Performance and validation of water surface temperature estimates from Landsat 8 of the Itaipu Reservoir, State of Paraná, Brazil.

Studies on water surface temperature (WST) from thermal infrared remote sensing are still incipient in Brazil, and for many water resources, they do not exist. Many algorithms have been developed to estimate surface temperature in satellite images. There are also many difficulties in implementing these algorithms due to their complexity, especially in free software, which restricts the satisfactory processing of these data by users of the technique. Thus, this work aimed to validate an algorithm used to estimate land surface temperature (LST) when applied to the surface of inland water bodies. Water surface temperature estimates (WSTe) were generated from Itaipu State of Paraná (PR) reservoir, Brazil, calculated from Landsat 8 - TIRS satellite images (WSTs) and water surface temperature data from 37 in situ stations (WSTi). A linear regression model of the WSTe was generated in 60% of the samples and its validation with the remaining 40%, subject to prior evaluation of some statistical indicators. The model was considered significant since the coefficient of determination (r2) was 0.90 (95% of confidence), root mean square deviation (RMSD) 0.8 °C, Willmott Index (d) = 0.97, and Nash-Sutcliffe efficiency coefficient (NSE) = 0.89. The methodology used to extract WSTs from the Python QGIS plugin was relatively quick to apply, easy to understand, and had a better performance of the estimates than those presented in the literature review.

The role of spatial mobility in malaria transmission in the Brazilian Amazon: The case of Porto Velho municipality, Rondônia, Brazil (2010-2012).

BACKGROUND: This study aims to describe the role of mobility in malaria transmission by discussing recent changes in population movements in the Brazilian Amazon and developing a flow map of disease transmission in this region. METHODOLOGY/PRINCIPAL FINDINGS: This study presents a descriptive analysis using an ecological approach on regional and local scales. The study location was the municipality of Porto Velho, which is the capital of Rondônia state, Brazil. Our dataset was obtained from the official health database, the population census and an environmental database. During 2000-2007 and 2007-2010, the Porto Velho municipality had an annual population growth of 1.42% and 5.07%, respectively. This population growth can be attributed to migration, which was driven by the construction of the Madeira River hydroelectric complex. From 2010 to 2012, 63,899 malaria-positive slides were reported for residents of Porto Velho municipality; 92% of the identified samples were autochthonous, and 8% were allochthonous. The flow map of patients' movements between residential areas and areas of suspected infection showed two patterns of malaria transmission: 1) commuting between residential areas and the Jirau hydropower dam reservoir, and 2) movements between urban areas and farms and resorts in rural areas. It was also observed that areas with greater occurrences of malaria were characterized by a low rate of deforestation. CONCLUSIONS: The Porto Velho municipality exhibits high malaria endemicity and plays an important role in disseminating the parasite to other municipalities in the Amazon and even to non-endemic areas of the country. Migration remains an important factor for the occurrence of malaria. However, due to recent changes in human occupation of the Brazilian Amazon, characterized by intense expansion of transportation networks, commuting has also become an important factor in malaria transmission. The magnitude of this change necessitates a new model to explain malaria transmission in the Brazilian Amazon.