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Journal articles on the topic 'Geography – Data processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Ikhsan, Fahrudi Ahwan, Fahmi Arif Kurnianto, Bejo Apriyanto, and Elan Artono Nurdin. "GEOGRAPHY SKILLS DOMAIN TAXONOMY." Geosfera Indonesia 2, no. 1 (April 30, 2018): 54. http://dx.doi.org/10.19184/geosi.v2i1.7525.

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This study aims to explain the geography student skills domain. The focus of this research is the domain of geography skills possessed by students. The research method with the a qualitative approach. Subjects were students of Jember University geography education consisting of 2 men and 2 women with indicators of academic ability value of the national geography exam results. Data collection techniques by observation and interview. Data were analyzed using the processing unit, categorization and interpretation of data. The findings show that the skills of geography for prospective teachers of geography and geographers to be possessed composed as follows: 1st level thinking skills geography (space, phenomena, location and place, region, environment, coordinate, and humans), level 2 skills of analysis geography (scale, distribution, patterns of interaction, interrelation, connectivity, corologi, descriptions, and agglomeration), and level 3 skills of geographic applications (mapping/cartography, remote sensing, geographic information systems, surveying and mapping of the area, and Global Position systems (GPS). This level difference is used to distinguish the use of knowledge and application of the science of geography. Keywords: Students of geography education, geography Skills

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Zolnikova, Julia, Eugeni Ovsyannikov, and Ivan Soloviev. "Geoinformation support of the academic discipline “Geography of the population with the basics of demography”." InterCarto. InterGIS 26, no. 1 (2020): 279–88. http://dx.doi.org/10.35595/2414-9179-2020-1-26-279-288.

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The authors pointed out that the rapid growth of technical supply and the emergence of new information and communication technologies has led to the common usage of new technologies towards the various functions and needs of higher education. A university graduate should have the skills to develop and use information systems for decision support as a basic framework for analyzing unfolding situations, developing informed decisions and as a result — problem-solving. The connecting link for professional skills development appears as a GIS technology usage. GIS provide unique opportunities for its implementation in educational programs putting in touch with forecasting and analysis of the phenomena of the world around us; there are comprehension and allocation of the main causes and factors, possible consequences, with subsequent planning and adoption of strategic decisions of the actions taken. Geoinformation technologies can change the content of activities for both teachers and students. GIS technologies allow to master the methods of data gathering and processing; development of models and forecasts for specific geographical problem-solving. Students, using GIS, unaidedly obtain data, absorb new methods of data processing, receive best practices for working in various fields. The article gives a description and analyzes of the GIS usage for studying the course “Population geography with the demography basics”. The GIS usage for studying the course “Population geography with the demography basics” allows to significantly diversify the methods and forms of laboratory studies, student’s research work. In the course of work with GIS, a geographer comprehends the features of spatial data presented in digital form, analyzes geographic data, presents geographic data in the form of maps, tables, graphs.

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Bezvoda, Václav, and Tomáš Kučera. "On the possibilities of using data-analytic systems in geography." Geografie 91, no. 2 (1986): 133–39. http://dx.doi.org/10.37040/geografie1986091020133.

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The transition from traditional to modern concepts in geography requires multidimensional data sets to be taken into account. Apart from other methods of corresponding data processing an important role is played by the factor analysis, possibilities and limitations of which are analysed in the article. Attention is also paid to the data-analytical systems (especially BMDP) which make the multivariant methods easy to use.

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Yongjun, Zhang. "Combined GPS/GLONASS data processing." Geo-spatial Information Science 5, no. 4 (January 2002): 32–36. http://dx.doi.org/10.1007/bf02826472.

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SOH, CHEE-KIONG, WOON-PENG WONG, KOK-WAI PHANG, and KUM-YEW LAI. "INTEGRATING KNOWLEDGE AND DATA PROCESSING FOR CONSTRUCTION SCHEDULING." Civil Engineering Systems 12, no. 4 (November 1995): 287–305. http://dx.doi.org/10.1080/02630259508970178.

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Skoks, Viktors, and Christian Steurer. "An Overview of the Use of GML in Modern Spatial Data Infrastructures." Scientific Journal of Riga Technical University. Computer Sciences 42, no. 1 (January 1, 2010): 60–67. http://dx.doi.org/10.2478/v10143-010-0043-5.

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An Overview of the Use of GML in Modern Spatial Data InfrastructuresThis paper introduces an overview of the use of Geography Markup Language in modern Spatial Data Infrastructures. The goal of the paper was to indicate some of the main consequences of the use of Geography Markup Language in the important geospatial data harmonisation processes, both search and access, which are in current use. In order to show a practical example of the use of Geography Markup Language, the system for Earth observation data processing and distribution at the Institute for Applied Remote Sensing at EURAC, Bolzano was studied. The results of the paper set out how Geography Markup Language is used in modern Spatial Data Infrastructures, and the degree to which the Geography Markup Language standard is helpful in achieving data harmonisation and interoperability.

