Detalhes bibliográficos
| Ano de defesa: |
2021 |
| Autor(a) principal: |
Oliveira, Anderson de |
| Orientador(a): |
Ribeiro, Andreza Portella
 |
| Banca de defesa: |
Ribeiro, Andreza Portella
,
Quaresma, Cristiano Capellani
,
Santos, Daniel Nery dos
|
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Nove de Julho
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Cidades Inteligentes e Sustentáveis
|
| Departamento: |
Administração
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Palavras-chave em Inglês: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://bibliotecatede.uninove.br/handle/tede/2981
|
Resumo: |
In search of measures and sharing and commitment to environmental issues, the United Nations team created the 2030 agenda, which lists 17 Sustainable Development goals (SDGs). Specifically, SDG 6 Drinking Water and Sanitation in addition to international cooperation, it is necessary to develop actions on a regional and local scale, aimed at protecting springs, rivers, basins and sharing technology and sewage treatment. The eutrophication process is caused by the disposal of effluents by residence, industries in rivers, streams, dams favor the enrichment of nutrients in aquatic environments, causes the proliferation of aerobic bacteria that causes the growth of algae that prevent the penetration of sunlight, preventing the exchange of oxygen from the water, resulting in the death of aquatic life. To assess the degree of eutrophication, traditionally used chemical methods, evaluating chlorophyll-a and phosphorus in water samples. In the study area, the Billings Dam, there are 11 monitoring stations. In situ collection is an expensive and time-consuming process and the objective of the research is to use remote sensing to monitor water quality in springs, using mathematical modeling using Landsat 8 satellite images, scenes from 2014 to 2016 triennial, to be a support tool for in situ collections, measuring chlorophyll-a and the Trophic State Index. The RGEE package was used, which uses the Google Earth Engine API that uses the R language for scripting, the QGIS software for the creation of thematic maps, and also the Jamovi software, Friedman's non-parametric test to compare data from Collection of CETESB and those from satellite images. The results of extracting the values of chlorophyll-a and the IET, using satellite images, brought good results, stating that it is possible to use this technique, as an aid and statistical tests, showing that there is no significant difference between the medians for the years of 2014 to 2016 between CETESB data in relation to estimated satellite data. Finally, the model to estimate chlorophyll-a showed that some points were discrepant compared to CETESB data, however, the dates of in situ collection and the passage of the Satellite in the study area did not coincide with the same period, with some differences from two to three weeks and also to cloud interference. The calculation of IET had no discrepant differences, as the median of each year of satellite images was calculated to assess the degree of trophy. |
