Is the “random thing” pertinent in deriving mapped data?
Are geographic distributions a natural extension of numerical distributions? Can spatial dependencies be modeled? How can “on-farm studies” augment agriculture research? This paper explores the conceptual differences between spatial and non-spatial data, its analysis and the opportunities and challenges it poses. Introduction Site-specific management, commonly referred to as precision farming, is about doing the right thing, in the right way, at the right place and time. It involves assessing and reacting to field variability and tailoring management actions, such as fertilization levels, seeding rates and variety selection, to match changing field conditions. It assumes that managing field variability leads to both cost savings and production increases. Site-specific management isn t just a bunch of pretty maps, but a set of new procedures that link mapped variables to appropriate management actions. This conceptual linkage between crop productivity and field conditions requires the t
