O crescimento das cidades juntamente com a formação desordenada de grandes metrópoles ao redor do mundo resulta em grandes mudanças no uso e ocupação do solo. Porém, há poucos estudos que relacionem a expansão urbana e seus efeitos nas cidades do Nordeste do Brasil (NEB). Assim, o objetivo deste estudo foi avaliar a expansão urbana em Maceió-Alagoas entre 1985 e 2020 a partir de produtos orbitais Land Surface Temperature (LST) e Normalized Difference Vegetation Index (NDVI), com a finalidade de detectar as mudanças e os seus efeitos ambientais. Para isto foram utilizados produtos orbitais adquiridos dos sistemas-sensores Landsat 5/Thematic Mapper (TM) e 8/Operational Land Imager (OLI). No estudo utilizaram-se quatro imagens para a observação da variação espaço-temporal da urbanização, correspondente aos anos de 1987,1998, 2006 e 2020. Os mapas temáticos de NDVI e LST foram gerados a partir do software de ambiente R. Os resultados obtidos apontaram alterações substanciais no uso e ocupação do solo detectado pelo NDVI, e aumento na LST ao longo dos 35 anos. Tal variabilidade ocorreu nos bairros localizados na porção norte e noroeste da cidade, resultante dos programas de incentivo do Governo Federal na década de 2009, principalmente o Complexo do Benedito Bentes (CBB) com as maiores transformações no uso e ocupação do solo, principalmente o maior aumento na LST entre 7,5-10,0°C. Os efeitos produzidos pela expansão urbana foram atenuados devido as áreas de proteção ambiental.
The objectives of the study are: i) to evaluate the climatology of rain in Maceió based on observed data, with emphasis on climatic and environmental aspects and ii) to validate the precipitation product for the municipality. Data from 1979 to 2013 of the precipitation product CHELSA (Climatologies at High Resolution for the Earth's Land Surface Areas) were validated by rainfall data from the National Water Agency (NWA) from 1960 to 2016. Statistical indicators showed a high coefficient of determination and linear correlation between CHELSA and observed data (R2 = 0.80; r = 0.89) and the smallest errors (SEE = 6.58 mm and RMSE = 18.76 mm), therefore the CHELSA product can be applied in the region. The time series presented a period 1 (P1) - (1960 to 1989) with rainfall above the historical average and a period 2 (P2) - (1990 to 2016) with a significant reduction in rainfall. Observed data versus climatological normals showed a significant decrease in normal 1 (1961-1990) in the rainy season, while in relation to normal 2 (1981-2010) there was an increase in the months of February, March and April (between 10 to 20%) and October and December (between 5 to 15%). The spatial distribution of monthly rainfall via the CHELSA product showed the formation of a pluviometric gradient between the coast and the upper part of Maceió. The topography influences the rainfall regime in neighborhoods belonging to the administrative regions (AR) - (R4, R5 and R6) with the highest rainfall records. The ENOS phases are directly responsible for the variability of interannual rain, while the decadal variability corresponded to the PDO phase change and changes in land use and occupation in Maceió.
O surgimento de incêndios florestais pode ser de origem antrópica ou natural, ambas causam grandes prejuízos socioeconômico e ambiental, e em boa parte dessas ocorrências são resultantes da ocorrência de Focos de Calor (FC). Nos últimos anos, o Brasil tem sofrido com o aumento significativo de FC, ao qual resultaram em grandes incêndios. Desta maneira, o objetivo do presente estudo foi diagnosticar o comportamento espaço-temporal dos FC no Brasil entre 1999 e 2020, baseados nos dados de dados BDQueimadas do CPTEC/INPE. Para a manipulação e o processamento dos dados, utilizou-se o software de ambiente R versão 3.4-1. Após o armazenamento dos dados, calculou-se os registros totais, médias anual e mensal, e a composição dos anos mais significativos, neste caso, os anos de 2015, 2017, 2019 e 2020. Os resultados apontaram que os maiores acumulados totais e médios anuais variaram entre 10-50 mil FC e 0,5-1,5 mil FC, concentrados na região centro-norte do Brasil, principalmente nos estados do Maranhão, Pará e Tocantins. Este padrão de alto registros de FC está relacionado ao desmatamento e expansão agrícola nessas regiões. Em escala mensal, as maiores ocorrências de FC ocorrem entre os meses de agosto e novembro, com valores de 0,20-0,45 mil FC, devido ao período de estiagem. Verificou-se que nos últimos anos, o El Niño-Oscilação Sul influenciou a incidência dos FC através da persistência de longos períodos de estiagem, que resultaram em escassez de chuvas e grandes incêndios verificados em 2020 no bioma Pantanal.
In recent years, due to irregular rainfall, several regions across the globe suffer from some type of environmental degradation. Depending on the degree of intensity, they can lead to a series of socioeconomic problems, both regional and national. One of the most emblematic types of degradation today is the desertification development process, resulting in a combination of factors: anthropic, climatic, and/or environmental. In an attempt to understand the behavior of these impacts, this work evaluated the degradation process based on the Aridity Index (AI) on biomes located in the Brazilian Northeast (Caatinga, Atlantic Forest, Amazon, and Cerrado). The AI consists of the relationship between the use of evapotranspiration (in this case, the Thornthwaite estimation method) and precipitation. The data used correspond to the product Climatologies at high resolution for the earth's land surface areas (CHELSA), which have a spatial resolution of 1km x 1km and temporal resolution on a monthly scale, from 1979 to 2013. In addition, it was found that the AI behavior during years of the occurrence of the El Niño-Southern Oscillation (ENSO) warm phase, the El Niños. The identification of El Niño episodes was based on the Oceanic Niño Index (ONI) climate proxy, characterized by the Equatorial Pacific region known as the Niño 3.4 region, from which the years 1983, 1993, 1998, and 2012 were selected. AI results point out different behaviors between the biomes, mainly over the south of the northeastern Cerrado and the Caatinga, motivated by the strong variability of rainfall in the respective regions. The Caatinga stands out, which exhibited a large part of its area was classified as arid (AI between 0.05 -0.20) and hyper-arid (AI < 0.05), mainly in 2012. The Amazon and biomes, on the other hand. Atlantic Forest has areas classified as semi-arid (AI < 0.5). El Niño had a reduction in the AI values, motivated by the long periods of drought and irregular rainfall that negatively impacted the semi-arid of the Northeast region.
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