Author(s)

M. CAPRIOLI & E. TARANTINO

Abstract

Land cover exerts a great influence on many basic environmental processes and consequently any transformation in it may have a marked impact on the environment from the local to the global scales. In multidisciplinary research contexts, satellite remote sensing offers opportunities both to evaluate the effects of these processes and to provide one of the information layers needed for designing national strategies oriented to protection and sustainable use of our resources. The advent of recent satellite imagery has increased the possibility to investigate large-scale areas in great detail. Together with an increase in spatial and radiometric resolution, there is, usually, an increase in the variability within land parcels, generating a decrease in the accuracy of land use classification on a per-pixel basis. In order to avoid such negative impacts, an object-oriented classification methodology on IKONOS multispectral data has been implemented on the test area of the Alta Murgia National Park, in the Apulia region (Italy), where soil adaptation for agricultural practices, through rock breaking, has taken place over the last 20 years. The analysis has been conducted with a classification strategy that is able to distinguish land use functions on the basis of differences in spatial distribution and pattern of land cover forms. It consists of two phases: segmentation of the image into meaningful multipixel objects of various sizes, based on both spectral and spatial characteristics of groups of pixels; then, assignment of the segments (objects) to classes using fuzzy logic and a hierarchical decision key.

Keywords

land cover transformation, object-oriented classification, VHR satellite imagery.