cases were a survey of real landslides sites using fixed optimized parameters. Sub centimetric-accuracy with few outliers was obtained using the best parameters (session duration of 60 minutes, baseline 1 km or less), with the noise level on the horizontal component half that of the vertical one. The performance (percent of aborting solutions, outliers) was reduced with sessions shorter than 30 minutes. The environment also had a strong influence on the percent of aborting solutions (ambiguity search problem), due to multiple reflections or satellites obstructed by trees and mountains. The length of the baseline (distance reference-rover, single baseline processing) reduced the accuracy above 1 km but had no significant effect below this limit. In critical weather conditions, the system’s robustness was limited: snow, avalanche, and frost-covered some rovers, including the antenna and vertically oriented solar panels, leading to data interruption; and strong wind damaged a reference station. The possibility of changing the sessions’ parameters remotely was very useful. In conclusion, the rover network tested provided the foreseen sub-centimetric-accuracy while providing a dense spatial resolution landslide survey. The ease of implementation and the fully automatic long-term survey were timesaving. Performance strongly depends on surrounding conditions, but short pre-measures should allow moving a rover to a better final placement. The system offers a promising hazard mitigation technique. Improvements could include data post-processing for alerts and automatic modification of the duration and numbers of sessions based on battery level and rover displacement velocity.

Keywords: GNSS, GSM, landslide, long-term, network, solar, spatial resolution, sub-centimeter.

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Authors: Meredith M. Pratt

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The Atlantic sailfish (Istiophorus albicans) ranges from 40°N to 40°S in the Western Atlantic Ocean and has great economic and recreational value for sport fishers. Off the eastern coast of Florida, charter boats often target this species. Stuart, Florida, bills itself as the sailfish capital of the world. Sailfish tag data from The Billfish Foundation and NOAA was used to determine the relationship between sea surface temperature (SST) and the distribution of Atlantic sailfish caught and released over a fifteen-year period (2003 to 2018). Tagging information was collected from local sports fishermen in Florida. Using the time and location of each landed sailfish, a satellite-derived SST value was obtained for each point. The purpose of this study was to determine if sea surface warming was associated with changes in sailfish distribution. On average, sailfish were caught at 26.16 ± 1.70°C (x̄ ± s.d.) over the fifteen-year period. The most sailfish catches occurred at temperatures ranging from 25.2°C to 25.5°C. Over the fifteen-year period, sailfish catches decreased at lower temperatures (~23°C and ~24°C) and at 31°C. At ~25°C and ~30°C there was no change in catch numbers of sailfish. From 26°C to 29°C, there was an increase in the number of sailfish. Based on these results, increasing ocean temperatures will have an impact on the distribution and habitat utilization of sailfish. Warming sea surface temperatures create a need for more policy and regulation to protect the Atlantic sailfish and related highly migratory billfish species.

Keywords: atlantic sailfish, Billfish, istiophorus albicans, sea surface temperature

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Authors: Kacper Tomasz Kröber-Mulawa

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This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

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Authors: Abdullah Alsaeed

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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

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In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: Saleh Nabiyev

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Renewable energy is becoming increasingly important in today's world due to its significant impact on the green economy, ecology, environment, and climate change. Renewable energy sources, such as solar and wind, are clean and sustainable, making them an ideal solution to reduce carbon emissions and mitigate the effects of climate change. The Karabakh region is located in the South Caucasus and covers an area of approximately 11,500 km². The region has a mountainous terrain, which can affect the availability of wind and solar resources. The Karabakh region has significant wind power potential, particularly in its mountainous areas where wind speeds are typically higher. According to a study conducted by the European Commission Joint Research Centre, the average wind speed in the Karabakh region is between 4 and 6 meters per second (m/s) at a height of 50 meters above ground level (AGL). However, wind speeds can be higher in some areas, reaching up to 10 m/s in some mountainous areas. The region also has significant solar power potential, with an average of 2,000 to 2,200 hours of sunshine per year. The region's high altitude and clear skies make it particularly suitable for the development of solar power projects. In this research, the application of satellite images, solar radiation, wind speed and direction, as well as various other materials to determine suitable areas for alternative energy sources, is investigated. The methodology for selecting suitable locations for solar and wind energy consists of four main parts: identification of factors, evaluation of factors, data preparation, and application of suitability analysis. At the end of the research, the territory of the Kalbajar and Lachin districts is suitable for wind energy. The southern plain part of Karabakh is highly evaluated in terms of solar energy potential, especially Jabrayil district. Generally, outcomes taken from this research are essential data for increasing of rational using natural resources, as well as combating climate change.

