Search results for: georeferenced data

Authors: Bruno D. Souza, Gerson G. Cunha, Michael O. Ferreira, Roberto Rosenhaim, Robson C. Santos, Sergio O. Santos

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Devices and applications that use satellite-based positioning are becoming more popular day-by-day. Thus, evolution and improvement in this technology are mandatory. Accordingly, satellite georeferenced systems need to accomplish the same evolution rhythm. Either GPS (Global Positioning System) or its similar Russian GLONASS (Global Navigation Satellite System) are system samples that offer us powerful tools to plot coordinates on the earth surface. The development of this research aims the study of several aspects related to use of GPS and GLONASS technologies, given its application and collected data improvement during geodetic data acquisition. So, both relevant theoretic and practical aspects are considered. In this context, at the theoretical part, the main systems' characteristics are shown, observing its similarities and differences. At the practical part, a series of experiences are performed and obtained data packages are compared in order to demonstrate equivalence or differences among them. The evaluation methodology targets both quantitative and qualitative analysis provided by GPS and GPS/GLONASS receptors. Meanwhile, a specific collected data storage system was developed to better compare and analyze them (SisGeo - Georeferenced Research Comparison Support System).

Keywords: satellites, systems, applications, experiments, receivers

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Authors: Jakub Havlicek, Jiri Cajthaml

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The article describes the effect of the replacement of the used reference coordinate system in the georeferencing of an old map of Europe. In particular, it was the map entitled “Europe, the Map of Rivers and Mountains on a 1 : 12 000 000 Scale”, elaborated by professor D. Cipera and Dr. J. Metelka for Otto’s Geographic Atlas of 1924. The work was most likely produced using the equal-area conic (Albers) projection. The map was georeferenced into three types of projection – the equal-area conic, cylindrical Plate Carrée and cylindrical Mercator map projection. The map was georeferenced by means of the affine and the second-order polynomial transformation. The resulting georeferenced raster datasets from the Plate Carrée and Mercator projection were projected into the equal-area conic projection by means of projection equations. The output is the comparison of drawn graphics, the magnitude of standard deviations for individual projections and types of transformation.

Keywords: georeferencing, reference coordinate system, transformation, standard deviation

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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During the last 20 years, the globalization of economies, population growth, and the increase in the consumption of fresh agricultural products have generated greater demand for ornamentals, flowers, fresh fruits, and vegetables, mainly from tropical areas. This market situation has demanded greater competitiveness and control over production, with more efficient protected agriculture technologies, which provide greater productivity and allow us to guarantee the quality and quantity that is required in a constant and sustainable way. Guatemala, located in the north of Central America, is one of the largest exporters of agricultural products in the region and exports fresh vegetables, flowers, fruits, ornamental plants, and foliage, most of which were grown in greenhouses. Although there are no official agricultural statistics on greenhouse production, several thesis works, and congress reports have presented consistent estimates. A wide range of protection structures and roofing materials are used, from the most basic and simple ones for rain control to highly technical and automated structures connected with remote sensors for monitoring and control of crops. With this breadth of technological models, it is necessary to analyze georeferenced data related to the cultivated area, to the different existing models, and to the covering materials, integrated with altitude, climate, and soil data. The georeferenced registration of the production units, the data collection with digital tools, the use of satellite images, and geographic information systems (GIS) provide reliable tools to elaborate more complete, agile, and dynamic information maps. This study details a methodology proposed for gathering georeferenced data of high protection structures (greenhouses) in Guatemala, structured in four phases: diagnosis of available information, the definition of the geographic frame, selection of satellite images, and integration with an information system geographic (GIS). It especially takes account of the actual lack of complete data in order to obtain a reliable decision-making system; this gap is solved through the proposed methodology. A summary of the results is presented in each phase, and finally, an evaluation with some improvements and tentative recommendations for further research is added. The main contribution of this study is to propose a methodology that allows to reduce the gap of georeferenced data in protected agriculture in this specific area where data is not generally available and to provide data of better quality, traceability, accuracy, and certainty for the strategic agricultural decision öaking, applicable to other crops, production models and similar/neighboring geographic areas.

