ABSTRACT

Introduction The past few years have been marked by an unprecedented burgeoning of geographic information systems (GIS) arid remote sensing applications in natural resource sciences and ecology. These applications span physical scales ranging from the microscopic (e.g., soil structure profiles) to regional and global scales. Regionalized variable analysis (e.g., spatial statistics) is undergoing a similar revival in the environmental sciences (Ford and Renshaw, 1984; Bradshaw, 1991; Turner et ai, 1991). With a parallel growth in computer technology, an increased reliance on these techniques is anticipated (Stafford et ai, this volume).