A multi-scale segmentation/object relationship modelling methodology for landscape analysis

Natural complexity can best be explored using spatial analysis tools based on concepts of landscape as process continuums that can be partially decomposed into objects or patches. We introduce a five-step methodology based on multi-scale segmentation and object relationship modelling. Hierarchical patch dynamics (HPD) is adopted as the theoretical framework to address issues of heterogeneity, scale, connectivity and quasi-equilibriums in landscapes. Remote sensing has emerged as the most useful data source for characterizing land use/land cover but a vast majority of applications rely on basic image processing concepts developed in the 1970s: one spatial scale, per-pixel classification of a multi-scale spectral feature space. We argue that this methodology does not make sufficient use of spatial concepts of neighbourhood, proximity or homogeneity. In contrast, the authors demonstrate in this article the utility of the HPD framework as a theoretical basis for landscape analysis in two different projects using alternative image processing methodologies, which try to overcome the ‘pixel-centred’ view. The first project focuses on habitat mapping using a high dimension multi-scale GIS database. Focal patches are derived through aggregating automatically generated landscape segments using sub-patch information including dominant tree crown densities and species. The second project uses fractal-based segmentation to produce multiple candidate segmented agricultural scenes, and then develops a decision framework to choose the combination of segmentation levels best suited to identifying shrub encroachment. The challenge and flexibility of the multi-scale segmentation/object relationship modelling approach lies in the defining of the semantic rules which relate the lower level landscape units or holons to higher levels of organization. We seek to embrace the challenges of scale and hierarchy in landscapes and have tested two different ways to decompose complex natural environments into focal units utilising topological relations to model between the smallest units of differentiation and the focal level. We believe the use of a HPD theoretical framework will help development of better tools for characterizing the patterns and processes, acting through a range of scales, which make up landscapes. © 2003 Elsevier Science B.V. All rights reserved.