An information model to describe systems for spatially variable field operations
Identifieur interne : 000B50 ( Istex/Corpus ); précédent : 000B49; suivant : 000B51An information model to describe systems for spatially variable field operations
Auteurs : D. Goense ; J. W. Hofstee ; J. Van BergeijkSource :
- Computers and Electronics in Agriculture [ 0168-1699 ] ; 1996.
Abstract
Data in systems are usually described by information models. In precision agriculture, management data related to soils and crops only have meaning when they are also related to the position to which they apply. An information model is necessary to obtain a common level of understanding. This is a prerequisite for the successful application of electronics and information technology in agriculture; especially because agriculture is a multi-vendor environment, and hardware, software and firmware from different vendors have to work together. The paper describes four different methods (lane table, raster table, pattern table, and polygon table) that can be used to tabulate data for geographical objects. Further, an analysis is made of the different types of data that are or can be used in systems that handle location-specific data. The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work. An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. The entity types are specified in an appendix.
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DOI: 10.1016/0168-1699(95)00048-8
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Van Bergeijk</name><affiliation><mods:affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:C17CCFC21560FB5AF4CB6C5268260056D925BBA8</idno><date when="1996" year="1996">1996</date><idno type="doi">10.1016/0168-1699(95)00048-8</idno><idno type="url">https://api.istex.fr/document/C17CCFC21560FB5AF4CB6C5268260056D925BBA8/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000B50</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000B50</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">An information model to describe systems for spatially variable field operations</title><author><name sortKey="Goense, D" sort="Goense, D" uniqKey="Goense D" first="D." last="Goense">D. Goense</name><affiliation><mods:affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</mods:affiliation></affiliation></author><author><name sortKey="Hofstee, J W" sort="Hofstee, J W" uniqKey="Hofstee J" first="J. W." last="Hofstee">J. W. Hofstee</name><affiliation><mods:affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</mods:affiliation></affiliation></author><author><name sortKey="Van Bergeijk, J" sort="Van Bergeijk, J" uniqKey="Van Bergeijk J" first="J." last="Van Bergeijk">J. Van Bergeijk</name><affiliation><mods:affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Computers and Electronics in Agriculture</title><title level="j" type="abbrev">COMPAG</title><idno type="ISSN">0168-1699</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1996">1996</date><biblScope unit="volume">14</biblScope><biblScope unit="issue">2–3</biblScope><biblScope unit="page" from="197">197</biblScope><biblScope unit="page" to="214">214</biblScope></imprint><idno type="ISSN">0168-1699</idno></series><idno type="istex">C17CCFC21560FB5AF4CB6C5268260056D925BBA8</idno><idno type="DOI">10.1016/0168-1699(95)00048-8</idno><idno type="PII">0168-1699(95)00048-8</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0168-1699</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Data in systems are usually described by information models. In precision agriculture, management data related to soils and crops only have meaning when they are also related to the position to which they apply. An information model is necessary to obtain a common level of understanding. This is a prerequisite for the successful application of electronics and information technology in agriculture; especially because agriculture is a multi-vendor environment, and hardware, software and firmware from different vendors have to work together. The paper describes four different methods (lane table, raster table, pattern table, and polygon table) that can be used to tabulate data for geographical objects. Further, an analysis is made of the different types of data that are or can be used in systems that handle location-specific data. The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work. An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. The entity types are specified in an appendix.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>D. Goense</name><affiliations><json:string>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</json:string></affiliations></json:item><json:item><name>J.W. 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The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work. An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. 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In precision agriculture, management data related to soils and crops only have meaning when they are also related to the position to which they apply. An information model is necessary to obtain a common level of understanding. This is a prerequisite for the successful application of electronics and information technology in agriculture; especially because agriculture is a multi-vendor environment, and hardware, software and firmware from different vendors have to work together. The paper describes four different methods (lane table, raster table, pattern table, and polygon table) that can be used to tabulate data for geographical objects. Further, an analysis is made of the different types of data that are or can be used in systems that handle location-specific data. The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work. An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. 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In precision agriculture, management data related to soils and crops only have meaning when they are also related to the position to which they apply. An information model is necessary to obtain a common level of understanding. This is a prerequisite for the successful application of electronics and information technology in agriculture; especially because agriculture is a multi-vendor environment, and hardware, software and firmware from different vendors have to work together.</ce:simple-para><ce:simple-para>The paper describes four different methods (lane table, raster table, pattern table, and polygon table) that can be used to tabulate data for geographical objects. Further, an analysis is made of the different types of data that are or can be used in systems that handle location-specific data. The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work.</ce:simple-para><ce:simple-para>An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. The entity types are specified in an appendix.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Geographic Information System</ce:text></ce:keyword><ce:keyword><ce:text>Information model</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>An information model to describe systems for spatially variable field operations</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>An information model to describe systems for spatially variable field operations</title></titleInfo><name type="personal"><namePart type="given">D.</namePart><namePart type="family">Goense</namePart><affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</affiliation><description>Corresponding author.</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">J.W.</namePart><namePart type="family">Hofstee</namePart><affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">van Bergeijk</namePart><affiliation>Wageningen Agricultural University, Department of Agricultural Engineering and Physics, Agrotechnion, Bomenweg 4, 6703 HD Wageningen, Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">1996</dateIssued><copyrightDate encoding="w3cdtf">1996</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Data in systems are usually described by information models. In precision agriculture, management data related to soils and crops only have meaning when they are also related to the position to which they apply. An information model is necessary to obtain a common level of understanding. This is a prerequisite for the successful application of electronics and information technology in agriculture; especially because agriculture is a multi-vendor environment, and hardware, software and firmware from different vendors have to work together. The paper describes four different methods (lane table, raster table, pattern table, and polygon table) that can be used to tabulate data for geographical objects. Further, an analysis is made of the different types of data that are or can be used in systems that handle location-specific data. The different types of data can be: data related to an operation (execution of work), with a distinction between product-/produce-dependent and -independent data, data related to a crop production unit, and data collected during the execution of work. An Entity Relationship Diagram (ERD) that represents the different objects and the relations between them is presented. This ERD shows the relations between the different geographical objects, the methods for tabulating the data, and the different types of data itself. The entity types are specified in an appendix.</abstract><subject><genre>Keywords</genre><topic>Geographic Information System</topic><topic>Information model</topic></subject><relatedItem type="host"><titleInfo><title>Computers and Electronics in Agriculture</title></titleInfo><titleInfo type="abbreviated"><title>COMPAG</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">199602</dateIssued></originInfo><identifier type="ISSN">0168-1699</identifier><identifier type="PII">S0168-1699(00)X0004-X</identifier><part><date>199602</date><detail type="issue"><title>Spatially Variable Field Operations</title></detail><detail type="volume"><number>14</number><caption>vol.</caption></detail><detail type="issue"><number>2–3</number><caption>no.</caption></detail><extent unit="issue pages"><start>99</start><end>253</end></extent><extent unit="pages"><start>197</start><end>214</end></extent></part></relatedItem><identifier type="istex">C17CCFC21560FB5AF4CB6C5268260056D925BBA8</identifier><identifier type="DOI">10.1016/0168-1699(95)00048-8</identifier><identifier type="PII">0168-1699(95)00048-8</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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