Empirical correction for the improvement of covers waterproof classifi-cation using medium resolution satellite images

Abstract

The classification of impermeable cover of shallow and unconfined aquifers becomes fundamental for purposes ofwater resources management and mathematical models, considering that this directly affects the amount of water that infiltrates the soil and recharges the aquifer. Although images of Landsat satellites are widely used for classification of the land, such images do not show appropriate for classification per pixel in urban landscapes due to its resolution. To circumvent this limitation, a method of correction was proposed with the use of vectorized and manually classified images, taken from Google Earth. Based on the proposed methodology, it was possible to establish an empirical relationship that allowed a more realistic calculation of impervious land cover classification from per pixel which generated significant errors in urban areas.Then, it was used to calculate the degree of waterproofing Aquifer Rio Claro in the city of Rio Claro / SP. In areas with high levels of waterproofing, variations in water level showed a different pattern of regions free of waterproofing, indicating reduced recharge rates in the urban center of Rio Claro / SP.This paper presents an alternative to improve the classification of sealed areas with satellite images with medium resolution surface overlying shallow aquifers in order to quantify the impacts on natural recharge of these aquifers is exempting them from the need to employ images with high resolution.