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Geographic Information Systems in Agriculture

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Springer Handbook of Geographic Information

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Abstract

Since the beginning of the 1990s, modern agriculture and farming has changed dramatically. Agriculture has become a high-tech industry. With the possibility of locating agricultural machinery in the field using satellite positioning technologies (Global Navigation Satellite Systems, GNSS) and the increasing availability of geographic information in digital form and in increasing quality, farmers are now able to measure the spatial and temporal variability in soil, vegetation, relief, etc., within a field and to modify their operations to react to this. Farmers keep electronic field records and farm diaries, which they are able to use on site with mobile electronic devices in order to enter or retrieve information. Agricultural machinery is also being continuously developed, since due to the in-field heterogeneity many different operations (from yield mapping to plant protection) are performed on site and logged so that they may be later evaluated by computer. Due to legal regulations (IACS, cross compliance, traceability, quality management, etc.), GIS (and GeoWeb services) and information-driven crop production are becoming common tools in agriculture, which must be integrated into usual farm practices.

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References

  • Pierce, F.J., Clay, D. (eds.): GIS Applications in Agriculture. CRC, Boca Raton, p. 224 (2007)

    Google Scholar 

  • Steinberger, G., Rothmund, M., Auernhammer, H.: Mobile farm equipment as a data source in an agricultural service architecture. Comput. Electron. Agric. 65(2), 238–246 (2009)

    Article  Google Scholar 

  • van Diepen, F., Charvat, K., Dittmann, C., Jezek, J., Martini, D., Wagner, R.: AgriXchange – European data exchange in agriculture. In: Proc. Workshop LPIS Appl. Qual., Sofia. EC Joint Research Centre, Ispra (2008)

    Google Scholar 

  • Fountas, S., Wulfsohn, D., Blackmore, B.S., Jacobsen, H.L., Pedersen, S.M.: A model of decision-making and information flows for information-intensive agriculture. Agric. Syst. 87(2), 192–210 (2006)

    Article  Google Scholar 

  • Nash, E., Korduan, P., Bill, R.: Applications of open geospatial web services in precision agriculture: A review. Precis. Agric. 10(6), 546–560 (2009)

    Article  Google Scholar 

  • Bill, R.: Interoperable GIS-Infrastruktur im landwirtschaftlichen Betrieb. In: Dachverband wissenschaftlicher Gesellschaften der Agrar-, Forst-, Ernährungs-, Veterinär- und Umweltforschung (ed.) Geographische Informationssysteme in der Landwirtschaft und im ländlichen Raum. DAF, KTBL, Darmstadt (2004)

    Google Scholar 

  • Hufnagel, J., Herbst, R., Jarfe, A., Werner, A.: Precision Farming – Analyse, Planung, Umsetzung in der Praxis. KTBL Schrift, vol. 419. Landwirtschaftsverlag, Müster (2004)

    Google Scholar 

  • Mulla, D.J.: Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosyst. Eng. 114, 358–371 (2013)

    Article  Google Scholar 

  • Henault, F., Brouant, B.: Accuracy of 10 guidance systems for farming under the same conditions at the same time. In: Proc. 2005 EFITA/WCCA Jt. Congr. IT Agric. pp. 687–694. EFITA, Vila Real (2005)

    Google Scholar 

  • Grenzdörffer, G., Donath, C.: Generation and analysis of digital terrain models with parallel guidance systems for precision agriculture. In: Proc. 1st Int. Conf. Mach. Control Guid. pp. 141–150. ETH, Zürich (2008)

    Google Scholar 

  • Peets, S., Mouazen, A.M., Blackburn, K., Kuang, B., Wiebensohn, J.: Methods and procedures for automatic collection and management of data acquired from on-the-go sensors with application to on-the-go soil sensors. Comput. Electron. Agric. 81(0), 104–112 (2012). https://doi.org/10.1016/j.compag.2011.11.011

    Article  Google Scholar 

  • Kay, S., Milenov, P.: Status of the Implementation of LPIS in the EU Member States. EC Joint Research Centre, Ispra (2008)

    Google Scholar 

  • Léo, O., Lemoine, G.: Land Parcel Identification Systems in the Frame of Regulation (EC) 1593/2000, Version 1.4. EC Joint Research Centre, Ispra (2001)

    Google Scholar 

  • Werner, A., Jarfe, A.: Precision Agriculture. Herausforderung an Integrative Forschung, Entwicklung und Anwendung in der Praxis. KTBL Sonderveröff., vol. 038. Landwirtschaftsverlag, Münster (2002)

