precision agriculture(PA) orsatellite farmingorsite specific crop management(SSCM)

(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 ofprecision agricultureresearch will be the ability to define aDecision 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, McBratneyet al. (2005),[2]and Whelan et al. (2003)[3]). 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 aphytogeomorphologicalapproach which ties multi-year crop growth stability/characteristics to topological terrain attributes.[4][5]The interest in the phytogeomorphological approach stems from the fact that thegeomorphologycomponent typically dictates thehydrologyof thefarm field. Multi-year datasets are now becoming available that show this stability and these effects (Kaspar et al., (2003)), however, thereis 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 ofGPSandGNSS. 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) andthe reference to the VESPERkrigingsystem). Spatial and temporal variability of crop variablesare 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 generalizeddecision support systemthat could be defined for farm use. Precision agriculture hasalso been enabled by technologies likecrop yield monitorsmounted on GPS equippedcombines, the development of variable rate technology (VRT)like seeders, sprayers, etc., the development of an array of real-time vehicle mountable sensors thatmeasure everything from chlorophyll levels to plant water status,multi-andhyper-spectralaerial and satelliteimagery, from which products likeNDVImaps can be made, although the costs of these are high