Academic literature on the topic 'Meteorology, Agricultural – Data processing'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Meteorology, Agricultural – Data processing.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Meteorology, Agricultural – Data processing"
Kataev, M. Yu, M. O. Krylov, and P. P. Geiko. "Software to compare images of the vegetation index obtained by satellite devices and unmanned aircraft." Proceedings of Tomsk State University of Control Systems and Radioelectronics 23, no. 4 (December 25, 2020): 63–70. http://dx.doi.org/10.21293/1818-0442-2020-23-4-63-70.
Full textPolukoshko, Svetlana, and Janis Hofmanis. "USE OF “CATERPILLAR” – SSA METHOD FOR ANALYSIS AND FORECASTING OF INDUSTRIAL AND ECONOMIC INDICATORS." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (August 3, 2015): 241. http://dx.doi.org/10.17770/etr2009vol2.1030.
Full textPeng, Li, Fei Fei Tang, Zhi Yue Zhou, Xing Liu, and Zhi Min Ruan. "Applying Lightweight UAV in Landslide Monitoring." Applied Mechanics and Materials 738-739 (March 2015): 738–45. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.738.
Full textWebb, Mathew, and Budiman Minasny. "A digital mapping application for quantifying and displaying air temperatures at high spatiotemporal resolutions in near real-time across Australia." PeerJ 8 (October 7, 2020): e10106. http://dx.doi.org/10.7717/peerj.10106.
Full textSeguin, B., D. Courault, and M. Guérif. "Satellite thermal infrared data applications in agricultural meteorology." Advances in Space Research 13, no. 5 (May 1993): 207–17. http://dx.doi.org/10.1016/0273-1177(93)90547-o.
Full textFoster, James, Michael Bevis, and Steven Businger. "GPS Meteorology: Sliding-Window Analysis*." Journal of Atmospheric and Oceanic Technology 22, no. 6 (June 1, 2005): 687–95. http://dx.doi.org/10.1175/jtech1717.1.
Full textNovak, V. G., and À. V. Novak. "AGRICULTURAL METEOROLOGY TERMS 2017–2018 AGRICULTURAL YEAR FROM DATA OF WEATHERSTATION UMAN." Bulletin of Uman National University of Horticulture, no. 2 (2018): 73–75. http://dx.doi.org/10.31395/2310-0478-2018-21-73-75.
Full textAfanasyev, V. S., and S. A. Kiselev. "Modern methods of processing and visualization of meteorological data." Quality. Innovation. Education, no. 4 (2020): 61–66. http://dx.doi.org/10.31145/1999-513x-2020-4-61-66.
Full textHORIGUCHI, Ikuo, Hiroshi TANI, and Shunji MORIKAWA. "Applications of Satellite Data to the Studies of Agricultural Meteorology." Journal of Agricultural Meteorology 40, no. 4 (1985): 379–85. http://dx.doi.org/10.2480/agrmet.40.379.
Full textHORIGUCHI, Ikuo, Hiroshi TANI, and Toshihiro MOTOKI. "Applications of Satellite Data to the Studies of Agricultural Meteorology." Journal of Agricultural Meteorology 42, no. 2 (1986): 129–35. http://dx.doi.org/10.2480/agrmet.42.129.
Full textDissertations / Theses on the topic "Meteorology, Agricultural – Data processing"
Roman, Diego. "Modelagem computacional de dados: um sistema de tomada de decisão para gestão de recursos agrometeorológicos - SIAGRO." Universidade do Estado do Rio de Janeiro, 2007. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=764.
Full textSince most of the applications involving the influence of climate in agriculture require a great amount of data that usually are unavailable, a computational tool is needed to help to organize the necessary data. The computational system SIAGRO was developed in an attempt to support such a demand of users of climate information in agriculture. The system makes it possible to register other stations, import climatic data, to calculate evapotranspiration by means of different methods (Thornthwaite; Camargo; Thornthwaite modified by Camargo and Hagreaves e Samani), to apply a climatic classification and to determine averages for different periods of time from daily data. The system presents its results in graphics and tables, which can be copied for use in other computer applications or used to be compared with results of other weather stations registered in this system. To supply SIAGRO with profitable information for irrigation scheduling and increase the efficiency in water use by crops, allowed the evaluation of three reference methods to estimating evapotranspiration through correlation with data obtained in constant water table lisimeter. The data were collected daily and processed in a monthly basis. The performance evaluations of the methods were based on the correlation coefficient r and Willmott agreement coefficient d. The results showed that the best estimate was obtained with the Thornthwaite modified by Camargo model, which shows the best adjustment to lysimeter data, with the index d equal to 0.91.