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Bakli, Mohamed, Mahmoud Sakr, and Taysir Hassan A. Soliman. "HadoopTrajectory: a Hadoop spatiotemporal data processing extension." Journal of Geographical Systems 21, no. 2 (February 1, 2019): 211–35. http://dx.doi.org/10.1007/s10109-019-00292-4.

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Shi, Dinghao. "Principle and Application of Complex Function in Geography, Optics, Communication Engineering." Highlights in Science, Engineering and Technology 88 (March 29, 2024): 86–91. http://dx.doi.org/10.54097/10g7qe09.

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As a matter of fact, complex function has been widely used in various fields. This study explores the applications of complex functions in the fields of geography, optics, and communication engineering. By analyzing practical problems in different domains, scholars have discovered the unique value and prospects of complex functions in these areas. By integrating complex function theory with geographic data analysis, one has achieved efficient processing and analysis of geographic data and especially in calculating the minimum height. In the field of optics, one has utilized complex function methods to study the imaging and transmission characteristics of optical systems and image fusion and have achieved satisfactory results. Additionally, this study has introduced complex functions into the field of communication engineering, studying transforming the signal in the time domain into the frequency domain. The findings of this research enrich the theoretical content of scientific fields such as geography, optics, and communication engineering, providing strong support and references for related work.

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Hongian, You, Liu Schaochuang, and Li Shukai. "Data processing technology of airborne 3D image." Geo-spatial Information Science 4, no. 3 (January 2001): 62–67. http://dx.doi.org/10.1007/bf02826926.

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Whiteaker, T. L., D. R. Maidment, H. Gopalan, C. Patino, and D. C. Mckinney. "Raster‐network regionalization for watershed data processing." International Journal of Geographical Information Science 21, no. 3 (March 2007): 341–53. http://dx.doi.org/10.1080/13658810600965255.

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Priandana, Rangga Kusuma, and Indra Indra. "Rule-Based Natural Language Processing in Volcanic Ash Data Searching System." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 18, no. 1 (January 31, 2024): 49. http://dx.doi.org/10.22146/ijccs.88081.

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Indonesia is a country with a unique geography. The confluence of three tectonic plates located in the country results in frequent natural disasters, from earthquakes to volcanic activity. BMKG is a monitoring agency tasked with providing information related to these natural disasters. However, one type of natural disaster data, the SIGMET data (Significant Meteorological Information) used to provide information on volcanic ash, has a complicated format that is difficult for ordinary people to understand. Therefore, this research seeks to make finding information related to volcanic ash and volcanic eruptions in Indonesia easier in terms of access and comprehension. In this research, an application design will be carried out that can search SIGMET data by implementing natural language processing with a production rule base. The research results have an accuracy rate of 84% using 25 test sample sentences that combine sentences and words contained in the important words section.

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Abril Fradel, Diego Orlando, and José Nelson Pérez Castillo. "Current data warehousing and OLAP technologies’ status applied to spatial databases." Ingeniería e Investigación 27, no. 1 (January 1, 2007): 58–67. http://dx.doi.org/10.15446/ing.investig.v27n1.14782.

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Organisations require their information on a timely, dynamic, friendly, centralised and easy-to-access basis for analysing it and taking correct decisions at the right time. Centralisation can be achieved with data warehouse technology. On-line analytical processing (OLAP) is used for analysis. Technologies using graphics and maps in data presentation can be exploited for an overall view of a company and helping to take better decisions. Geographic information systems (GIS) are useful for spatially locating information and representing it using maps. Data warehouses are generally implemented with a multidimensional data model to make OLAP analysis easier. A fundamental point in this model is the definition of measurements and dimensions; geography lies within such dimensions. Many researchers have concluded that the geographic dimension is another attribute for describing data in current analysis systems but without having an in-depth study of its spatial feature and without locating them on a map, like GIS does. Seen this way, interoperability is necessary between GIS and OLAP (called spatial OLAP or SOLAP) and several entities are currently researching this. This document summarises the current status of such research.

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Liu, Lilong, Hongyan Wen, and Bin Liu. "Comparison of models for GPS kinematic data processing." Geo-spatial Information Science 11, no. 2 (January 2008): 152–56. http://dx.doi.org/10.1007/s11806-008-0049-0.

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Werner, Piotr. "Szanse reintegracji a remediacja cyfrowa geografii." Prace i Studia Geograficzne 69, no. 1 (March 31, 2024): 41–64. http://dx.doi.org/10.48128/pisg/2024-69.1-03.