Keywords: greenhouses, protected agriculture, GIS, Guatemala, satellite image, digital tools, precision agriculture

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Authors: Mariana Roberta Ribeiro, Isabela de Cássia Caramello, Roberto Saverio Souza Costa

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Currently, one of the most important environmental problems is soil degradation. This wear is the result of inadequate agricultural practices, with water erosion as the main agent. As the runoff water is concentrated in certain points, it can reach a more advanced stage, which are the gullies. In view of this, the objective of this work was to evaluate which methodology is most suitable for the purpose of elaborating a project for the recovery of a gully, relating work time, data reliability, and the final cost. The work was carried out on a rural road in Monte Alto - SP, where there is 0.30 hectares of area under the influence of a gully. For the evaluation, an aerophotogrammetric survey was used with RPA, with georeferenced points, and with a GNSS L1/L2 receiver. To assess the importance of georeferenced points, there was a comparison of altimetric data using the support points with altimetric data using only the aircraft's internal GPS. Another method used was the survey by conventional topography, where coordinates were collected by total station and L1/L2 Geodetic GPS receiver. Statistical analysis was performed using analysis of variance (ANOVA) using the F test (p<0.05), and the means between treatments were compared using the Tukey test (p<0.05). The results showed that the surveys carried out by aerial photogrammetry and by conventional topography showed no significant difference for the analyzed parameters. Considering the data presented, it is possible to conclude that, when comparing the parameters of accuracy, the final volume of the gully, and cost, for the purpose of elaborating a project for the recovery of a gully, the methodologies of aerial photogrammetric survey and conventional topography do not differ significantly. However, when working time, use of labor, and project detail are compared, the aerial photogrammetric survey proves to be more viable.

Keywords: drones, erosion, soil conservation, technology in agriculture

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Authors: Maria Antonieta Erna Castillo Holly

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During the last decade, data analysis, strategic decision making, and the use of artificial intelligence (AI) tools in Latin American agriculture have been a challenge. In some countries, the availability, quality, and reliability of historical data, in addition to the current data recording methodology in the field, makes it difficult to use information systems, complete data analysis, and their support for making the right strategic decisions. This is something essential in Agriculture 4.0. where the increase in the global demand for fresh agricultural products of tropical origin, during all the seasons of the year requires a change in the production model and greater agility in the responses to the consumer market demands of quality, quantity, traceability, and sustainability –that means extensive data-. Having quality information available and updated in real-time on what, how much, how, when, where, at what cost, and the compliance with production quality standards represents the greatest challenge for sustainable and profitable agriculture in the region. The objective of this work is to present a methodological proposal for the collection of georeferenced data from the protected agriculture sector, specifically in production units (UP) with tall structures (Greenhouses), initially for Venezuela, taking the state of Mérida as the geographical framework, and horticultural products as target crops. The document presents some background information and explains the methodology and tools used in the 3 phases of the work: diagnosis, data collection, and analysis. As a result, an evaluation of the process is carried out, relevant data and dashboards are displayed, and the first satellite maps integrated with layers of information in a geographic information system are presented. Finally, some improvement proposals and tentatively recommended applications are added to the process, understanding that their objective is to provide better qualified and traceable georeferenced data for subsequent analysis of the information and more agile and accurate strategic decision making. One of the main points of this study is the lack of quality data treatment in the Latin America area and especially in the Caribbean basin, being one of the most important points how to manage the lack of complete official data. The methodology has been tested with horticultural products, but it can be extended to other tropical crops.

