Precision agriculture

[File:Daedelus comparison, remote sensing in precision farming.jpg|thumb|upright|False-color images demonstrate remote sensing applications in precision farming. Courtesy NASA Earth Observatory]] 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), and Whelan et al. (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. 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.