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Nowadays, geographers and specialists in other disciplines perceive information and communication technologies, including GIS software, as part of the inevitable changes in practice and science (including geography). Recent ways of generating, processing, storing, analyzing and sharing data, creating and sharing texts, visualizing, mapping, analyzing, communicating ideas, video, podcasts, and presentations, sharing information, social networks and mainstream media are entirely dependent on computing technologies. Modern science in the digital age uses big data, artificial intelligence – machine learning methods (data mining, pattern recognition, geovisualization, spatial statistics, optimization and spatial simulation), which in turn have renewed interest in and ties with the fields of computational social sciences and data-driven geography, to gain deeper insights into quantitative, time-scale, multi-resolution and multi-scale research. The tool and product of a geographer’s research is, among other things, the map, a medium, a vehicle for geographic theories and ideas and a tool for conveying geo-information. However, the remediation of a traditional map into a digital map involves the transformation, addition, restriction or change of the meaning system of the original. The new digital medium arouses different attitudes, different emotions and triggers new practices of receiving geo-information among professionals and the public. Undoubtedly, this also applies to researchers–geographers who apply in their geospatial research multi-, inter- or transdisciplinary approaches based on different research paradigms. Integrated and problem-focused scientific discourse in geographic research and digital remediation of maps allow us to look at the future of (currently diversified) geographic research with some hope for its reintegration. The aim of the paper is to identify the possibilities, current and prospective paths and research topics of geography in Poland, which are interdisciplinary, combining the field of interest of physical, socio-economic geographers and specialists of space economy, using the modern instrumentarium of information and communication technologies in geography, i.e. geographic information systems.

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Sudirman, Sudirman. "Pelatihan Pengolahan Data Penelitian Pendidikan IPA Menggunakan STATA Data Analysis." Jurnal Pengabdian UNDIKMA 4, no. 3 (August 19, 2023): 621. http://dx.doi.org/10.33394/jpu.v4i3.8481.

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The community service aims to increase the capacity of Universitas Qamarul Huda Badaruddin (UNIQHBA) lecturers in processing and analyzing science education research data using STATA Software. The method of community service was used for interactive training for two weeks with the Zoom application for 37 lecturers from UNIQHBA. To determine the participants' ability to use the STATA software, practice processing and data analysis were carried out using a science education case study guide provided by the facilitator. The evaluation was carried out at the end of the training to get participants' responses through online questionnaires that were then analyzed descriptively. The results of this community service were that as many as 89.32% of the participants were able to complete the practice correctly based on the assignments given, 89.74% of the presentations given by the facilitator were clear and easy to understand and will use STATA for the processing and analysis of their research data because it was easy to use. Most of the participants recommended further training using the STATA Software.

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WILLIAMS, R. D. "New Methods for Storing and Processing Spatial Data." New Zealand Geographer 46, no. 1 (April 1990): 4–9. http://dx.doi.org/10.1111/j.1745-7939.1990.tb01939.x.

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Smith, M. W., J. L. Carrivick, and D. J. Quincey. "Structure from motion photogrammetry in physical geography." Progress in Physical Geography: Earth and Environment 40, no. 2 (November 26, 2015): 247–75. http://dx.doi.org/10.1177/0309133315615805.

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Accurate, precise and rapid acquisition of topographic data is fundamental to many sub-disciplines of physical geography. Technological developments over the past few decades have made fully distributed data sets of centimetric resolution and accuracy commonplace, yet the emergence of Structure from Motion (SfM) with Multi-View Stereo (MVS) in recent years has revolutionised three-dimensional topographic surveys in physical geography by democratising data collection and processing. SfM-MVS originates from the fields of computer vision and photogrammetry, requires minimal expensive equipment or specialist expertise and, under certain conditions, can produce point clouds of comparable quality to existing survey methods (e.g. Terrestrial Laser Scanning). Consequently, applications of SfM-MVS in physical geography have multiplied rapidly. There are many practical options available to physical geographers when planning a SfM-MVS survey (e.g. platforms, cameras, software), yet, many SfM-MVS end-users are uncertain as to the errors associated with each choice and, perhaps most fundamentally, the processes actually taking place as part of the SfM-MVS workflow. This paper details the typical workflow applied by SfM-MVS software packages, reviews practical details of implementing SfM-MVS, combines existing validation studies to assess practically achievable data quality and reviews the range of applications of SfM-MVS in physical geography. The flexibility of the SfM-MVS approach complicates attempts to validate SfM-MVS robustly as each individual validation study will use a different approach (e.g. platform, camera, georeferencing method, etc.). We highlight the need for greater transparency in SfM-MVS processing and enhanced ability to adjust parameters that determine survey quality. Looking forwards, future prospects of SfM-MVS in physical geography are identified through discussion of more recent developments in the fields of image analysis and computer vision.

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Jarolímek, Jan, Jan Pavlík, Jana Kholova, and Swarna Ronanki. "Data Pre-processing for Agricultural Simulations." Agris on-line Papers in Economics and Informatics 11, no. 01 (March 30, 2019): 49–53. http://dx.doi.org/10.7160/aol.2019.110105.