Keywords: GIS, remote sensing, suitability analysis, solar energy, wind energy

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Prakash K. Aithal, U. Dinesh Acharya, Rajesh Gopakumar

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Edge is variation of brightness in an image. Edge detection is useful in many application areas such as finding forests, rivers from a satellite image, detecting broken bone in a medical image etc. The paper discusses about finding edge of multiple aerial images in parallel .The proposed work tested on 38 images 37 colored and one monochrome image. The time taken to process N images in parallel is equivalent to time taken to process 1 image in sequential. The proposed method achieves pixel level parallelism as well as image level parallelism.

Keywords: edge detection, multicore, gpu, opencl, mpi

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

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This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

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Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

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Authors: Rimmy Yadav, Anmol Preet Kaur

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Big Data has demonstrated the vast potential in streamlining, deciding, spotting business drifts in different fields, for example, producing, fund, Information Technology. This paper gives a multi-disciplinary diagram of the research issues in enormous information and its procedures, instruments, and system identified with the privacy, data storage management, network and energy utilization, adaptation to non-critical failure and information representations. Other than this, result difficulties and openings accessible in this Big Data platform have made.

Keywords: big data, privacy, data management, network and energy consumption

Procedia PDF Downloads 292

Authors: P. Priya Madhuri, J. Kamini, S. C. Jayanthi

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Assessment of land use and transportation networks is essential for sustainable urban growth, urban planning, efficient public transportation systems, and reducing traffic congestion. The study focuses on land use, population density, and their correlation with the road network for future development. The scope of the study covers inventory and assessment of the road network dataset (line) at the city, zonal, or ward level, which is extracted from very high-resolution satellite data (spatial resolution < 0.5 m) at 1:4000 map scale and ground truth verification. Road network assessment is carried out by computing various indices that measure road coverage and connectivity. In this study, an assessment of the road network is carried out for the study region at the municipal and ward levels. In order to identify gaps, road coverage and connectivity were associated with urban land use, built-up area, and population density in the study area. Ward-wise road connectivity and coverage maps have been prepared. To assess the relationship between road network metrics, correlation analysis is applied. The study's conclusions are extremely beneficial for effective road network planning and detecting gaps in the road network at the ward level in association with urban land use, existing built-up, and population.

Keywords: road connectivity, road coverage, road network, urban land use, transportation analysis

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Authors: Yeliz Sarı Nayim, B. Niyami Nayim

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Biotopes such as forest areas rich in biodiversity, wetlands, hedgerows and woodlands play important ecological roles in agricultural landscapes. Of these semi-natural areas and features, hedgerows are the most common landscape elements. Their most significant features are that they serve as a barrier between the agricultural lands, serve as shelter, add aesthetical value to the landscape and contribute significantly to the wildlife and biodiversity. Hedgerows surrounding agricultural landscapes also provide an important habitat for pollinators which are important for agricultural production. This study looks into the identification of hedgerows in agricultural lands in the Mugada rural area within Bartın province, Turkey. From field data and-and satellite images, it is clear that in this area, especially around rural settlements, large forest areas have been cleared for settlement and agriculture. A network of hedgerows is also apparent, which might potentially play an important role in the otherwise open agricultural landscape. We found that these hedgerows serve as an ecological and biological corridor, linking forest ecosystems. Forest patches of different sizes and creating a habitat network across the landscape. Some examples of this will be presented. The overall conclusion from the study is that ecologically, biologically and aesthetically important hedge biotopes should be maintained in the long term in agricultural landscapes such as this. Some suggestions are given for how they could be managed sustainably into the future.

Keywords: agricultural biotopes, Hedgerows, landscape ecology, Turkey

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

Procedia PDF Downloads 505

Authors: Aishwarya Shekhar, Himanshu Sharma

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Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

Procedia PDF Downloads 369

Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Tomy Prihananto, Damar Apri Sudarmadi

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Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

Procedia PDF Downloads 167

Authors: Amy Gooden

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When human genomic data is considered, this is often done through only one dimension of the law, or the interplay between the various dimensions is not considered, thus providing an incomplete picture of the legal framework. This research considers and analyzes the various dimensions in South African law applicable to genomic sequence data – including property rights, personality rights, and intellectual property rights. The effective use of personal genomic sequence data requires the acknowledgement and harmonization of the rights applicable to such data.

Keywords: artificial intelligence, data, law, genomics, rights

Procedia PDF Downloads 132