Detalhes bibliográficos
| Ano de defesa: |
2020 |
| Autor(a) principal: |
BEZERRA, Alan Cézar
 |
| Orientador(a): |
MOURA, Geber Barbosa de Albuquerque |
| Banca de defesa: |
NASCIMENTO, Cristina Rodrigues,
RIBEIRO, Eberson Pessoa,
GALVÍNCIO, Josiclêda Domiciano,
LOPES, Pabrício Marcos Oliveira |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Agrícola
|
| Departamento: |
Departamento de Engenharia Agrícola
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9070
|
Resumo: |
Geotechnologies make it possible to analyze ecosystem information with spatial and temporal scope, especially remote sensing. In addition, digital cloud processing allows for increased processing time and data quantity. Therefore, this study aimed to verify spatial-temporal environmental changes through biophysical parameters in the state of Pernambuco in the period from 2000 to 2019 with the use of geotechnologies and digital processing on the cloud. The method consisted of collecting precipitation data from 45 stations throughout the state, from 1987 to 2019. These data were grouped following the cluster analysis methodology with Ward method to define homogeneous precipitation zones yearly. Then, the Rain Anomaly Index (RAI) was identified to determine the variability of rainfall, as well as the dry and the wet period. The analysis of biophysical parameters was carried out with MODIS products for the period from 2000 to 2019 on the Google Earth Engine platform. A representative image of each year was determined for the vegetation indices (NDVI, EVI and SAVI), water index (NDWI), albedo and surface temperature. To determine the image for each year, two different reduction criteria were used: the average and the maximum. Thus, 20 images were generated for each parameter in the total of 60 images for the period from 2000 to 2009 for the criterion of average reduction, and another 60 for maximum reduction, resulting in 120 images. The seasonality of the biophysical parameters was verified in the years considered of extreme precipitation: very dry and very humid. These images allowed for statistics of the images and the representation of the cards to be verified. Analysis of the grouping of homogeneous groups showed the formation of three homogeneous groups, one for the semiarid, another for the coast and another for a transition region between the wild (agreste) and forest zone (zona da mata). A period of recent drought was observed from 2012 to 2016 in all precipitation zones, and more prominent in the region of the semiarid group, due to the low annual precipitation rates. Statistically, there were no changes in biophysical parameters, and concerning the homogeneous precipitation zones, there was a tendency to reduce the vegetation cover in the coastal region of Pernambuco; the other groups showed no changes in parameters. In years of extreme precipitation, there is a difference in the level of responses of biophysical parameters, however the behavior between them is similar. For monitoring rainfall in the state of Pernambuco, the most appropriate biophysical parameter is the NDWI index. In the desertification nucleus of Cabrobó, there seems to be a shift towards the southeast, which requires a more detailed analysis and actions by the government to mitigate its effects. |
