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precision agriculture (PA) or satellite farming or site specific crop management (SSCM) is a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops. Crop variability typically has both a spatial and temporal component which makes statistical/computational treatments quite involved. The holy grail of precision agriculture research will be the ability to define a Decision Support System (DSS) for whole farm management with the goal of optimizing returns on inputs while preserving resources. The reality today is that seemingly simple concepts such as the ability to define management zones, areas where different management practices will apply, for a single crop type on a single field over time are difficult to define (see, for example, McBratney et al. (2005),〔McBratney, A., Whelan, B., Ancev, T., 2005. Future Directions of Precision Agriculture. Precision Agriculture, 6, 7-23.〕 and Whelan et al. (2003)〔Whelan, B.M., McBratney, A.B., 2003. Definition and Interpretation of potential management zones in Australia, In: Proceedings of the 11th Australian Agronomy Conference, Geelong, Victoria, Feb. 2-6 2003.〕). Whelan and McBratney (2003) articulate a number of approaches that are currently being used to define management zones (mostly by the research community); these include hand drawn polygons on yield maps, supervised and unsupervised classification procedures on satellite or aerial imagery, identification of yield stability patterns across seasons, etc. Among these many approaches is a phytogeomorphological approach which ties multi-year crop growth stability/characteristics to topological terrain attributes.〔Howard, J.A., Mitchell, C.W., 1985. Phytogeomorphology. ''Wiley''.〕〔Kaspar, T.C, Colvin, T.S., Jaynes, B., Karlen, D.L., James, D.E, Meek, D.W., 2003. Relationship between six years of corn yields and terrain attributes. ''Precision Agriculture'', 4, 87-101.〕 The interest in the phytogeomorphological approach stems from the fact that the geomorphology component typically dictates the hydrology of the farm field. Multi-year datasets are now becoming available that show this stability and these effects (Kaspar et al., (2003)), however, there is a lot of work remaining to create an actual DSS that could universally help farmers. It can be said that the practice of precision agriculture was enabled by the advent of GPS and GNSS. The farmer's and/or researcher's ability to locate their precise position in a field allows for the creation of maps of the spatial variability of as many variables as can be measured (e.g. crop yield, terrain features/topography, organic matter content, moisture levels, nitrogen levels, pH, EC, Mg, K, etc.). Further, these maps can be interpolated onto a common grid for comparison (see Whelan et al. (2003) and the reference to the VESPER kriging system). Spatial and temporal variability of crop variables are at the heart of PA, while the spatial and temporal behaviours of that variability are key to defining amendment strategies, or 'recipe maps'. Recipe maps would be the output of any generalized decision support system that could be defined for farm use. Precision agriculture has also been enabled by technologies like crop yield monitors mounted on GPS equipped combines, the development of variable rate technology (VRT) like seeders, sprayers, etc., the development of an array of real-time vehicle mountable sensors that measure everything from chlorophyll levels to plant water status, multi- and hyper-spectral aerial and satellite imagery, from which products like NDVI maps can be made, although the costs of these are high. ==Overview== Precision agriculture aims to optimize field-level management with regard to: * crop science: by matching farming practices more closely to crop needs (e.g. fertilizer inputs); * environmental protection: by reducing environmental risks and footprint of farming (e.g. limiting leaching of nitrogen); * economics: by boosting competitiveness through more efficient practices (e.g. improved management of fertilizer usage and other inputs). Precision agriculture also provides farmers with a wealth of information to: * build up a record of their farm; * improve decision-making; * foster greater traceability * enhance marketing of farm products * improve lease arrangements and relationship with landlords * enhance the inherent quality of farm products (e.g. protein level in bread-flour wheat) 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Precision agriculture」の詳細全文を読む スポンサード リンク
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