Keywords: greenhouses, protected agriculture, data analysis, geographic information systems, Venezuela

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Authors: Christian Bruss, Simona Gamba, Davide Azzolini, Federico Podestà

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In this paper, the authors assess the impact of different political and environmental shocks on the size and on the age and gender composition of asylum-related migration flows to Europe. With this paper, the authors contribute to the literature by looking at the impact of different political and environmental shocks on the gender and age composition of migration flows in addition to the size of these flows. Conflicting theories predict different outcomes concerning the relationship between political and environmental shocks and the migration flows composition. Analyzing the relationship between the causes of migration and the composition of migration flows could yield more insights into the mechanisms behind migration decisions. In addition, this research may contribute to better informing national authorities in charge of receiving these migrant, as women and children/the elderly require different assistance than young men. To be prepared to offer the correct services, the relevant institutions have to be aware of changes in composition based on the shock in question. The authors analyze the effect of different types of shocks on the number, the gender and age composition of first time asylum seekers originating from 154 sending countries. Among the political shocks, the authors consider: violence between combatants, violence against civilians, infringement of political rights and civil liberties, and state terror. Concerning environmental shocks, natural disasters (such as droughts, floods, epidemics, etc.) have been included. The data on asylum seekers applying to any of the 32 Schengen Area countries between 2008 and 2015 is on a monthly basis. Data on asylum applications come from Eurostat, data on shocks are retrieved from various sources: georeferenced conflict data come from the Uppsala Conflict Data Program (UCDP), data on natural disasters from the Centre for Research on the Epidemiology of Disasters (CRED), data on civil liberties and political rights from Freedom House, data on state terror from the Political Terror Scale (PTS), GDP and population data from the World Bank, and georeferenced population data from the Socioeconomic Data and Applications Center (SEDAC). The authors adopt a Difference-in-Differences identification strategy, exploiting the different timing of several kinds of shocks across countries. The highly skewed distribution of the dependent variable is taken into account by using count data models. In particular, a Zero Inflated Negative Binomial model is adopted. Preliminary results show that different shocks - such as armed conflict and epidemics - exert weak immediate effects on asylum-related migration flows and almost non-existent effects on the gender and age composition. However, this result is certainly affected by the fact that no time lags have been introduced so far. Finding the correct time lags depends on a great many variables not limited to distance alone. Therefore, finding the appropriate time lags is still a work in progress. Considering the ongoing refugee crisis, this topic is more important than ever. The authors hope that this research contributes to a less emotionally led debate.

Keywords: age, asylum, Europe, forced migration, gender

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Authors: Camila Lima, Murilo Andrade Valle, Patrícia Teixeira Leite Asano

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The growth in demand for electricity, caused by human development, depletion and environmental impacts caused by traditional sources of electricity generation have made new energy sources are increasingly encouraged and necessary for companies in the electricity sector. Based on this scenario, this paper assesses the negative environmental impacts associated with thermoelectric power plants in Brazil, pointing out the importance of using renewable energy sources, reducing environmental aggression. This article points out the existence of an energy alternative, wind energy, of the municipalities of São Paulo, represented by georeferenced maps with the help of GIS, using as a premise the indicators of sustainability and multicriteria analysis in the decision-making process.

Keywords: GIS (geographic information systems), multicriteria analysis, sustainability, wind energy

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Authors: S. Cencek, A. Markun

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Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

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Authors: Abderrazak Bannari, Ghadeer Kadhem

