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In the city of Bueno Brandão, South of Minas Gerais State, Brazil, the Watershed of Rio das Antas is located prior to the public water supply and is susceptible to hydro-degradation due to the intensive agricultural activities developed in the area. The potato plantation is the most significant cropping in the city. Because of the possibility of interfering in the preservation areas, mainly the ones surrounding water courses and springs, it is very important to do the assessment of the plantation sites, in order to avoid the risk of water contamination. The procedures adopted by the agro activity farmers generally present the following features: intensive use of agro-chemicals, cropping in places with slopes which are higher than 20%, close to or in permanent preservation areas. The scope of this study was to develop the proper methodology for the assessment of the plantation areas, regarding the short time of procedure, as the period between the plantation and the harvest occurs in six months the furthest. These areas vary year in year out, as the plantation sites often change due to the land degradation. Because of that, geotechnologies are recommended to detect the plantation areas by the use of satellite images and accurate data processing. Considering the availability of LANDSAT medium resolution images, methods for their appropriate classification were approached to provide effective target detection.

The present work intends to identify the areas which have appropriate environment for the procreation of the disease vector in the northern part of Labrea municipality, in the state of Amazonas. The environmental conditions found in the study region are highly favorable to the elevate density of mosquitoes and to their procreation in the larvae phase, as it is known that the ideal environment considered to its procreation is the aquatic one, where occurs around 3⁄4 of the mosquito life cycle. The digital image processing techniques have been considered as an important tool to identify these areas and have aided the decision making in the public health segment. In order to achieve the purpose of this work, two approaches were made: the object-oriented analysis classification of an optical image and the proposal of a new methodological approach for the terrain description, resulting from the application of the algorithm called HAND. In this approach, the purpose is to characterize both the water bodies identified during the image classification and the possible flood regions, thus, favorable for the procreation of the Anopheles vector. In the spatial analysis stage, a local spatial regression model was used. As a result, it was concluded that de descriptor terrain model in the flood areas of the study region is an explanatory factor of the malaria incidence in the northern part of Labrea.