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Pakdil, Mete Ercan, and Rahmi Nurhan Çelik. "Serverless Geospatial Data Processing Workflow System Design." ISPRS International Journal of Geo-Information 11, no. 1 (December 30, 2021): 20. http://dx.doi.org/10.3390/ijgi11010020.

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Geospatial data and related technologies have become an increasingly important aspect of data analysis processes, with their prominent role in most of them. Serverless paradigm have become the most popular and frequently used technology within cloud computing. This paper reviews the serverless paradigm and examines how it could be leveraged for geospatial data processes by using open standards in the geospatial community. We propose a system design and architecture to handle complex geospatial data processing jobs with minimum human intervention and resource consumption using serverless technologies. In order to define and execute workflows in the system, we also propose new models for both workflow and task definitions models. Moreover, the proposed system has new Open Geospatial Consortium (OGC) Application Programming Interface (API) Processes specification-based web services to provide interoperability with other geospatial applications with the anticipation that it will be more commonly used in the future. We implemented the proposed system on one of the public cloud providers as a proof of concept and evaluated it with sample geospatial workflows and cloud architecture best practices.

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Dasgupta, Siddhartha, Steven Mims, and Richard Onders. "THE ECONOMICS AND MANAGEMENT OF SMALL-SCALE FISH PROCESSING PLANTS USING PADDLEFISH PROCESSING DATA FROM KENTUCKY." Aquaculture Economics & Management 12, no. 1 (January 2008): 39–53. http://dx.doi.org/10.1080/13657300801959621.

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Новосад, E. Novosad, Христиановский, and Pavel Khristianovskiy. "GIS-based risk monitoring of zoonotic cestodiasis in human." Russian Journal of Parasitology 3, no. 4 (December 25, 2016): 475–87. http://dx.doi.org/10.12737/23071.

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Objective of research: The target of the paper is to develop a model of GIS-based risk monitoring of zoonotic cestodiasis in human. Materials and methods: The use of geographic information systems (GIS) as an epizootiological and epidemiological method for the risk-based monitoring of human cestodiasis enables the development of a multi-level platform for solution of a wide range of tasks related to the control of this disease. The modern GIS tools use the methods of geoinformatics applying powerful software and hardware: open access geographic web servers, tools for multidimensional complex analysis, creating most accurate electronic and paper maps. Full-featured GIS contain a full set for processing geospatial data including acquisition of data, its integration and storage, automatic data processing, editing, creation and maintenance of topology, spatial analysis, access to the database management system (DBMS), visualization and creation of hard copies of any cartographic data. Results and discussion: The use of GIS enables to study more closely the regularities of epizootic process, geography of human cestodiasis and to improve the methodology both for short-term and long-term retrospective epizootiological analyses.

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Mokbel, Mohamed F., Xiaopeng Xiong, Moustafa A. Hammad, and Walid G. Aref. "Continuous Query Processing of Spatio-Temporal Data Streams in PLACE." GeoInformatica 9, no. 4 (November 8, 2005): 343–65. http://dx.doi.org/10.1007/s10707-005-4576-7.

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Han, Fang, Aidos Adai, and Bimerei Daurenkyzy Zhandilla. "Application of GIS technology in cross-border tourism cooperation planning. Taking the analysis of the spatial pattern of cross-border eco-tourism cooperation in the Altai Mountains region as an example." Bulletin of the Karaganda University. “Biology, medicine, geography Series” 110, no. 2 (June 30, 2023): 199–205. http://dx.doi.org/10.31489/2023bmg2/199-205.

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Since the 1960s, the application of GIS technology in the field of geography has led geography to the development path of informatization and digitization. GIS technology, which focuses on spatial information analysis and spatial data management, has become an important spatial system for geographic exploration. GIS technology has extremely important advantages in collecting, processing, simulating, analyzing and expressing geospatial data. Object: This paper takes the spatial pattern of cross-border tourism cooperation in the Altai Mountains region as the research object. Methods: The research methods are: the terrain analysis, threedimensional scene simulation, data statistics, suitability analysis, visual domain analysis, transportation network analysis, and project site selection of GIS technology in tourism planning. Results: The presented research is analytical in nature. The specific application of GIS technology in tourism planning is discussed. Also, 7 types of GIS applications were considered in the paper. In summary, GIS is mainly composed of data input system, data management system, spatial analysis system and data output system. It has very important application value in tourism management and development.

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Zequn, Guan, and Li Deren. "Study on gis data directly integrated into image processing." Geo-spatial Information Science 3, no. 4 (January 2000): 16–19. http://dx.doi.org/10.1007/bf02829390.

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Aronoff, Stan, and Hugh Parliament. "From data to information ‐ image processing for decision making." Geocarto International 2, no. 3 (September 1987): 25–30. http://dx.doi.org/10.1080/10106048709354104.