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The objectives of this paper are the validation and the evaluation of MBES-CARIS BASE surface data performance for bathymetric mapping of shallow water in the Kingdom of Bahrain. The latter is an archipelago with a total land area of about 765.30 km², approximately 126 km of coastline and 8,000 km² of marine area, located in the Arabian Gulf, east of Saudi Arabia and west of Qatar (26° 00’ N, 50° 33’ E). To achieve our objectives, bathymetric attributed grid files (X, Y, and depth) generated from the coverage of ship-track MBSE data with 300 x 300 m cells, processed with CARIS-HIPS, were downloaded from the General Bathymetric Chart of the Oceans (GEBCO). Then, brought into ArcGIS and converted into a raster format following five steps: Exportation of GEBCO BASE surface data to the ASCII file; conversion of ASCII file to a points shape file; extraction of the area points covering the water boundary of the Kingdom of Bahrain and multiplying the depth values by -1 to get the negative values. Then, the simple Kriging method was used in ArcMap environment to generate a new raster bathymetric grid surface of 30×30 m cells, which was the basis of the subsequent analysis. Finally, for validation purposes, 2200 bathymetric points were extracted from a medium scale nautical map (1:100 000) considering different depths over the Bahrain national water boundary. The nautical map was scanned, georeferenced and overlaid on the MBES-CARIS generated raster bathymetric grid surface (step 5 above), and then homologous depth points were selected. Statistical analysis, expressed as a linear error at the 95% confidence level, showed a strong correlation coefficient (R² = 0.96) and a low RMSE (± 0.57 m) between the nautical map and derived MBSE-CARIS depths if we consider only the shallow areas with depths of less than 10 m (about 800 validation points). When we consider only deeper areas (> 10 m) the correlation coefficient is equal to 0.73 and the RMSE is equal to ± 2.43 m while if we consider the totality of 2200 validation points including all depths, the correlation coefficient is still significant (R² = 0.81) with satisfactory RMSE (± 1.57 m). Certainly, this significant variation can be caused by the MBSE that did not completely cover the bottom in several of the deeper pockmarks because of the rapid change in depth. In addition, steep slopes and the rough seafloor probably affect the acquired MBSE raw data. In addition, the interpolation of missed area values between MBSE acquisition swaths-lines (ship-tracked sounding data) may not reflect the true depths of these missed areas. However, globally the results of the MBES-CARIS data are very appropriate for bathymetric mapping of shallow water areas.

Keywords: bathymetry mapping, multibeam echosounder systems, CARIS-HIPS, shallow water

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Authors: Andrea Gion Saluz, Tal Hertig, Axel Heinrich, Stefan Stevanovic

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Higher temperatures, seasonal changes in precipitation, and extreme weather events are increasingly affecting trees. To counteract the increasing challenges of urban trees, strategies are increasingly being sought to preserve existing tree populations on the one hand and to prepare for the coming years on the other. One such strategy lies in strategic climate tree species selection. The search is on for species or varieties that can cope with the new climatic conditions. Many efforts in German-speaking countries deal with this in detail, such as the tree lists of the German Conference of Garden Authorities (GALK), the project Stadtgrün 2021, or the instruments of the Climate Species Matrix by Prof. Dr. Roloff. In this context, different methods for a correct species selection are offered. One possibility is to select certain physiological attributes that indicate the climate resilience of a species. To calculate the dissimilarity of the present climate of different geographic regions in relation to the future climate of any city, a weighted (standardized) Euclidean distance (SED) for seasonal climate values is calculated for each region of the Earth. The calculation was performed in the QGIS geographic information system, using global raster datasets on monthly climate values in the 1981-2010 standard period. Data from a European forest inventory were used to identify tree species growing in the calculated analogue climate regions. The inventory used is the compilation of georeferenced point data at a 1 km grid resolution on the occurrence of tree species in 21 European countries. In this project, the results of the methodological application are shown for the city of Zurich for the year 2060. In the first step, analog climate regions based on projected climate values for the measuring station Kirche Fluntern (ZH) were searched for. In a further step, the methods mentioned above were applied to generate tree species lists for the city of Zurich. These lists were then qualitatively evaluated with respect to the suitability of the different tree species for the Zurich area to generate a cleaned and thus usable list of possible future tree species.

