Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine

Detalhes bibliográficos
Autor(a) principal: OLIVEIRA JÚNIOR, José Galdino de
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFRPE
Texto Completo: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9095
Resumo: Land use and cover change is the leading cause of worldwide land degradation. However, efficient means of detecting and monitoring these environmental changes improve the understanding of this process, especially in developing more effective policies to combat land degradation. The objective of this study was to evaluate the spatio-temporal trends of environmental changes that occurred in the Desertification Nucleus of Cabrobó (DNC), PE, (comprised of the municipalities of Belém do São Francisco, Cabrobó, Carnaubeira da Penha, Floresta, and Itacuruba) between 2001 and 2020. We obtained rainfall data from weather stations belonging to the National Meteorology Institute and the National Water and Sanitation Agency, used to validate the CHIRPS product data on an annual scale via statistical indicators (Pearson correlation coefficient, mean error, Nash-Sutcliffe coefficient of efficiency, percent BIAS and RMSE). Subsequently, we manipulated CHIRPS data, MODIS sensor products related to NDVI (MOD13), surface temperature (MOD11), surface albedo (MCD43), and potential evapotranspiration - PET (MOD16) and MapBiomas data in the Google Earth Engine digital platform (GEE) and QGIS software (version 3.10.9). Using a programming routine, we performed surface albedo and Vegetation Health Index (VHI) calculations, and, after that, we executed a spatio-temporal trend assessment for all biophysical parameters via non-parametric Mann-Kendall (MK) and Sen's Slope Estimator (SSE) tests. In addition, we analyzed land use and land cover changes over the last 20 years using MapBiomas data. The results obtained showed the effectiveness of using these orbital products for long-term environmental analysis and highlighting the municipalities of Belém do São Francisco, Cabrobó, and Floresta. Such counties showed significant trends at the 1% probability level of the biophysical indices (from a decrease in PET, NDVI, and VHI and an increase in albedo and surface temperature) due to greater land use and land cover change, which culminated in a loss of 285.3 km2 (15.6%), 87.04 km2 (5.25%) and 34.82 km2 (0.95%) of their respective original native vegetation cover areas. Such mapping methodology proved to be effective for studies related to the discrimination of spatio-temporal trends in the region of the Desertification Nucleus of Cabrobó, thus being able to be applied in the future in other areas of the Caatinga after the appropriate methodological adjustments.
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spelling LOPES, Pabrício Marcos OliveiraMOURA, Geber Barbosa de AlbuquerqueOLIVEIRA JÚNIOR, José Francisco dehttp://lattes.cnpq.br/3514941731206738OLIVEIRA JÚNIOR, José Galdino de2023-06-20T18:45:45Z2022-02-18OLIVEIRA JÚNIOR, José Galdino de. Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine. 2022. 79 f. Dissertação (Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9095Land use and cover change is the leading cause of worldwide land degradation. However, efficient means of detecting and monitoring these environmental changes improve the understanding of this process, especially in developing more effective policies to combat land degradation. The objective of this study was to evaluate the spatio-temporal trends of environmental changes that occurred in the Desertification Nucleus of Cabrobó (DNC), PE, (comprised of the municipalities of Belém do São Francisco, Cabrobó, Carnaubeira da Penha, Floresta, and Itacuruba) between 2001 and 2020. We obtained rainfall data from weather stations belonging to the National Meteorology Institute and the National Water and Sanitation Agency, used to validate the CHIRPS product data on an annual scale via statistical indicators (Pearson correlation coefficient, mean error, Nash-Sutcliffe coefficient of efficiency, percent BIAS and RMSE). Subsequently, we manipulated CHIRPS data, MODIS sensor products related to NDVI (MOD13), surface temperature (MOD11), surface albedo (MCD43), and potential evapotranspiration - PET (MOD16) and MapBiomas data in the Google Earth Engine digital platform (GEE) and QGIS software (version 3.10.9). Using a programming routine, we performed surface albedo and Vegetation Health Index (VHI) calculations, and, after that, we executed a spatio-temporal trend assessment for all biophysical parameters via non-parametric Mann-Kendall (MK) and Sen's Slope Estimator (SSE) tests. In addition, we