Wong, Ka-yan, and 王嘉欣. "Positioning patterns from multidimensional data and its applications in meteorology." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B39558630.
Full textFernando, Dweepika Achela Kumarihamy. "On the application of artificial neural networks and genetic algorithms in hydro-meteorological modelling." Thesis, Hong Kong : University of Hong Kong, 1997. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18618546.
Full textMugadza, Precious. "An assessment of the usefulness of spatial agricultural land resource digital data for agritourism and ecotourism." Thesis, Link to the online version, 2005. http://hdl.handle.net/10019/1125.
Full textIruria, Daniel Muriuki. "An information systems study on the generation, communication, and utilisation of information on agricultural technology and innovations for small-scale farmers in Kenya." Thesis, University of Strathclyde, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299078.
Full textBottomley, Laura Jones. "The application of IBM PC's and distrometers in a satellite propagation experiment." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/90919.
Full textM.S.
Kintoki, Alain Nzuzi. "The e-agriculture research landscape in South Africa : a systematic literature review." Thesis, Cape Peninsula University of Technology, 2017. http://hdl.handle.net/20.500.11838/2586.
Full textThe objective of this study was to determine the current status of e-agriculture research in the South African context. A systematic literature review was used to gather and analyse data in alignment with the objective of the study. The researcher used keywords and combined search keywords on web search engines and digital databases to obtain pertinent research papers. The scope of the study was limited to the period 2000-2016. The books, theses, conference papers and journal articles identified as pertinent to conduct the study, amounted to 114 in number. The analysis of the study described the focus of research papers, research methods, research approaches, theoretical lenses, units of analysis and observation, levels of analysis, historical development, and major concepts and disciplines used by authors in their studies. The study also sought to discover the year of publication and assessment of searchability of the papers. The results indicate that 13 papers (11.4%) were published in the first five years (2000- 2004) and 51 papers (44.7%) in the last five years (2012-2016) of the delimited period for the study. The results of the study further indicate that the application of geographic information systems (GISs) towards improving agriculture was the most prominent eagriculture research area in South Africa (27 papers, 23.6%), followed by the use of satellite enhancing agriculture (26 papers, 22.8%). E-government direct services, mobile in agriculture, and agricultural information systems were the least prominent e-agriculture research areas in South Africa with a contribution of two papers (1.8%) each. The results of this study show that information mapping was the most used research method by researchers in their studies (57 papers, 50%), followed by the case study method with 31 papers (27.1%). The results further denote that the least used research method was industry reports with no mention of it in any of the pertinent papers, followed by grounded theory with two papers (1.7%). Interpretivism was the most used research approach by researchers (six papers, 5.2%) during the period 2000-2016. The findings of this study clearly show that researchers still need to address certain issues or problems regarding e-agriculture in South Africa in order to improve the agricultural sector. The contribution of the study is to understand the importance of enhancing research capability and socio-economic transformation of farmworkers and farmers through enhanced communication of agriculture research knowledge in the area of agricultural informatics. A foundation for further studies was created for continuous e-agriculture research in South Africa.
Schreiber, Werner. "GIS and EUREPGAP : applying GIS to increase effective farm management in accordance GAP requirements." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53440.