Keywords: climate change, climate region, climate tree, urban tree

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Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, João Casaca

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Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens sl. mosquitoes collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures), daily total rainfall, altitude, land use/land cover and proximity to water bodies are evaluated. Focus is on the mosquito females; the characterization of its habitat is the key for the planning of chirurgical non-aggressive prophylactic countermeasures to avoid ambient degradation. The GIS allow for the spatial determination of the zones were the mosquito mean captures has been above average; using the meteorological values at these coordinates, the limits of each parameter are identified/computed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the thresholds obtained for each parameter. The intersection of the maps obtained for each month show the evolution of the area favorable to the species through the mosquito season, which is from May to October at these latitudes. In parallel, mean and above average captures were related to the physiographic parameters. Three levels of risk could be identified for each parameter, using above average captures as an index. The results were applied to the suitability meteorological maps of each month. The Culex pipiens critical niche is delimited, reflecting the critical areas and the level of risk for transmission of the pathogens to which they are competent vectors (West Nile virus, iridoviruses, rheoviruses and parvoviruses).

Keywords: Culex pipiens, ecological niche, risk assessment, risk management

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Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Akinsola Oluwatosin, Udofia Samuel, Odofin Mayowa

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The study is aimed at assessing the Geographic Information System (GIS)-based spatial analysis of Survival Pattern and Treatment Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) cases for Lagos, Nigeria, with an objective to inform priority areas for public health planning and resource allocation. Multi-drug resistant tuberculosis (MDR-TB) develops due to problems such as irregular drug supply, poor drug quality, inappropriate prescription, and poor adherence to treatment. The shapefile(s) for this study were already georeferenced to Minna datum. The patient’s information was acquired on MS Excel and later converted to . CSV file for easy processing to ArcMap from various hospitals. To superimpose the patient’s information the spatial data, the addresses was geocoded to generate the longitude and latitude of the patients. The database was used for the SQL query to the various pattern of the treatment. To show the pattern of disease spread, spatial autocorrelation analysis was used. The result was displayed in a graphical format showing the areas of dispersing, random and clustered of patients in the study area. Hot and cold spot analysis was analyzed to show high-density areas. The distance between these patients and the closest health facility was examined using the buffer analysis. The result shows that 22% of the points were successfully matched, while 15% were tied. However, the result table shows that a greater percentage of it was unmatched; this is evident in the fact that most of the streets within the State are unnamed, and then again, most of the patients are likely to supply the wrong addresses. MDR-TB patients of all age groups are concentrated within Lagos-Mainland, Shomolu, Mushin, Surulere, Oshodi-Isolo, and Ifelodun LGAs. MDR-TB patients between the age group of 30-47 years had the highest number and were identified to be about 184 in number. The outcome of patients on ART treatment revealed that a high number of patients (300) were not ART treatment while a paltry 45 patients were on ART treatment. The result shows the Z-score of the distribution is greater than 1 (>2.58), which means that the distribution is highly clustered at a significance level of 0.01.

Keywords: tuberculosis, patients, treatment, GIS, MDR-TB

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Gus Calderon, Richard McCreight, Tammy Schwartz

