Urban development in the Athens metropolitan area using remote sensing data with supervised analysis and GIS

In this study, a set of multi‐spectral satellites images were used to locate and identify the irregular settlements zones in the Athens metropolitan area. To achieve this goal, indexes—Brightness Index and Normalized Difference Vegetation Index—and supervised classifications are computed and applied to the images. In order to locate and identify these regions, common biophysical characteristics related to the urban and suburban landscape structures were identified. Five types of biophysical class were distinguished: (1) inner dense city with high buildings and absence of vegetation; (2) suburban areas with recent construction of buildings and absence of vegetation; (3) green suburban areas; (4) high‐density vegetation zones; and (5) recent forest fire regions. Some limitations are presented and discussed due to confusion of land‐cover types between bare land and recent constructed areas, or between various types of vegetation and some urban green zones. Results are integrated within a Geographical Information System (GIS), allowing the user to check the legal situation of the classified areas using the Urban Plan of Athens (1983–1995) documentation. This facilitates a proposal and representation of typology of irregular settlements. Such techniques might be very fruitful for developing countries or recently industrialized ones to identify specific irregular settlements.