ABSTRACT

Land change research necessarily draws upon an interdisciplinary milieu of theories and practices ranging from ecology to geography to policy and beyond; a dominant approach successfully used in this arena over the past few decades has been that of scale-pattern-process.1 Choice of scale influences which landscape patterns can be discerned, in turn used to infer process. The number of resulting landscape studies have increased substantially over the past decade.2,3,4,5 Assessing sensitivities of pattern detection and subsequent inferable processes to changes in scale (typically spatial resolution or pixel size) of remotely sensed data has become an important research agenda for remote sensing specialists.6,7 This work draws in particular on principles of landscape ecology that posit the possible impacts that scale can have on landscape characterization.8 Scale is comprised of two primary facets: grain, the size of an observational unit (e.g., the dimensions of a single pixel), and extent, typically represented as the size of the overall study area. Although these component parts are typically applied to spatial scale, they as easily may be applied to temporal scale (e.g., scale as the frequency of observation and extent as the total length of study).