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Forensic analysis of community wildfire destruction in California has shown that reducing or removing flammable vegetation in proximity to buildings and structures is one of the most important wildfire defenses available to homeowners. State laws specify the requirements for homeowners to create and maintain defensible space around all structures. Unfortunately, this decades-long effort had limited success due to noncompliance and minimal enforcement. As a result, vulnerable communities continue to experience escalating human and economic costs along the wildland-urban interface (WUI). Quantifying vegetative fuels at both the community and parcel scale requires detailed imaging from an aircraft with remote sensing technology to reduce uncertainty. FireWatch has been delivering high spatial resolution (5” ground sample distance) wildfire hazard maps annually to the community of Rancho Santa Fe, CA, since 2019. FireWatch uses a multispectral imaging system mounted onboard an aircraft to create georeferenced orthomosaics and spectral vegetation index maps. Using proprietary algorithms, the vegetation type, condition, and proximity to structures are determined for 1,851 properties in the community. Secondary data processing combines object-based classification of vegetative fuels, assisted by machine learning, to prioritize mitigation strategies within the community. The remote sensing data for the 10 sq. mi. community is divided into parcels and sent to all homeowners in the form of defensible space maps and reports. Follow-up aerial surveys are performed annually using repeat station imaging of fixed GPS locations to address changes in defensible space, vegetation fuel cover, and condition over time. These maps and reports have increased wildfire awareness and mitigation efforts from 40% to over 85% among homeowners in Rancho Santa Fe. To assist homeowners fighting increasing insurance premiums and non-renewals, FireWatch has partnered with Black Swan Analytics, LLC, to leverage the multispectral imagery and increase homeowners’ understanding of wildfire risk drivers. For this study, a subsample of 100 parcels was selected to gain a comprehensive understanding of wildfire risk and the elements which can be mitigated. Geospatial data from FireWatch’s defensible space maps was combined with Black Swan’s patented approach using 39 other risk characteristics into a 4score Report. The 4score Report helps property owners understand risk sources and potential mitigation opportunities by assessing four categories of risk: Fuel sources, ignition sources, susceptibility to loss, and hazards to fire protection efforts (FISH). This study has shown that susceptibility to loss is the category residents and property owners must focus their efforts. The 4score Report also provides a tool to measure the impact of homeowner actions on risk levels over time. Resiliency is the only solution to breaking the cycle of community wildfire destruction and it starts with high-quality data and education.

Keywords: defensible space, geospatial data, multispectral imaging, Rancho Santa Fe, susceptibility to loss, wildfire risk.

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

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Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

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Authors: Hoda A. Abdel Hafez

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Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: mining big data, big data, machine learning, telecommunication

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Authors: Louis Nahimana

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Most maps are in a raster or pdf format and it is not easy to get vector layers of published maps. Faced to the production of geological simplified map of the northern Lake Tanganyika countries without geological information in vector format, I tried a method of obtaining vector layers from raster layers created from geological maps of Rwanda and DR Congo in pdf and jpg format. The procedure was as follows: The original raster maps were georeferenced using ArcGIS10.2. Under Adobe Photoshop, map areas with the same color corresponding to a lithostratigraphic unit were selected all over the map and saved in a specific raster layer. Using the same image processing software Adobe Photoshop, each RGB raster layer was converted in grayscale type and improved before importation in ArcGIS10. After georeferencing, each lithostratigraphic raster layer was transformed into a multitude of polygons with the tool "Raster to Polygon (Conversion)". Thereafter, tool "Aggregate Polygons (Cartography)" allowed obtaining a single polygon layer. Repeating the same steps for each color corresponding to a homogeneous rock unit, it was possible to reconstruct the simplified geological constitution of Rwanda and the Democratic Republic of Congo in vector format. By using the tool «Append (Management)», vector layers obtained were combined with those from Burundi to achieve vector layers of the geology of the « Northern Lake Tanganyika countries ».

Keywords: creating raster layer under image processing software, raster to polygon, aggregate polygons, adobe photoshop

Procedia PDF Downloads 412

Authors: Theertha Chandroth

Abstract:

This paper presents a comparative study on how to check JSON (JavaScript Object Notation) data against XML (eXtensible Markup Language) data from a software testing point of view. JSON and XML are widely used data interchange formats, each with its unique syntax and structure. The objective is to explore various techniques and methodologies for validating comparison and integration between JSON data to XML and vice versa. By understanding the process of checking JSON data against XML data, testers, developers and data practitioners can ensure accurate data representation, seamless data interchange, and effective data validation.