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Liakos, Leonidas, and Panos Panagos. "Challenges in the Geo-Processing of Big Soil Spatial Data." Land 11, no. 12 (December 13, 2022): 2287. http://dx.doi.org/10.3390/land11122287.

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This study addressed a critical resource—soil—through the prism of processing big data at the continental scale. Rapid progress in technology and remote sensing has majorly improved data processing on extensive spatial and temporal scales. Here, the manuscript presents the results of a systematic effort to geo-process and analyze soil-relevant data. In addition, the main highlights include the difficulties associated with using data infrastructures, managing big geospatial data, decentralizing operations through remote access, mass processing, and automating the data-processing workflow using advanced programming languages. Challenges to this study included the reproducibility of the results, their presentation in a communicative way, and the harmonization of complex heterogeneous data in space and time based on high standards of accuracy. Accuracy was especially important as the results needed to be identical at all spatial scales (from point counts to aggregated countrywide data). The geospatial modeling of soil requires analysis at multiple spatial scales, from the pixel level, through multiple territorial units (national or regional), and river catchments, to the global scale. Advanced mapping methods (e.g., zonal statistics, map algebra, choropleth maps, and proportional symbols) were used to convey comprehensive and substantial information that would be of use to policymakers. More specifically, a variety of cartographic practices were employed, including vector and raster visualization and hexagon grid maps at the global or European scale and in several cartographic projections. The information was rendered in both grid format and as aggregated statistics per polygon (zonal statistics), combined with diagrams and an advanced graphical interface. The uncertainty was estimated and the results were validated in order to present the outputs in the most robust way. The study was also interdisciplinary in nature, requiring large-scale datasets to be integrated from different scientific domains, such as soil science, geography, hydrology, chemistry, climate change, and agriculture.

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Shavrov, S. A. "CHARACTERISTICS OF A DATA PROCESSING TECHNOLOGY FOR THE REVISION OF DIGITAL MAPS." Mapping Sciences and Remote Sensing 24, no. 2 (April 1987): 96–103. http://dx.doi.org/10.1080/07493878.1987.10641660.

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Komarov, S. A., V. L. Mironov, A. N. Romanov, and A. V. Yevtyushkin. "REMOTE SENSING OF THE WATER TABLE: MEASUREMENT AND A DATA PROCESSING ALGORITHM." Mapping Sciences and Remote Sensing 36, no. 1 (January 1999): 1–10. http://dx.doi.org/10.1080/07493878.1999.10642103.

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Smith, James W. F., and Ian A. Campbell. "Error in polygon overlay processing of geomorphic data." Earth Surface Processes and Landforms 14, no. 8 (December 1989): 703–17. http://dx.doi.org/10.1002/esp.3290140805.

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DEMİRCİ, Ömer, and Zekeriya Fatih İNEÇ. "An Examination of Digital Geography Games and Their Effects on Mathematical Data Processing and Social Studies Education Skills." Acta Didactica Napocensia 16, no. 1 (August 31, 2023): 215–32. http://dx.doi.org/10.24193/adn.16.1.15.

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"This study aims to advance the development of the mathematical processing skills of students by suggesting the use of digital geography games. This includes an analysis of its contribution to the standard mathematics curriculum in areas such as data processing as well as its contribution to social studies curricula in areas such as map literacy, location analysis, problem solving, and other skills related to understanding tables, graphs, and diagrams. The study also examines the findings of the experts that relate to these dynamics. A case study of a digital geography game called Gezgin, developed by İneç (2021) is examined in this research using qualitative research approaches. Under this framework, the data obtained by critical case sampling from six experts through a semi-structured online interview were collected with cloud technologies and examined by using a content analysis. The findings obtained showed that the use of Gezgin can help develop skills related to data processing, problem solving, problem formulation, general mathematical processes, the ability to transfer mathematics to real life, and the ability to create and correctly interpret tables and graphs. The findings also indicate that the real-life context that is provided by this game supports educational development in the areas of map literacy, location analysis, problem-solving skills and graph, table and diagram creation and interpretation for social studies curricula. The expert opinions about Gezgin were determined to be mostly positive, especially with respect to the interdisciplinary structure and its rich content, but some of its functions were found to be limited."

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LIU, Yongming, Ruru DENG, Yan QIN, and Yeheng LIANG. "Data processing methods and applications of airborne LiDAR bathymetry." National Remote Sensing Bulletin 21, no. 6 (2017): 982–95. http://dx.doi.org/10.11834/jrs.20176395.

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Roy, Parth Sarathi. "Montane vegetation stratification through digital processing of landsat MSS data." Geocarto International 2, no. 1 (March 1987): 19–26. http://dx.doi.org/10.1080/10106048709354078.