analyzed land use and land cover changes over the last 20 years using MapBiomas data. The results obtained showed the effectiveness of using these orbital products for long-term environmental analysis and highlighting the municipalities of Belém do São Francisco, Cabrobó, and Floresta. Such counties showed significant trends at the 1% probability level of the biophysical indices (from a decrease in PET, NDVI, and VHI and an increase in albedo and surface temperature) due to greater land use and land cover change, which culminated in a loss of 285.3 km2 (15.6%), 87.04 km2 (5.25%) and 34.82 km2 (0.95%) of their respective original native vegetation cover areas. Such mapping methodology proved to be effective for studies related to the discrimination of spatio-temporal trends in the region of the Desertification Nucleus of Cabrobó, thus being able to be applied in the future in other areas of the Caatinga after the appropriate methodological adjustments.A mudança no uso e cobertura da terra é a principal causa de processos de degradação ambiental ao redor do mundo. Contudo, meios eficientes de detecção e monitoramento dessas alterações ambientais melhoram o entendimento de tal processo, principalmente no desenvolvimento de políticas mais eficazes de combate à degradação ambiental. O objetivo desse estudo foi avaliar as tendências espaço-temporais das mudanças ambientais ocorridas no Núcleo de Desertificação de Cabrobó (NDC), PE, (composto pelos municípios de Belém do São Francisco, Cabrobó, Carnaubeira da Penha, Floresta e Itacuruba) entre 2001 e 2020. Dados pluviométricos foram obtidos de estações meteorológicas pertencentes ao Instituto Nacional de Meteorologia e à Agência Nacional de Águas e Saneamento Básico, sendo usados para validar os dados do produto CHIRPS em escala anual via indicadores estatísticos (Coeficiente de Correlação de Pearson, Erro Médio, Coeficiente de Eficiência de Nash-Sutcliffe, BIAS Percentual e RMSE). Posteriormente, os dados do CHIRPS, os produtos do sensor MODIS relacionados ao NDVI (MOD13), temperatura de superfície (MOD11), albedo de superfície (MCD43) e evapotranspiração potencial - ETp (MOD16) e os dados do MapBiomas foram manipulados na plataforma digital Google Earth Engine (GEE) e no software QGIS (versão 3.10.9). Por meio de uma rotina de programação, foram realizados os cálculos do albedo de superfície e do Vegetation Health Index (VHI) e, após isto, foi feita uma avaliação de tendência espaço-temporal para todos os parâmetros biofísicos, via testes não-paramétricos Mann-Kendall (MK) e Sen's Slope Estimator (SSE). Além disso, foi executada uma análise das alterações de uso e cobertura da terra nos últimos 20 anos a partir do MapBiomas. Os resultados obtidos apontaram a eficácia do uso destes produtos orbitais para a análise ambiental a longo prazo, assim como destacaram os municípios de Belém do São Francisco, Cabrobó e Floresta com tendências significativas ao nível de 1% de probabilidade dos índices biofísicos (de decréscimo para a ETp, o NDVI e o VHI, e de acréscimo para o albedo e a temperatura de superfície) devido à maior alteração de uso e cobertura da terra, que culminou em uma perda de 285,3 km2 (15,6%), 87,04 km2 (5,25%) e 34,82 km2 (0,95%) das suas respectivas áreas de cobertura vegetal nativas originais. Tal metodologia de mapeamento demonstrou ser eficaz para estudos ligados à discriminação de tendências espaço-temporais na região do Núcleo de Desertificação de Cabrobó, podendo assim, ser aplicada futuramente em outras áreas de Caatinga após às devidas adequações metodológicas.Submitted by (ana.araujo@ufrpe.br) on 2023-06-20T18:45:45Z No. of bitstreams: 1 Jose Galdino de Oliveira Junior.pdf: 2480963 bytes, checksum: cfe811e94c73bf146b5291c111421ed2 (MD5)Made available in DSpace on 2023-06-20T18:45:45Z (GMT). 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dc.title.por.fl_str_mv Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
dc.title.alternative.eng.fl_str_mv Detection of environmental changes in the brazilian semi-arid using time series and Google Earth Engine
title Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
spellingShingle Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
OLIVEIRA JÚNIOR, José Galdino de
Caatinga
Degradação ambiental
Mudança climática
Precipitação (Meteorologia)
Sensoriamento
CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
title_short Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
title_full Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
title_fullStr Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
title_full_unstemmed Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