    Google Scholar 

  • Gebbers, R., Adamchuk, V.I.: Precision agriculture and food security. Science 327(5967), 828–831 (2010). https://doi.org/10.1126/science.1183899

    Article  Google Scholar 

  • Huhtala, A., Suhonen, K., Mäkelä, P., Hakojärvi, M., Ahokas, J.: Evaluation of instrumentation for cow positioning and tracking indoors. Biosyst. Eng. 96(3), 399–405 (2007)

    Article  Google Scholar 

  • Ipema, A.H., Bleumer, E.J.B., Hogewerf, P.H., Lokhurst, C., de Mol, R.M., Janssen, H., van der Wal, T.: Recording tracking behavior of dairy cows with wireless technologies. In: Precision Livestock Farming ’09 – Proc. 4th Eur. Conf. Precis. Livest. Farming, Wageningen, pp. 135–142. Wageningen Academic, Wageningen (2009)

    Google Scholar 

  • Bishop-Hurley, G.J., Swain, D.L., Anderson, D.M., Sikka, P., Crossman, C., Corke, P.: Virtual fencing applications: Implementing and testing an automated cattle control system. Comput. Electron. Agric. 56(1), 14–22 (2007)

    Article  Google Scholar 

  • Resnik, B., Bill, R.: Vermessungskunde für den Planungs-, Bau- und Umweltbereich. Wichmann, Heidelberg, p. 380 (2018)

    Google Scholar 

  • Bill, R.: Grundlagen der Geo-Informationssysteme. Wichmann, Heidelberg (2016)

    Google Scholar 

  • Fountas, M., Carli, G., Sorensen, C.G., Tsiropoulos, Z., Cavalaris, C., Vatsanidou, A., Liakos, B., Canavari, M., Wiebensohn, J., Tisserye, B.: Farm management information systems: Current situation and future perspectives. Comput. Electron. Agric. 115, 40–50 (2015). https://doi.org/10.1016/j.compag.2015.05.011

    Article  Google Scholar 

  • Korduan, P., Grenzdörffer, G., Bill, R.: Informationsmanagement und Informationsbeschaffung in der modernen Landwirtschaft. In: Conf. Dig. 2nd Wismarer Wirtschaftsinformatiktage, pp. 282–291. Fachhochschule Wismar, Wismar (2000)

    Google Scholar 

  • Corwin, D.L., Lesch, S.M.: Apparent soil electrical conductivity measurements in agriculture. Comput. Electron. Agric. 46(1–3), 11–43 (2005). https://doi.org/10.1016/j.compag.2004.10.005

    Article  Google Scholar 

  • Herbst, R.: Bodenschätzung, geoelektrische Sondierung und pedostatistische Modellierung als Basis von digitalen Hof-Bodenkarten im Präzisen Landbau. Schriftenreihe des Instituts für Pflanzenernährung und Bodenkunde, vol. 60. Univ. Kiel, Kiel (2002)

    Google Scholar 

  • Morellos, A., Pantazia, X.-E., Moshou, D., Alexandridis, T., Whetton, R., Tziotzios, G., Wiebensohn, J., Bill, R., Mouazen, A.M.: Machine learning based prediction of soil total nitrogen, organic carbon and moisture content by using VIS-NIR spectroscopy. Biosyst. Eng. 152, 104–116 (2016). https://doi.org/10.1016/j.biosystemseng.2016.04.018

    Article  Google Scholar 

  • Reichelt, M., Jürgens, C.: Adoption and future perspective of precision farming in Germany: Results of several survey among different agricultural target groups. Precis. Agric. 10(1), 73–94 (2009)

    Article  Google Scholar 

  • Lee, D.H., Sudduth, K.A., Drummond, S.T., Chung, S.O., Myers, D.B.: Automated yield map delay identification using phase correlation methodology. Trans. ASABE 55(3), 743–752 (2012)

    Article  Google Scholar 

  • Blackmore, S., Marshall, C.: Yield mapping: Errors and algorithms. In: Robert, P.C., Rust, R.M., Larsen, W.E. (eds.) Proc. 3rd Int. Conf. Precis. Agric. p. 403. ASA CSSA SSSA, Madison (1996)