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Hosen, Bappa, Mosfudar Rahaman, Shailesh Kumar, Lalit Sagar, and Md Nazir Akhtar. "LEVERAGING ARTIFICIAL INTELLIGENCE AND BIG DATA FOR ADVANCED SPATIAL ANALYTICS AND DECISION SUPPORT SYSTEMS IN GEOGRAPHY." Malaysian Applied Geography 1, no. 2 (July 24, 2023): 62–67. http://dx.doi.org/10.26480/magg.02.2023.62.67.

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Geospatial artificial intelligence (GeoAI) is an emerging scientific discipline that combines innovations in spatial science, artificial intelligence methods in machine learning, data mining, and high-performance computing to extract knowledge from spatial big data. GeoAI, or geospatial artificial intelligence, has become an emerging topic and the frontier for spatial analytics in Geography. This study explores how these technologies can enhance spatial analysis and decision support systems, leading to more accurate, efficient, and sustainable outcomes. The integration of AI and Big Data facilitates improved data acquisition and management, enabling the processing of large volumes of geospatial data. The paper highlighted the applications of AI and Big Data in geography, such as optimizing urban development, environmental monitoring, and disaster management. However, it also acknowledges the challenges, including data privacy and security concerns, potential biases in algorithms, and data quality and integration issues. The paper concludes by emphasizing the need for interdisciplinary collaborations and the development of user-friendly tools and platforms to democratize the adoption of AI and Big Data applications in geography.

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Ganesan, Madhubala, Ah-Lian Kor, Colin Pattinson, and Eric Rondeau. "Green Cloud Software Engineering for Big Data Processing." Sustainability 12, no. 21 (November 7, 2020): 9255. http://dx.doi.org/10.3390/su12219255.

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Internet of Things (IoT) coupled with big data analytics is emerging as the core of smart and sustainable systems which bolsters economic, environmental and social sustainability. Cloud-based data centers provide high performance computing power to analyze voluminous IoT data to provide invaluable insights to support decision making. However, multifarious servers in data centers appear to be the black hole of superfluous energy consumption that contributes to 23% of the global carbon dioxide (CO2) emissions in ICT (Information and Communication Technology) industry. IoT-related energy research focuses on low-power sensors and enhanced machine-to-machine communication performance. To date, cloud-based data centers still face energy–related challenges which are detrimental to the environment. Virtual machine (VM) consolidation is a well-known approach to affect energy-efficient cloud infrastructures. Although several research works demonstrate positive results for VM consolidation in simulated environments, there is a gap for investigations on real, physical cloud infrastructure for big data workloads. This research work addresses the gap of conducting real physical cloud infrastructure-based experiments. The primary goal of setting up a real physical cloud infrastructure is for the evaluation of dynamic VM consolidation approaches which include integrated algorithms from existing relevant research. An open source VM consolidation framework, Openstack NEAT is adopted and experiments are conducted on a Multi-node Openstack Cloud with Apache Spark as the big data platform. Open sourced Openstack has been deployed because it enables rapid innovation, and boosts scalability as well as resource utilization. Additionally, this research work investigates the performance based on service level agreement (SLA) metrics and energy usage of compute hosts. Relevant results concerning the best performing combination of algorithms are presented and discussed.

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Barik, Rabindra K., Rojalina Priyadarshini, Rakesh K. Lenka, Harishchandra Dubey, and Kunal Mankodiya. "Fog Computing Architecture for Scalable Processing of Geospatial Big Data." International Journal of Applied Geospatial Research 11, no. 1 (January 2020): 1–20. http://dx.doi.org/10.4018/ijagr.2020010101.

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Geospatial data analysis using cloud computing platform is one of the promising areas for analysing, retrieving, and processing volumetric data. Fog computing paradigm assists cloud platform where fog devices try to increase the throughput and reduce latency at the edge of the client. In this research paper, the authors discuss two case studies on geospatial data analysis using Fog-assisted cloud computing namely, (1)Ganga River Basin Management System; and (2)Tourism Information Management of India. Both case studies evaluate proposed GeoFog architecture for efficient analysis and management of geospatial big data employing fog computing. The authors developed a prototype of GeoFog architecture using Intel Edison and Raspberry Pi devices. The authors implemented some of the open source compression methods for reducing the data transmission overload in the cloud. Proposed architecture performs data compression and overlay analysis of data. The authors further discussed the improvement in scalability and time analysis using proposed GeoFog architecture and Geospark tool. Discussed results show the merit of fog computing that holds an enormous promise for enhanced analysis of geospatial big data in river Ganga basin and tourism information management scenario.

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Shook, Eric, Michael E. Hodgson, Shaowen Wang, Babak Behzad, Kiumars Soltani, April Hiscox, and Jayakrishnan Ajayakumar. "Parallel cartographic modeling: a methodology for parallelizing spatial data processing." International Journal of Geographical Information Science 30, no. 12 (April 26, 2016): 2355–76. http://dx.doi.org/10.1080/13658816.2016.1172714.

