With more than 80% of Brazilians living in cities, urbanization has had an important impact on climatic variations. São José dos Campos is located in a region experiencing rapid urbanization, which has produced a remarkable Urban Heat Island (UHI) effect. This effect influences the climate, environment and socio-economic development on a regional scale. In this study, the brightness temperatures and land cover types from Landsat TM images of São José dos Campos from 1986, 2001 and 2010 were analyzed for the spatial distribution of changes in temperature and land cover. A quantitative approach was used to explore the relationships among temperature, land cover areas and several indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) and Normalized Difference Built-up Index (NDBI). The results showed that urban and bare areas correlated positively with high temperatures. Conversely, areas covered in vegetation and water correlated positively with low temperatures. The indices showed that correlations between the NDVI and NDWI and temperature were low (<0.5); however, a moderate correlation was found between the NDBI and temperature.

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Background Migratory animals use information from the Earth’s magnetic field on their journeys. Geomagnetic navigation has been observed across many taxa, but how animals use geomagnetic information to find their way is still relatively unknown. Most migration studies use a static representation of geomagnetic field and do not consider its temporal variation. However, short-term temporal perturbations may affect how animals respond - to understand this phenomenon, we need to obtain fine resolution accurate geomagnetic measurements at the location and time of the animal. Satellite geomagnetic measurements provide a potential to create such accurate measurements, yet have not been used yet for exploration of animal migration. Methods We develop a new tool for data fusion of satellite geomagnetic data (from the European Space Agency’s Swarm constellation) with animal tracking data using a spatio-temporal interpolation approach. We assess accuracy of the fusion through a comparison with calibrated terrestrial measurements from the International Real-time Magnetic Observatory Network (INTERMAGNET). We fit a generalized linear model (GLM) to assess how the absolute error of annotated geomagnetic intensity varies with interpolation parameters and with the local geomagnetic disturbance. Results We find that the average absolute error of intensity is − 21.6 nT (95% CI [− 22.26555, − 20.96664]), which is at the lower range of the intensity that animals can sense. The main predictor of error is the level of geomagnetic disturbance, given by the Kp index (indicating the presence of a geomagnetic storm). Since storm level disturbances are rare, this means that our tool is suitable for studies of animal geomagnetic navigation. Caution should be taken with data obtained during geomagnetically disturbed days due to rapid and localised changes of the field which may not be adequately captured. Conclusions By using our new tool, ecologists will be able to, for the first time, access accurate real-time satellite geomagnetic data at the location and time of each tracked animal, without having to start new tracking studies with specialised magnetic sensors. This opens a new and exciting possibility for large multi-species studies that will search for general migratory responses to geomagnetic cues. The tool therefore has a potential to uncover new knowledge about geomagnetic navigation and help resolve long-standing debates.

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A região metropolitana do Rio de Janeiro (RMRJ) é um espaço de grandes transformações que resultam em problemas e impactos ambientais, dentre os quais aqueles relacionados ao clima das cidades. O sensoriamento remoto tem se mostrado útil para mensurar, estimar e avaliar as mudanças e impactos na atmosfera urbana e contribuído para a ciência do clima urbano. As imagens de satélite da plataforma Landsat são aquelas bastante utilizadas para este fim, especialmente quanto à utilização de índices temáticos e estimativa da temperatura.  O objetivo deste trabalho é analisar a evolução do campo térmico e da área urbana na RMRJ, entre 2001 e 2020, através da Temperatura da Superfície Continental (TSC) e do Índice de Área Construída (IBI) extraídos das imagens de satélite Landsat. Foram selecionadas as três cidades mais contrastantes no espaço metropolitano e explorados o campo térmico e a sua área urbana. Os resultados mostram que as áreas urbanas evoluíram e coincidem com os mais elevados valores da TSC, dando espaço à manifestação da Ilha de Calor Urbana (ICU), ao passo que aqueles espaços de área natural sem uso urbano expõe a Ilha de Frescor Urbana (IFU). Muitos espaços na RMRJ continuam seu processo de expansão urbana e, portanto, merecem integrar o conhecimento do clima urbano ao seu planejamento.