Spectro-temporal analysis of the Paraopeba River water after the tailings dam burst of the Córrego do Feijão mine, in Brumadinho, Brazil.

Remote sensing is an important tool for environmental assessment, especially in the event of disasters such as the tailings dam burst at the Córrego do Feijão mine, located in the Paraopeba River basin, Brazil. Thus, this study aimed to carry out a spectro-temporal analysis of the Paraopeba River water given the dam burst, using multispectral images from the MSI sensor onboard Sentinel-2 satellites. For this analysis, sections along the river were defined by the creation of buffers, with 10-km intervals each, starting from the origin of the burst. For each section, the average visible to near-infrared (NIR) reflectance values per band and the Normalized Difference Water Index (NDWI) were obtained. We found that the red edge and NIR bands (B5, B6, B7, B8, and B8A) showed higher reflectance values when compared to the visible bands in the months immediately after the disaster, especially in the first 20 km. In these months, negative NDWI values were also found for almost all sections downstream, demonstrating the large volume of mining tailings in the Paraopeba River. The seasonal variation of the observed values indicates the resuspension of the material deposited at the river bottom with the beginning of the rainy season. Finally, we highlight the usefulness of the MSI/Sentinel-2 red edge and NIR bands for further studies on the monitoring from space of water bodies subjected to contamination by large amounts of mud with iron ore tailings and contaminants, as occurred in the state of Minas Gerais, southeastern Brazil.

Wildfires as a major challenge for natural regeneration in Atlantic Forest.

The natural regeneration management is a good strategy of ecological restoration of the Atlantic Forest, one of the most devastated biomes on the planet. However, the frequent occurrence of wildfires is one of the challenges to the success of this method. The objective of this study was to evaluate the effects of wildfires on forest dynamics in Atlantic Forest. The studied area was explored during the coffee cycle when plantations replaced primary forests. We used remote sensing data to analyze the forest dynamics over a period of 50 years (1966-2016). We used the INPE burn database to find the occurrence of hot spots from 1998 to 2016. During this period, we selected the years most affected by the fires for the identification of fire scars using the Normalized Burn Ratio spectral index. From this set of information, we used the methodology of weights of evidence to relate forest dynamics and wildfire events with biophysical and anthropic variables. The results showed that in 1966 the forest area accounted for 8.01% of the land cover, and in 2016 this number rose to 18.55% due to the spontaneous natural regeneration process. The regenerating areas were mainly related to the proximity of the remaining fragments and the portions of the landscape receiving the least amount of global solar radiation. The proximity to urban areas, roads and highways, damaged regeneration and favored both deforestation and wildfire events. Fire scars preferentially occur where there is greater sun exposure. It is possible to observe a negative correlation between the natural regeneration process and the fire scars. We concluded that fire severity is one of the factors that shape the landscape of the region while slowing the regeneration process in preferential areas.

Potentials and limitations of remote fire monitoring in protected areas.

Protected areas (PAs) play an important role in maintaining the biodiversity and ecological processes of the site. One of the greatest challenges for the PA management in several biomes in the world is wildfires. The objective of this work was to evaluate the potentialities and limitations of the use of data obtained by orbital remote sensing in the monitoring fire occurrence in PAs. Fire Occurrence Records (FORs) were analyzed in Serra do Brigadeiro State Park, Minas Gerais, Brazil, from 2007 to 2015, using photo interpreted data from TM, ETM+ and OLI sensors of the Landsat series and the Hot Spot Database (HSD) from the Brazilian Institute of Space Research - INPE. It was also observed the time of permanence of the scar left by fire on the landscape, through the multitemporal analysis of the behavior of NDVI (Normalized Difference Vegetation Index) and NBR (Normalized Burn Ratio) indexes, before and after the occurrence. The greatest limitation found for the orbital remote monitoring was the presence of clouds in the passage of the sensor in dates close to the occurrence of the fires. The burned area identified by photo interpretation was 54.9% less than the area contained in the FOR. Although the HSD reported fire occurrences in the buffer zone (up to 10km from the Park), no FORs were found at a distance greater than 1100m from the boundaries of the PA. As the main potential of remote sensing, the possibility of identifying burned areas throughout the park and surroundings is highlighted, with low costs and greater accuracy.

Spatial and temporal distribution of urban heat islands.

The formation of an urban heat island (UHI) is one of the most common impacts of the urbanization process. To mitigate the effects of UHI, the planning of urban forests (e.g., creation of parks, forests and afforestation streets) has been the major tool applied in this context. Thus, the aim of this study is to evaluate the spatial and temporal distribution of heat islands in Vila Velha, ES, Brazil using the mono-window algorithm. The study followed these methodological steps: 1) mapping of urban green areas through a photointerpretation screen; 2) application of the mono-window algorithm to obtain the spatial and temporal patterns of land surface temperature (LST); 3) correlation between LST and the normalized difference vegetation index (NDVI) and normalized difference build-up index (NDBI); 4) application of ecological evaluation index. The results showed that the mean values of LST in urban areas were at least 2.34 to 7.19°C higher than undeveloped areas. Moreover, the positive correlation between LST and NDBI showed an amplifying effect of the developed areas for UHI, while areas with a predominance of vegetation attenuated the effect of UHI. Urban centers, clustered in some parts of the city, received the worst ecological assessment index. Finally, the adoption of measures to guide the urban forest planning within urban centers is necessary to mitigate the effect of heat islands and provide thermal comfort in urban areas.