Full textENGLISH ABSTRACT: With the inception of precision farming techniques during the last decade, agricultural efficiency has improved, leading to greater productivity and enhanced economic benefits associated with agriculture. The awareness of health risks associated with food borne diseases has also increased. Systems such as Hazard Analysis and Critical Control Points (RACCP) in the USA and Good Agricultural Practices (GAP) in Europe are trying to ensure that no food showing signs of microbial contamination associated with production techniques are allowed onto the export market. Growers participating in exporting are thus being forced to conform to the requirements set by international customers. The aim of this study was to compile a computerized record keeping system that would aid farmers with the implementation of GAP on farms, by making use of GIS capabilities. A database, consisting of GAP-specific data was developed. ArcView GIS was used to implement the database, while customized analyses procedures through the use of Avenue assisted in GAP-specific farming related decisions. An agricultural area focusing on the export market was needed for this study, and the nut producing Levubu district was identified as ideal. By making use of ArcView GIS, distinct relationships between different data sets were portrayed in tabular, graphical, geographical and report format. GAP requirements state that growers must base decisions on timely, relevant information. With information available in the above-mentioned formats, decisions regarding actions taken can be justified. By analysing the complex interaction between datasets, the influences that agronomical inputs have on production were portrayed, moving beyond the standard requirements of GAP. Agricultural activities produce enormous quantities of data, and GIS proved to be an indispensable tool because of the ability to analyse and manipulate data with a spatial component. The implementation of good agricultural practices lends itself to the use of GIS. With the correct information available at the right time, better decisions can promote optimal croppmg, whilst rmmrrnzmg the negative effects on the consumer and environment.
AFRIKAANSE OPSOMMING: Gedurende die afgelope dekade het die gebruik van presisie boerderytegnieke tot verbeterde gewasverbouing gelei, wat verhoogde produktiwiteit en ekonomiese welvarendheid tot gevolg gehad het. 'n Wêreldwye bewustheid ten opsigte van die oordrag van siektekieme geasosieer met varsprodukte het ontstaan. Met die implementering van Hazard Analysis and Critical Control Points (HACCP) en Good Agricultural Practices (GAP), poog die VSA en Europa om voedsel wat tekens van besmetting toon van die invoermark te weerhou. Buitelandse produsente en uitvoerders word dus hierdeur gedwing om by internasionale voedselstandaarde aan te pas. Hierdie navorsing het ten doel gehad om 'n gerekenariseerde rekordhouding stelsel daar te stel wat produsente sal bystaan tydens die implementering van GAP, deur gebruik te maak van GIS. 'n Databasis gerig op die implementering van GAP is ontwerp. ArcView GIS is gebruik word om die databasis te implementeer, waarna spesifieke navrae die data ontleed het om sodoende die besluitnemingsproses te vergemaklik. 'n Landbou-area wat aktief in die uitvoermark deelneem was benodig vir dié studie, en die Levubu distrik was ideaal. Verwantskappe tussen datastelle is bepaal en uitgebeeld in tabel-, grafiek- en verslag vorm. Die suksesvolle implementering van GAP vereis dat alle besluite op relevante inligting gebaseer word, en met inligting beskikbaar in die bogenoemde formaat kan alle besluite geregverdig word. Deur die komplekse interaksie tussen insette en produksie te analiseer, was dit moontlik om verwantskappe uit te beeld wat verder strek as wat GAP vereistes stipuleer. Deur die gebruikerskoppelvlak in ArcView te verpersoonlik is die gebruiker nie belaai met onnodige berekeninge nie. Aktiwiteite soos landbou produseer groot datastelle, en die vermoë van GIS om die ruimtelike verwantskappe te analiseer en uit te beeld, het getoon dat GIS 'n instrumentele rol in die besluitnemingsproses speel. Deur middel van beter besluitneming kan optimale gewasverbouing verseker word, terwyl die negatiewe impak op die verbruiker en omgewing tot 'n minimum beperk word.
Brilhador, Anderson. "Análise semi-automática do arranjo espacial de plantas de milho utilizando visão computacional." Universidade Tecnológica Federal do Paraná, 2015. http://repositorio.utfpr.edu.br/jspui/handle/1/2954.
Full textGlobal demand for food is growing every year, requiring the development of new technologies that increase grain production without increasing the areas destined for planting. The corn crop is a major commodity in the world and is used as food, feed for other animals, in addition to having other industrial purposes. Corn is sensitive to the spatial arrangement of plants and any variation in distribution pattern can lead to reduction in the production of corn. Currently, the process of checking the uniformity of spacing between plants is done manually by agronomists and producers in order to predict possible production losses. In this context, this paper proposes an automatic approach to the analysis of the spatial arrangement of plants by measuring the spacing between corn plants in early stages of growth. From this measurement are extracted relevant information such as population density, uniformity of planting and loss estimates. The proposed approach uses computer vision techniques of low computational cost to identify corn plants and measure the spacing between plants, allowing its use in devices with low computational power such as smartphones and tablets. A set of images was built as an additional contribution of work, containing 222 panoramic images of corn planting in three conditions of planting: direct, conventional and direct after applying herbicides. The experimental results achieve 90% of rate accuracy and 87% sensitivity in identification of corn plants present on the base. A comparison of the measurements of the distances between plants made of manual and computer vision way, no presented significant differences between the measurements, indicating the effectiveness of the proposed approach at work.