Keywords: XML, JSON, data comparison, integration testing, Python, SQL

Procedia PDF Downloads 79

Authors: Bolin Hua

Abstract:

In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

Procedia PDF Downloads 342

Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

Procedia PDF Downloads 482

Authors: Roman Bieda

Abstract:

The General Data Protection Regulation (GDPR) will come into force on 25 May 2018 which will create a new legal framework for the protection of personal data in the European Union. Article 20 of GDPR introduces a right to data portability. This right allows for data subjects to receive the personal data which they have provided to a data controller, in a structured, commonly used and machine-readable format, and to transmit this data to another data controller. The right to data portability, by facilitating transferring personal data between IT environments (e.g.: applications), will also facilitate changing the provider of services (e.g. changing a bank or a cloud computing service provider). Therefore, it will contribute to the development of competition and the digital market. The aim of this paper is to discuss the right to data portability and its influence on the development of new digital services.

Keywords: data portability, digital market, GDPR, personal data

Procedia PDF Downloads 433

Authors: Savas Yildiz

Abstract:

The article assesses the performance of international aid donors to determine the sub-national distribution of their aid projects dependent on recipient countries’ governance. The present paper extends the scope from a cross-country perspective to a more detailed analysis by looking at the effects of institutional qualities on the sub-national distribution of foreign aid. The analysis examines geo-referenced aid project in 37 countries and 404 regions at the first administrative division level in Sub-Saharan Africa from the World Bank (WB) and the African Development Bank (ADB) that were approved between the years 2000 and 2011. To measure the influence of institutional qualities on the distribution of aid the following measures are used: control of corruption, government effectiveness, regulatory quality and rule of law from the World Governance Indicators (WGI) and the corruption perception index from Transparency International. Furthermore, to assess the importance of ethnic heterogeneity on the sub-national distribution of aid projects, the study also includes interaction terms measuring ethnic fragmentation. The regression results indicate a general skew of aid projects towards regions which hold capital cities, however, being incumbent presidents’ birth region does not increase the allocation of aid projects significantly. Nevertheless, with increasing quality of institutions aid projects are less skewed towards capital regions and the previously estimated coefficients loose significance in most cases. Higher ethnic fragmentation also seems to impede the possibility to allocate aid projects mainly in capital city regions and presidents’ birth places. Additionally, to assess the performance of the WB based on its own proclaimed goal to aim the poor in a country, the study also includes sub-national wealth data from the Demographic and Health Surveys (DSH), and finds that, even with better institutional qualities, regions with a larger share from the richest quintile receive significantly more aid than regions with a larger share of poor people. With increasing ethnic diversity, the allocation of aid projects towards regions where the richest citizens reside diminishes, but still remains high and significant. However, regions with a larger share of poor people still do not receive significantly more aid. This might imply that the sub-national distribution of aid projects increases in general with higher ethnic fragmentation, independent of the diverse regional needs. The results provide evidence that institutional qualities matter to undermine the influence of incumbent presidents on the allocation of aid projects towards their birth regions and capital regions. Moreover, even for countries with better institutional qualities the WB and the ADB do not seem to be able to aim the poor in a country with their aid projects. Even, if one considers need-based variables, such as infant mortality and child mortality rates, aid projects do not seem to be allocated in districts with a larger share of people in need. Therefore, the study provides further evidence using more detailed information on the sub-national distribution of aid projects that aid is not being allocated effectively towards regions with a larger share of poor people to alleviate poverty in recipient countries directly. Institutions do not have any significant influence on the sub-national distribution of aid towards the poor.

Keywords: aid allocation, georeferenced data, institutions, spatial analysis

Procedia PDF Downloads 86

Authors: Fahad Hanash Alzahrani

Abstract:

This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

Procedia PDF Downloads 361

Authors: Mehmet Akif Aslan, Mehmet Simsek, Eyup Sensoy

Abstract:

Big Data stands for today’s cutting-edge technology. As the technology becomes widespread, so does Data. Utilizing massive data sets enable companies to get competitive advantages over their adversaries. Out of many area of Big Data usage, logistics has significance role in both commercial sector and military. This paper lays out what big data is and how it is used in both military and commercial logistics.

Keywords: big data, logistics, operational efficiency, risk management

Procedia PDF Downloads 605

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

Procedia PDF Downloads 336

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

Procedia PDF Downloads 124