Space-time analysis of vegetation trends and drought occurrence in domain area of tropical forest.

The purpose of this study is to evaluate temporal trends in changes in vegetation patterns within the Sooretama Biological Reserve and its surroundings, located in Espirito Santo State, Brazil. The evaluation will be performed using the EVI and NDVI index of the MODIS sensor, the Mann-Kendall monotonic trend, Seasonal Trend Analysis methods, and monitoring drought events through the VCI drought index for the years 2007 through 2015. The tools utilized were the EVI and NDVI indexes of the MOD13Q1 product and LST from the MOD11A2 product. These indices were used in order to represent the dynamics of the study area biomass and then to analyze the drought occurrence using the index best-suited to the area of study, identified as VCI. The temporal trends in the data set were examined, pixel by pixel, by application of the Mann-Kendall monotonic technique, treating each pixel in space as a one-dimensional temporal series of 16-day cycles. To evaluate the seasonal trend, the analysis used the STA technique (Seasonal Trend Analysis) implemented in the ETM module. The characterization and spatial distribution of drought events were performed through the Vegetation Condition Index (VCI). The use of (a) images and seasonal curves produced by the monotonic trend of Mann-Kendall and (b) analysis of seasonal trends generated the response of the vegetation to climate variations. The VCI indicated a potential for drought occurrence analysis in regions and areas with different vegetation densities. So, the VCI can be used as a powerful tool to compose a comprehensive and early system alert of drought that can accompany the changes in spatial coverage of vegetation and severity of change. Lastly, the analysis of the data from the MODIS NDVI, EVI, and TST images indicated that the data is suitable to a space-time analysis of drought occurrences and vegetation trends.

Relation of El Niño and La Niña phenomena to precipitation, evapotranspiration and temperature in the Amazon basin.

Weather phenomena El Niño and La Niña are observed by meteorological variables, which allows you to track climate change and its possible effects in certain regions. The objective of this study was to analyze the behavior of rainfall, temperature and evapotranspiration in the Amazon river basin (Latitudes 5° N to 20° S and Longitudes 50° W to 80° W), comparing them with the occurrence of El Niño and La Niña phenomena, from January 2000 to December 2016. The values referring to the meteorological variables were obtained from the TRMM and MODIS orbital sensors. After data pre-processing, the data were separated into monthly and annual scales and per period according to the presence or absence of El Niño and La Niña phenomena. Based on the results obtained, it was observed that the studied variables were affected by modification of both phenomena. The modifications are more noticeable in the distinction between the more and less rainy periods. Among the variables studied, the evapotranspiration was severely affected in the rainiest months, the La Niña phenomenon, and the least rainy months, El Niño. Thus, it was possible to conclude that, in general, the presence of La Niña increased precipitation values in comparison to the Neutral period, but the inverse occurs in the presence of El Niño. The methodology applied in the present study was adequate for the analysis of the modifications of the meteorological variables coming from the El Niño and La Niña phenomena, being able to be adapted to other variables and regions.

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.