REMOTE SENSING TIME SERIES ANALYSIS AIMED AT DETECTING AND MONITORING BRAZILIAN IRON ORE MINING DISASTERS
Keywords: change detection, time series, natural disaster
Abstract. Iron mining is one of the main activities of the State of Minas Gerais (Brazil). However, this activity offers significant environmental risks and may harm the local population. In 2019, the Brazil experienced large environmental disaster related to iron mining in the municipality of Brumadinho. The collapse of mining waste water Dam caused the mud spill composed of the mixture of water and tailings minerals that traveled from the dam through the network of local drainage. In this work, it is analyzed the environmental impact of the dam's collapse with the help of remote sensing image using two spectral bands (red and near infrared). The comparative study carried out by analysing Landsat OLI of several months enables evaluating the effect of the event on the water resources and also monitor the evolution of the situation by comparing multiple images. In the first step, direct digital values are measured along the rivers to compare the sediment load in each date, which allows monitoring the situation of the rivers. In a second step, the image series is combined using binary encoding to visualize changes in the catchment. The study shows that the Paraopeba and Córrego do Feijão rivers suffered a great impact from the dam break and that they are slowly recovering from the tragic event.