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CAO, Ning, Ping ZHOU, Xia WANG, Xinming TANG, and Guoyuan LI. "Refined processing of laser altimeter data-aided satellite geometry model." National Remote Sensing Bulletin 22, no. 4 (2018): 599–610. http://dx.doi.org/10.11834/jrs.20187252.

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Shupeng, Chen. "Mathematic Analysis and Data Processing on Remote Sensing in China." National Remote Sensing Bulletin, no. 4 (1989): 311–17. http://dx.doi.org/10.11834/jrs.1989040.

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Hueni, A., and M. Tuohy. "Spectroradiometer data structuring, pre‐processing and analysis – an IT based approach." Journal of Spatial Science 51, no. 2 (December 2006): 93–102. http://dx.doi.org/10.1080/14498596.2006.9635084.

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Singhal, Mragank, Ashish Payal, and Anil Kumar. "Procreation of training data using cognitive science in temporal data processing for burnt paddy fields mapping." Remote Sensing Applications: Society and Environment 22 (April 2021): 100516. http://dx.doi.org/10.1016/j.rsase.2021.100516.

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Hidayah, Zainul, Haryo Dwito Armono, Maulinna Kusumo Wardhani, and Dwi Budi Wiyanto. "The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java." Geosfera Indonesia 7, no. 3 (December 24, 2022): 207. http://dx.doi.org/10.19184/geosi.v7i3.30797.

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Land cover dynamics in a small island can be determined using Geographic Information System (GIS) approach based on multitemporal image analysis. This study aimed to classify major land cover types and to map land cover changes of Bawean Island. Two sets of 10 meter resolution satellite data ALOS AVNIR (2010) and Sentinel-2A (2020) were used in this study. Satellite image analysis was carried out through several stages namely image pre-processing including radiometric and geometric correction, supervised image classification and accuracy test. Image classification results from 2010 to 2020 showed a significant change in land cover on Bawean Island. The forest vegetation land cover declined significantly from 13,470.5 Ha in 2010 to 8,543.4 Ha in 2020. Most of the area have been converted into paddy fields and built-up areas. The accuracy test and validation were determined by comparing the 2020 Sentinel image classification results with field observation conducted in 2021. The analysis showed good results with 82.52% overall accuracy and 79.66 Kappa coefficient. Further investigation found that changes in land cover on Bawean Island occured due to the agriculture and infrastucture development. Keywords : Geographic Information System (GIS); land cover; satellite images; small island Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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Calderón-Fajardo, Víctor, Miguel Puig-Cabrera, and Ignacio Rodríguez-Rodríguez. "Deciphering Tourism’s Role in Antarctica’s Geosocial Concerns through Data Mining Techniques." Land 13, no. 6 (June 13, 2024): 843. http://dx.doi.org/10.3390/land13060843.

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This study explores the changing dynamics of tourism in Antarctica, focusing on the impact of digitalisation and User-Generated Content on platforms like Tripadvisor. It aims to understand how online reviews influence perceptions and decisions to visit Antarctica, a region known for its pristine environment and status as ‘the last frontier’. Utilising Environmental Perception and Behaviour Geography (EPBG) principles, this research conducts a quantitative analysis of reviews from potential and current travellers. Through text mining, topic modelling, sentiment analysis, and Natural Language Processing (NLP), it investigates the emotional and perceptual discourse surrounding Antarctic tourism and its alignment with Agenda 2030 and Sustainable Development Goals. The findings reveal a detailed narrative of sustainability challenges and the emotional geography related to tourism in Antarctica, highlighting emotions such as happiness, anger, surprise, fear, disgust, and sadness among visitors. This study uncovers differences in perception based on visitors’ backgrounds, noting that individuals from nature-focused cities display strong environmental concerns, whereas those from advanced urban centres show a more positive attitude. This research contributes to the understanding of EPBG, text mining, and NLP, offering insights into sustainable tourism practices in Antarctica.

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Wu, Yue, Maoguo Gong, Qiguang Miao, and Kai Qin. "Computational Intelligence in Remote Sensing." Remote Sensing 15, no. 22 (November 12, 2023): 5325. http://dx.doi.org/10.3390/rs15225325.

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With the development of Earth observation techniques, vast amounts of remote sensing data with a high spectral–spatial–temporal resolution are captured all the time, and remote sensing data processing and analysis have been successfully used in numerous fields, including geography, environmental monitoring, land survey, disaster management, mineral exploration and more [...]

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Donaldson, Dave, and Adam Storeygard. "The View from Above: Applications of Satellite Data in Economics." Journal of Economic Perspectives 30, no. 4 (November 1, 2016): 171–98. http://dx.doi.org/10.1257/jep.30.4.171.

