Identificação e quantificação semiautomática de desmatamento por sensoriamento remoto

Abstract

Forests play an important role in human history and deforestation accompanies population growth and development for thousands of years. Climate, culture, technology and trade have influence on the acceleration or deceleration of deforestation. It is estimated that approximately 50% of the area of the Cerrado has already been cleared to make way for farmland, pastures and urban areas. In order to optimize the current procedures for detecting deforestation, usually performed manually by photo interpretation of satellite imagery, this study presents, tests and validates the hypothesis that it is possible to perform such monitoring by mathematical operations between thematic maps of remnant vegetation. Case study conducted in the city São Gabriel do Oeste, in the state of Mato Grosso do Sul, where the variation of the vegetation was studied using TM/LANDSAT 5 satellite imagery and Geographic Information Systems (GIS), showed that it is possible to carry out the proposed monitoring with accurate results and in less than time required for image interpretation technique.