标题：Agroecological zoning as a necessary tool for monitoring evaluation of sensitive environments: Application to the area of low plains of Southern Tunisia
期刊名称：Science et changements planétaires / Sécheresse
印刷版ISSN：1147-7806
电子版ISSN：1777-5922
出版年度：2009
卷号：20
期号：4
页码：325-332
DOI：10.1684/sec.2009.0210
出版社：John Libbey Eurotext
摘要：Figures See all figures Authors Hanen Dhaou , Abderrazek Belghith Institut des régions arides Route El Jorf Médenine 4119 Tunisie, Centre national de la télédétection BP 200 1080 Tunis Cedex Tunisie Key words: agro-ecological zoning, cartographic generalisation, degradation, satellite imaging, Tunisia DOI : 10.1684/sec.2009.0210 Page(s) : 325-32 Published in: 2009 The natural and anthropized environment is presented in the form of a mosaic of landscapes and homogeneous zones. This homogeneity is due to a similarity of potentials and constraints of the parameters which constitute these zones. The zoning or the segmentation of the studied area facilitates its analysis and follow up. Such work consists in splitting the area into homogeneous units according to preset criteria. In this work the segmentation of the area into homogeneous zones was conducted on the basis of interaction of the parameters and the characteristics of soils, topography, biologic resources, climate and land use. These parameters were organised in layers in a geographical data base were they have been assigned weighting factors according to their role in the building of the homogeneous zone. This same work was also used to set up a methodology for the development of this tool of monitoring evaluation of sensitive environments. The developed methodology was applied to the area of low plains of southern Tunisia. This work of zoning became easier by using satellite images which made it possible to produce and update the parameters used. The GIS also made it possible to cross these parameters by sets of priorities according to their weights. In fact, the development of remote sensing and the evolution of spatial resolution have considerably increased the capacity of GIS to analyse and process multi-criterion and multi-scalar data.