title_sort Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine
author OLIVEIRA JÚNIOR, José Galdino de
author_facet OLIVEIRA JÚNIOR, José Galdino de
author_role author
dc.contributor.advisor1.fl_str_mv LOPES, Pabrício Marcos Oliveira
dc.contributor.referee1.fl_str_mv MOURA, Geber Barbosa de Albuquerque
dc.contributor.referee2.fl_str_mv OLIVEIRA JÚNIOR, José Francisco de
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/3514941731206738
dc.contributor.author.fl_str_mv OLIVEIRA JÚNIOR, José Galdino de
contributor_str_mv LOPES, Pabrício Marcos Oliveira
MOURA, Geber Barbosa de Albuquerque
OLIVEIRA JÚNIOR, José Francisco de
dc.subject.por.fl_str_mv Caatinga
Degradação ambiental
Mudança climática
Precipitação (Meteorologia)
Sensoriamento
topic Caatinga
Degradação ambiental
Mudança climática
Precipitação (Meteorologia)
Sensoriamento
CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
dc.subject.cnpq.fl_str_mv CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
description Land use and cover change is the leading cause of worldwide land degradation. However, efficient means of detecting and monitoring these environmental changes improve the understanding of this process, especially in developing more effective policies to combat land degradation. The objective of this study was to evaluate the spatio-temporal trends of environmental changes that occurred in the Desertification Nucleus of Cabrobó (DNC), PE, (comprised of the municipalities of Belém do São Francisco, Cabrobó, Carnaubeira da Penha, Floresta, and Itacuruba) between 2001 and 2020. We obtained rainfall data from weather stations belonging to the National Meteorology Institute and the National Water and Sanitation Agency, used to validate the CHIRPS product data on an annual scale via statistical indicators (Pearson correlation coefficient, mean error, Nash-Sutcliffe coefficient of efficiency, percent BIAS and RMSE). Subsequently, we manipulated CHIRPS data, MODIS sensor products related to NDVI (MOD13), surface temperature (MOD11), surface albedo (MCD43), and potential evapotranspiration - PET (MOD16) and MapBiomas data in the Google Earth Engine digital platform (GEE) and QGIS software (version 3.10.9). Using a programming routine, we performed surface albedo and Vegetation Health Index (VHI) calculations, and, after that, we executed a spatio-temporal trend assessment for all biophysical parameters via non-parametric Mann-Kendall (MK) and Sen's Slope Estimator (SSE) tests. In addition, we analyzed land use and land cover changes over the last 20 years using MapBiomas data. The results obtained showed the effectiveness of using these orbital products for long-term environmental analysis and highlighting the municipalities of Belém do São Francisco, Cabrobó, and Floresta. Such counties showed significant trends at the 1% probability level of the biophysical indices (from a decrease in PET, NDVI, and VHI and an increase in albedo and surface temperature) due to greater land use and land cover change, which culminated in a loss of 285.3 km2 (15.6%), 87.04 km2 (5.25%) and 34.82 km2 (0.95%) of their respective original native vegetation cover areas. Such mapping methodology proved to be effective for studies related to the discrimination of spatio-temporal trends in the region of the Desertification Nucleus of Cabrobó, thus being able to be applied in the future in other areas of the Caatinga after the appropriate methodological adjustments.
publishDate 2022
dc.date.issued.fl_str_mv 2022-02-18
dc.date.accessioned.fl_str_mv 2023-06-20T18:45:45Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
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dc.identifier.citation.fl_str_mv OLIVEIRA JÚNIOR, José Galdino de. Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine. 2022. 79 f. Dissertação (Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Federal Rural de Pernambuco, Recife.
dc.identifier.uri.fl_str_mv http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9095
identifier_str_mv OLIVEIRA JÚNIOR, José Galdino de. Detecção de mudanças ambientais no semiárido brasileiro usando séries temporais e Google Earth Engine. 2022. 79 f. Dissertação (Programa de Pós-Graduação em Engenharia Agrícola) - Universidade Federal Rural de Pernambuco, Recife.
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dc.publisher.none.fl_str_mv Universidade Federal Rural de Pernambuco
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dc.publisher.initials.fl_str_mv UFRPE
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Departamento de Engenharia Agrícola
publisher.none.fl_str_mv Universidade Federal Rural de Pernambuco
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