    Google Scholar 

  • Blackmore, S., Godwin, R.J., Fountas, S.: The analysis of spatial and temporal trends in yield map data over six years. Biosyst. Eng. 84(4), 455–466 (2003)

    Article  Google Scholar 

  • Fountas, S., Ess, D.R., Sørensen, C.G., Hawkins, S.E., Pedersen, H.H., Blackmore, B.S., Lowenberg-Deboer, J.: Information sources in precision agriculture in Denmark and the USA. In: Stafford, J., Werner, A. (eds.) Proc. 4th Eur. Conf. Precis. Agric., Wageningen. Wageningen Academic, Wageningen (2003)

    Google Scholar 

  • Schmidt, F.: Hochgenaue Digitale Geländemodelle – Untersuchungen zur Erstellung, Analyse und Anwendung in der Landwirtschaft (2003). http://www.geoinformatik.uni-rostock.de/schriften/schriften_einzel.asp?DiplID=131

  • Nugteren, A., Robert, P.: Usefulness and feasibility of high accuracy digital elevation models for precision management. In: Stafford, J. (ed.) Precision Agriculture ’99 – Proc. 2nd Eur. Conf. Precis. Agric., Odense, pp. 561–569. Sheffield Academic, Sheffield (1999)

    Google Scholar 

  • Constantin, D., Rehak, M., Akhtman, Y., Liebisch, F.: Detection of crop properties by means of hyperspectral remote sensing from a micro UAV. Bornimer Agrartech. Ber. 88, 129–137 (2015)

    Google Scholar 

  • Grenzdörffer, G.: Crop height determination with UAS point clouds. Int. Arch. Photogramm. Remote. Sens. Spatial Inf. Sci. XL-1, 135–140 (2014). https://doi.org/10.5194/isprsarchives-XL-1-135-2014

    Article  Google Scholar 

  • Whelan, B., McBratney, A.: Definition and interpretation of potential management zones in Australia. In: Solutions for a Better Environment – Proc. 11th Aust. Agron. Conf. Australian Society of Agronomy, Geelong (2003)

    Google Scholar 

  • Watson, M., Lowenberg-DeBoer, J.: Who will benefit from GPS auto guidance in the corn belt? (2002). http://www.agriculture.purdue.edu/ssmc/Frames/WhoGPSAutoGuidanceCornBelt.htm

  • Niemann, H., Schwaiberger, R., Fröba, N.: Parallelfahrsysteme 67. KTBL, Darmstadt (2007). http://www.ktbl.de/

    Google Scholar 

  • Nash, E., Bill, R., Bobert, J.: Anwendungsfallanalyse für den Einsatz von GDI-Technologien in Precision Farming. GIS Z. Geoinformat. 11, 12–19 (2007)

    Google Scholar 

  • Fountas, S., Blackmore, S., Ess, D., Hawkins, S., Blumhoff, G., Lowenberg-Deboer, J., Sørensen, C.G.: Farmer experience with precision agriculture in Denmark and the US eastern corn belt. Precis. Agric. 6(2), 121–141 (2005)

    Article  Google Scholar 

  • McBratney, A., Whelan, B.: Future directions of precision agriculture. Precis. Agric. 6(1), 7–23 (2005)

    Article  Google Scholar 

  • Walter, A., Finger, R., Huber, R., Buchmann, N.: Smart farming is key to developing sustainable agriculture. Proc. Natl. Acad. Sci. U. S. A. 114(24), 6148–6150 (2017). https://doi.org/10.1073/pnas.1707462114

    Article  Google Scholar 

  • Charvat, K., Gnip, P.: Analysis of external drivers for farm management and their influences on farm management information systems. In: van Henten, E.J., Goense, D., Lokhorst, C. (eds.) Precision Agriculture ’09 – Proc. 7th Eur. Conf. Precis. Agric., Wageningen. Wageningen Academic, Wageningen (2009)

    Google Scholar 

  • Korduan, P., Nash, E.: Integration von ISO- und agroXML in GML, INFORMATIK 2005 Informatik LIVE! In: Cremers, A.B., Manthey, R., Martini, P., Steinhage, V. (eds.) Beiträge der 35. Jahrestagung der Gesellschaft für Informatik e.V. (GI) 2005, Bonn, pp. 375–379. (2005)

    Google Scholar 

  • OGC: GeoSPARQL – A geographic query language for RDF data (2011). http://www.opengeospatial.org/standards/geosparql