Ramalingam, Nagarajan. "Non-contact multispectral and thermal sensing techniques for detecting leaf surface wetness." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1104392582.
Full textTitle from first page of PDF file. Document formatted into pages; contains xxii, 271 p.; also includes graphics (some col.) Includes bibliographical references (p. 206-214).
Books on the topic "Meteorology, Agricultural – Data processing"
Nong ye zhong da qi xiang zai hai zong he fu wu xi tong kai fa ji shu yan jiu. Beijing Shi: Qi xiang chu ban she, 2009.
Find full textBates, Earl M. Climatological data for Oregon agricultural regions. Corvallis, Or: Agricultural Experiment Station, Oregon State University, 1993.
Find full textKasimona, V. N. Final report on the use of meteorological & hydrological data in recession agriculture in the Gwembe-Valley study. [Lusaka: s.n., 1997.
Find full textWallbrink, Hendrik. The US Maury collection metadata 1796-1861. De Bilt, Netherlands: Koninklijk Nederlands Meteorologisch Instituut, 2009.
Find full textTokyo, Japan) Meeting on Asia-Pacific Satellite Data Utilization and Exchange (1999. Proceedings of Meeting on Asia-Pacific Satellite Data Utilization and Exchange,Tokyo, Japan, 2-4 February 1999. Tokyo]: Japan Meteorological Agency, 1999.
Find full textWallbrink, Hendrik. The US Maury collection metadata 1796-1861. De Bilt, Netherlands: Koninklijk Nederlands Meteorologisch Instituut, 2009.
Find full textECMWF Workshop on the Use of High Performance Computing in Meteorology (9th 2000 Reading, England). Developments in teracomputing: Proceedings of the Ninth ECMWF Workshop on the Use of High Performance Computing in Meteorology : Reading, UK, November 13-17, 2000. Edited by Zwieflhofer Walter, Kreitz Norbert, and European Centre for Medium Range Weather Forecasts. River Edge, NJ: World Scientific, 2001.
Find full textEberhard, Wynn. Improvements in profiler wind estimates using smoothed data in the spectrum finder algorithm. Boulder, Colo: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, 1987.
Find full textWalter, Zwieflhofer, Kreitz Norbert, and European Centre for Medium Range Weather Forecasts., eds. Developments in teracomputing: Proceedings of the ninth ECMWF Workshop on the Use of High Performance Computing in Meteorology. Singapore: World Scientific, 2001.
Find full textECMWF Workshop on the Use of High Performance Computing in Meteorology (10th 2002 Reading, England). Realizing teracomputing: Proceedings of the tenth ECMWF Workshop on the Use of High Performance Computing in Meteorology : Reading, UK, 4-8 November, 2002. Edited by Zwieflhofer Walter, Kreitz Norbert, and European Centre for Medium Range Weather Forecasts. River Edge, NJ: World Scientific, 2003.
Find full textBook chapters on the topic "Meteorology, Agricultural – Data processing"
Şen, Zekâi. "Meteorology." In Earth Systems Data Processing and Visualization Using MATLAB, 7–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01542-8_2.
Full textYao, Shujie. "Data Processing." In Agricultural Reforms and Grain Production in China, 247–71. London: Palgrave Macmillan UK, 1994. http://dx.doi.org/10.1007/978-1-349-23553-7_10.
Full textJohnsson, S. Lennart. "Data Parallel Supercomputing." In The Dawn of Massively Parallel Processing in Meteorology, 231–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-84020-3_15.
Full textBateman, D. A., and A. Haskell. "Plans for ERS-1 Data Acquisition, Processing and Distribution." In Remote Sensing Applications in Meteorology and Climatology, 425–39. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3881-6_23.
Full textHussein, Eslam, Ronewa Sadiki, Yahlieel Jafta, Muhammad Mujahid Sungay, Olasupo Ajayi, and Antoine Bagula. "Big Data Processing Using Hadoop and Spark: The Case of Meteorology Data." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 180–85. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41593-8_13.
