Análisis de la contaminación ambiental usando técnicas de teledetección y análisis de componentes principales

Due to population growth and industrialization, air pollution has become one of Colombia’s major issues in recent years. It affects large cities, harming the environment and human health. Therefore, in this paper, we propose a methodology to analyze air pollution in Medellin, Colombia using remote sensing techniques, Landsat-7 and Landsat-8 images, and air quality variables. The proposed methodology consists of four stages: (i) image preprocessing; (ii) image processing and calculation of the Surface Temperature (TS), Normalized Difference Vegetation Index (NDVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Normalized Difference Water Index (NDWI), and Normalized Difference Soil Index (NSI); (iii) interpolation of air quality variables, Particulate Matter (PM10 and PM2.5), Nitrogen Dioxide (NO2), and Ozone (O3); and (iv) principal component analysis. Based on the applied techniques, together with the estimation of the first major component (which contains 90% of information variation), an air quality map is obtained. According to this map, the sources of pollution are found in sectors with little vegetation cover, a great number of buildings, and high traffic flow. Conversely, areas with good air quality include sectors with greater vegetation cover, which are usually found in the limits of the city and in socioeconomic strata 4, 5, and 6. This map could be used as input for timely decision-making regarding urban planning because it allows for an early intervention in areas with poor air quality.