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A methodological proposal to analyze urban sprawl, negative environmental impacts, and land degradation in the case of João Pessoa City (Brazil) between 1991 and 2018.

Cynthia Alves Félix de SousaJosé Augusto Ribeiro da SilveiraCelso Augusto Guimarães SantosRicharde Marques da Silva
Published in: Environmental monitoring and assessment (2023)
Urbanization and changes in urban spaces have caused severe environmental and social problems in large Brazilian cities. As such, this study presents a methodological proposal to analyze urban sprawl, negative environmental impacts, and land degradation. The methodology employed involves a combination of remote sensing data, environmental modeling techniques, and mixed-method analyses of environmental impacts from 1991 to 2018. Analyzed variables included vegetation, surface temperature, water quality, and soil degradation within the study area. These variables were assessed based on an interaction matrix used to evaluate environmental impacts (low, medium, or high impacts). The obtained results show conflicts of land use and land cover (LULC), a lack of urban sanitation infrastructure, and an absence of environmental monitoring and inspection. A reduction of 24 km 2 of arboreal vegetation was observed from 1991 to 2018. High values of fecal coliforms were found in March across nearly all analyzed points, indicating a seasonal discharge of effluents. The interaction matrix presented various negative environmental impacts, including increased land surface temperature, soil degradation, inappropriate solid waste disposal, devastation of remaining vegetation, water pollution by domestic effluents, and the incidence of erosive processes. Ultimately, the impact quantification determined that the study area has a medium degree of significance in terms of environmental impacts. Thus, refining this quantification method will contribute to future research by making the analysis processes more objective and efficient.
Keyphrases
  • human health
  • climate change
  • life cycle
  • water quality
  • mental health
  • risk assessment
  • heavy metals
  • risk factors
  • particulate matter
  • drug induced
  • drinking water
  • big data
  • sewage sludge
  • municipal solid waste