Empirical Analysis of Fragility of Natural Environments (EAFNE) gives support to the territorial planning of areas in the urban expansion process. Once the EAFNE method is sensitive to land use and land cover data, it is necessary that this type of mapping is highly accurate. Given the high level of accuracy that can be obtained on land use/land cover mapping by applying the hybrid method of digital images classification, in this paper we aimed to verify the effects of the hybrid method on EAFNE. The comparison between the maps of Potential and Emerging Vulnerability generated from a land use/land cover map classified by automatic classification (global accuracy: 88%) and the maps of Potential and Emerging Vulnerability generated from a land use/land cover maps classified using the hybrid method (global accuracy: 97%) shows that the use of the hybrid method for the classification of land use/land cover maps lead to different percentages of areas classified in levels of environmental instability, which can result in restriction of land use/land cover of some areas to be over or under estimated.