A Method to Classify Ecoclimatic Arid and Semi-Arid Zones in Circum-Saharan Africa Using Monthly Dynamics of Multiple Indicators
Résumé
Within the context of monitoring desertification using a network of observatories, one faces the problem of the representativeness of biophysical, ecological and socio-economical variations. Ideally one would choose at least one observatory for each homogeneous zone, using indicators that capture these variations. Here we focused only on ecoclimatic aspects defined by the global physical and climatic conditions characterising arid and semi-arid zones. The challenging aim of this paper is to spatially identify the different patterns of ecoclimatic variations. For most of the indicators of arid or semi-arid zones, temporal characteristics and interactions through a typical year are observed. In order to take into account these dynamics in the clustering approach one must use a methodology that captures interactions between spatial location, time of measurement and indicator measured. For this purpose a multiway analysis, gen-eralising PCA (Principal Component Analysis), has been used on internationally recognised ecoclimatic indicators [1], [2] that characterise arid and semi-arid zones. Most of these indicators were used non-dynamically or qualitatively to approve and certify observatories of the ROSELT network (Réseau d'Observatoires pour le Suivi Ecologiquè a Long Termes) [3]. A direct application of this method would be to assess homogeneity and validity of ecoclimatic characteristics for each observatory comparatively to its regional location within its country or within the whole circum-Saharan region.
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