Full textSahu, Pradip Kumar. "Processing and Analysis of Data." In Research Methodology: A Guide for Researchers In Agricultural Science, Social Science and Other Related Fields, 75–130. India: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1020-7_8.
Full textJiang, Shufan, Rafael Angarita, Raja Chiky, Stéphane Cormier, and Francis Rousseaux. "Towards the Integration of Agricultural Data from Heterogeneous Sources: Perspectives for the French Agricultural Context Using Semantic Technologies." In Lecture Notes in Business Information Processing, 89–94. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49165-9_8.
Full textTheodorou, A., K. Nicolaides, and F. Tymvios. "Information System Regarding the Management and Processing of Data Base Software for Applications in Cases of Remote Sensing." In Advances in Meteorology, Climatology and Atmospheric Physics, 751–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29172-2_106.
Full textRapaka, Anuj, and Arulmurugan Ramu. "Multispectral Data Processing for Agricultural Applications Using Deep Learning Classification Methods." In EAI/Springer Innovations in Communication and Computing, 63–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47560-4_6.
Full textMeng, Yue, and Wenkuan Chen. "Dynamic Information Management System of Agricultural Economy Based on WebGIS." In Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019), 1715–21. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1468-5_204.
Full textConference papers on the topic "Meteorology, Agricultural – Data processing"
Ni, Guo, Wang Wei, Wang Xiaoping, Hu Die, Sha Sha, and Wang Lijuan. "Agricultural Drought Remote Sensing Monitoring and Analysis Platform in Northwest China Base on FY-3 Data." In 2019 International Conference on Meteorology Observations (ICMO). IEEE, 2019. http://dx.doi.org/10.1109/icmo49322.2019.9025995.
Full textArchibald, E. J. "Application oriented design of hydrological radar data processing systems." In IEE Colloquium on Radar Meteorology. IEE, 1995. http://dx.doi.org/10.1049/ic:19950196.
Full textJi, Xunsheng, Simeng He, and Qibing Zhu. "Agricultural greenhouse data processing based on Kalman filter." In 2018 Detroit, Michigan July 29 - August 1, 2018. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2018. http://dx.doi.org/10.13031/aim.201800471.
Full textLi, Yinan, Fuquan Zhang, Yifan Zhu, Sifan Zhang, Yu Mao, and Zhendong Niu. "Chinese Lexical Based Sentiment Analysis Framework in Meteorology." In 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). IEEE, 2019. http://dx.doi.org/10.1109/ispa-bdcloud-sustaincom-socialcom48970.2019.00244.
Full textMekruksavanich, Sakorn, and Thitirath Cheosuwan. "Visual Big Data Analytics for Sustainable Agricultural Development." In 2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE, 2018. http://dx.doi.org/10.1109/isai-nlp.2018.8692910.
Full textNtouros, K. D., I. Z. Gitas, and G. N. Silleos. "Mapping agricultural crops with EO-1 Hyperion data." In 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2009. http://dx.doi.org/10.1109/whispers.2009.5289057.
Full textJeff C Askey, Matthew Darr, Keith Webster, Benjamin Covington, and Jeremy Brue. "Automated Logistics Processing of GIS Data for Agricultural Harvest Equipment." In 2013 Kansas City, Missouri, July 21 - July 24, 2013. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2013. http://dx.doi.org/10.13031/aim.20131596410.
Full textDeepa, R., and S. Vigneshwari. "An Efficient DS-LSTMM Ontology for Paddy - Agricultural Data Processing." In 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV). IEEE, 2021. http://dx.doi.org/10.1109/icicv50876.2021.9388636.
Full textS, Navya, Khateeja Ambareen, and S. Meenakshi Sundaram. "A Survey on Agricultural Application based on Android." In 3rd National Conference on Image Processing, Computing, Communication, Networking and Data Analytics. AIJR Publisher, 2018. http://dx.doi.org/10.21467/proceedings.1.35.
Full textHruška, Jonáš, Telmo Adão, Luís Pádua, Pedro Marques, António Cunha, Emanuel Peres, António Sousa, Raul Morais, and Joaquim J. Sousa. "Machine learning classification methods in hyperspectral data processing for agricultural applications." In ICGDA '18: 2018 the International Conference on Geoinformatics and Data Analysis, ICGDA '18. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3220228.3220242.
Full text