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The past decade or so has seen a dramatic change in the way that economists can learn by watching our planet from above. A revolution has taken place in remote sensing and allied fields such as computer science, engineering, and geography. Petabytes of satellite imagery have become publicly accessible at increasing resolution, many algorithms for extracting meaningful social science information from these images are now routine, and modern cloud-based processing power allows these algorithms to be run at global scale. This paper seeks to introduce economists to the science of remotely sensed data, and to give a flavor of how this new source of data has been used by economists so far and what might be done in the future.

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Morphet, C. S. "The Mapping of Small-Area Census Data—A Consideration of the Role of Enumeration District Boundaries." Environment and Planning A: Economy and Space 25, no. 9 (September 1993): 1267–77. http://dx.doi.org/10.1068/a251267.

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Census enumeration districts (EDs) are not ‘natural’ areal units, and a strong presumption exists against their use for cartographic or analytical purposes. There is, however, some reason to suppose that their boundaries may coincide with divisions in the underlying social geography of an area, and that they therefore contain information which should not be lost in processing. A study of Newcastle upon Tyne EDs shows that ED boundaries do not, in fact, mark the boundaries of distinct areas. The presumption against the use of ED boundaries for cartographic representation is reinforced.

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Munandar, Aris, Enok Maryani, Dede Rohmat, and Mamat Ruhimat. "Assessment on Geography Field study at Universities in Indonesia." Jurnal SPATIAL Wahana Komunikasi dan Informasi Geografi 19, no. 1 (October 3, 2019): 1–10. http://dx.doi.org/10.21009/spatial.191.01.

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In Geography Study Program, fieldstudy is the hallmark of geography outdoor learning. The similar activities of fieldstudy are fieldwork, fieldtrip, outing, excursion, cooks tours and others. The implementation of fieldstudy in the universities of teacher training has the similarity in its naming, its definition, its purpose, material of the study, the duration of the activity, the location of the fieldstudy, and data processing. The difference of the fieldstudy implementation lies on the ratio of supervisor to students, funding, outcome product and assessment. Universities that conduct the fieldstudy should review the curriculum in its implementation so that the credit, the assessed product and process have the similarity both in the credit and the supervisors who assess.

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Čtrnáct, Pavel. "Geographical Aspects at the Census Data Processing to Take Place in 1991." Geografie 95, no. 4 (1990): 308–12. http://dx.doi.org/10.37040/geografie1990095040308.

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The author informs the geographers of the changes in the contents of the census prepared for 1991 due to the social development in Czechoslovakia. The paper treats, before all, of regional aspects of the census and of the possibilities of application of its results in the geographical investigation.

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FEDІI, O., L. VISHNIKIN, and A. SHUKANOVA. "APPLICATION OF GEOGRAPHICAL INFORMATION SYSTEM IN THE TRAINING OF FUTURE GEOGRAPHY TEACHERS." ТHE SOURCES OF PEDAGOGICAL SKILLS, no. 29 (September 10, 2022): 236–40. http://dx.doi.org/10.33989/2075-146x.2022.29.264357.

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The most important condition for training specialists in modern higher education institutions is the possession of information systems and technologies. The article highlights the relevance of training future teachers of geography via using modern geographic information systems. Informatization of society ensures the future development of science, education, production, forms a reality. For future teachers of geography it is important to be able to apply modern methods of information processing, use databases to develop projects based on modern geographical information systems. The article analyzed the importance of using software in the educational process on the example of open GIS SAGA and QGIS, the use of resources of EO Browser, Giovanni, Google (GoogleEarth). The specifics of the work of students of geographical specialties is the ability to operate with data that have geo-referenced objects, their mutual location in the territory, consistency between many factors of territorial organization. The result of such activities is a developed geographical map or system project. They demonstrate the patterns of distribution of objects or processes in the territory. The article identifies competency-oriented approaches in teaching future geography teachers in an information-modernized educational space. Working with open GIS SAGA during the implementation of practical tasks allows you to form general and professional competencies, soft skills – the ability to act collectively and teamwork skills. The importance of geographic information systems makes it necessary to increase the number of hours in student curricula. The curriculum for the training of specialists is constantly being improved by making suggestions by students, teachers, and stakeholders.

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Shobha, C., T. Geeta Prasanna, K. Nirmala, K. Renuka Reddy, B. Lakshmi, K. J. Hebbar, M. Suryanarayana, M. V. V. Kamaraju, and A. Bhattacharya. "A package for digital processing and automatic contouring of aeromagnetic data." Journal of the Indian Society of Remote Sensing 22, no. 2 (June 1994): 93–102. http://dx.doi.org/10.1007/bf03023879.

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Jonna, S., K. V. S. Badarinath, and J. Saibaba. "Digital image processing of Remote Sensing data for water quality studies." Journal of the Indian Society of Remote Sensing 17, no. 2 (June 1989): 59–64. http://dx.doi.org/10.1007/bf02991911.

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