  • W3C: SPARQL 1.1 overview (2013). https://www.w3.org/TR/sparql11-overview/

  • W3C: OWL 2 Web ontology language document overview (second edition) (2012). https://www.w3.org/TR/owl2-overview/

  • W3C: SWRL: A semantic Web rule language combining OWL and RuleML (2004). https://www.w3.org/Submission/SWRL/

  • W3C: RIF overview (second edition) (2013). https://www.w3.org/TR/rif-overview/

  • . http://parliament.semwebcentral.org

  • Stardog: Website (2021). https://www.stardog.com

  • Nikkilä, R., Wiebensohn, J., Nash, E., Seilonen, I., Koskinen, K.: A service infrastructure for the representation, discovery, distribution and evaluation of agricultural production standards for automated compliance control. Comput. Electron. Agric. 80, 80–88 (2012). https://doi.org/10.1016/j.compag.2011.10.011

    Article  Google Scholar 

  • Tillett, N.D., Hague, T., Marchant, J.A.: A robotic system for plant-scale husbandry. J. Agric. Eng. Res. 69(2), 169–178 (1998)

    Article  Google Scholar 

  • Astrand, B., Baerveldt, A.J.: An agricultural mobile robot with vision-based perception for mechanical weed control. Auton. Robots 13(1), 21–25 (2002)

    Article  Google Scholar 

  • van Henten, E.J., van Asselt, C.J., Blaauw, S.K., Govers, M.H., Hofstee, J.W., Jansen, R.M., Nieuwenhuizen, A.T., Speetjens, S.L., Stigter, J.D., van Straten, G., van Willigenburg, L.G.E.J.: WURking: A small sized autonomous robot for the farm of the future. In: van Henten, E.J., Goense, D., Lokhurst, C. (eds.) Precision Agriculture ’09 – Proc. 7th Eur. Conf. Precis. Agric., Wageningen, pp. 833–840. Wageningen Academic, Wageningen (2009)

    Google Scholar 

  • Emmi, L., Gonzalez-de-Soto, M., Pajares, G., Gonzalez-de-Santos, P.: New trends in robotics for agriculture: Integration and assessment of a real fleet of robots. Sci. World J. (2014). https://doi.org/10.1155/2014/404059

    Article  Google Scholar 

  • Noack, P.O., Muhr, T., Demmel, M., Stafford, J., Werner, A.: An algorithm for automatic detection and elimination of defective yield data. In: Proc. 4th Eur. Conf. Precis. Agric., vol. 1, pp. 445–450. (2003)

    Google Scholar 

  • Zhang, C., Kovacs, J.M.: The application of small unmanned aerial systems for precision agriculture: A review. Precis. Agric. 13, 693 (2012). https://doi.org/10.1007/s11119-012-9274-5

    Article  Google Scholar 

  • Sørensen, C.G., Rodias, E., Bochtis, D.: Auto-steering and controlled traffic farming – Route planning and economics. In: Pedersen, S., Lind, K. (eds.) Precision Agriculture: Technology and Economic Perspectives. Progress in Precision Agriculture, pp. 129–145. Springer, Cham (2017)

    Chapter  Google Scholar 

  • Nikkilä, R., Nash, E., Wiebensohn, J., Seilonen, I., Koskinen, K.: Spatial inference with an interchangeable rule format. Int. J. Geogr. Inf. Sci. 27(6), 1210–1226 (2013)

    Article  Google Scholar 

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Authors and Affiliations

  1. Faculty for Agricultural and Environmental Sciences, Rostock University, Rostock, Germany

    Ralf Bill & Görres Grenzdörffer

  2. DVZ Datenverarbeitungszentrum Mecklenburg-Vorpommern GmbH, Schwerin, Germany

    Edward Nash

  3. Premslin Farm KG, Karstädt, Germany

    Jens Wiebensohn

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  1. Ralf Bill
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  2. Edward Nash
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  3. Görres Grenzdörffer
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  4. Jens Wiebensohn
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Correspondence to Ralf Bill .

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Editors and Affiliations

  1. University of Applied Sciences Neubrandenburg, Neubrandenburg, Germany

    Wolfgang Kresse

  2. Esri, Vienna, VA, USA

    David Danko

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Bill, R., Nash, E., Grenzdörffer, G., Wiebensohn, J. (2022). Geographic Information Systems in Agriculture. In: Kresse, W., Danko, D. (eds) Springer Handbook of Geographic Information. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-030-53125-6_24

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