Digital image processing (DIP) applied to the analysis of the use and coverage of São Sebastião, federal district, Brazil

Abstract

The article explores the application of Digital Image Processing (DIP) and Remote Sensing (RS) techniques in analyzing land use and land cover changes in the Administrative Region of São Sebastião, Federal District, Brazil. DIP plays a pivotal role in automated data analysis and interpretation, particularly in the context of RS, where it efficiently processes Earth's surface data collected by sensors on satellites, aircraft, and Unmanned Aerial Vehicles (UAVs). The study covers the period from 2000 to 2020, utilizing data from satellites such as Landsat to provide a continuous view of the region. The spatial and temporal analyses incorporate considerations of hypsometry, slope, and surface temperature, aiming to understand the dynamics of land use and its impact on the microclimate. The methodology involves a comprehensive literature review, acquisition of spatial data from government agencies, and the use of computational tools such as ArcGIS and ENVI. Classification of Landsat images employs false-color compositions and Maximum Likelihood Classification to identify urban areas, water bodies, vegetation, shrubland, and exposed soil. The analysis also includes generating land surface temperature maps. Results indicate significant urban expansion, particularly in the Southeast direction, with a concentration of urban activities. The study highlights a continuous growth trend over the years, emphasizing the importance of understanding and monitoring these transformations for sustainable planning. The article contributes to the field by providing valuable insights into the dynamics of urban growth, offering a clear spatial distribution of changes over time. The detailed methodology ensures the accuracy and reliability of the analysis, supporting informed decision-making in the context of environmental exploration and regional development planning.