A Classification Procedure for Mapping Topo-climatic Conditions for Strategic Vegetation Planning Josep Maria Serra & Jordi Cristobal & Miquel Ninyerola Received: 25 May 2009 / Accepted: 21 June 2010 / Published online: 16 July 2010 # Springer Science+Business Media B.V. 2010 Abstract Environmental classification addresses issues involving the representation and analysis of continuous and variable ecological data. This study creates a methodology to define topo-climatic landscapes (TCL) in the north-west of Catalonia, which is situated in the north-east of the Iberian Peninsula. TCL provide data regarding the ecological behavior of a landscape in terms of its topography, physiog- nomy, and climate, which are the main drivers of an ecosystem. The variables selected are derived from a variety of different sources, such as remote sensing and climatic atlases. The methodology employed combines unsupervised iterative cluster classification with supervised fuzzy classifi- cation. Twenty eight TCL, which can be differentiated in terms of their vegetation physiognomy and vegetation altitudinal range type, were selected for the study area. Furthermore, a hierarchy among the TCL is established which permits the merging of clusters and allows for changes in thematic resolution. By using the topo-climatic landscape map, managers can identify patches with similar environmen- tal conditions and at the same time assess the uncertainty involved in classification. Keywords Environmental classification . Unsupervised classification . Cluster analysis . Topography . Climate . Remote sensing . Fuzzy logic Abbreviations TCL Topo-climatic Landscapes MCA Multiple correspondence analysis HMC Habitat Map of Catalonia 1 Introduction In recent years, many researchers have conducted studies aimed at defining landscape units and developing an ecological landscape classification [1]. A variety of approaches have been used to classify landscapes or, on a broader scale, to define eco-regions [2, 3]. The majority of these classifications have been based on ecological varia- bles related to landscape structure and have been carried out using landscape metrics [4], hydro-ecological factors [5], topography, and climatic variables [6, 7]. Defining homo- geneous climatic zones is also useful for ecosystem classification [8, 9]. According to Wolock [5], these classifications should “identify patterns in biotic and abiotic factors thought to generally influence ecological processes at a relatively broad scale” thus providing an ecological framework that encompasses specific uses and a broad ecological classification for management needs [10–12]. Two general approaches to landscape classification are identified [13]: human landscape-based classification [14] and biophysical approaches [15, 16]. In the present study, a biophysical approach was chosen to identify areas with similar topographic and climatic behavior. Remote sensing, on the other hand, makes it possible to describe land cover and classify landscapes [17] by providing information about a specific vegetation cover based on a set of widespread remote sensing indexes used in ecology [18], such as the normalized difference vegetation index (NDVI), wetness index computed (WI), and land surface temperature (LST) J. M. Serra (*) : M. Ninyerola Department of Animal Biology, Plant Biology and Ecology, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Valles, Barcelona, Spain e-mail: josep.serra@uab.cat J. Cristobal Department of Geography, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Valles, Barcelona, Spain Environ Model Assess (2011) 16:77–89 DOI 10.1007/s10666-010-9232-4