Accurate information about the spatiotemporal variability of actual crop evapotranspiration (ETa), crop coefficient (K_c) and water productivity (WP) is crucial for water efficient management in the agriculture. The Earth Engine Evapotranspiration Flux (EEFlux) application has become a popular approach for providing spatiotemporal information on ETa and Kc worldwide. The aim of this study was to quantify the variability of water consumption (ETa) and the K_c for an irrigated commercial planting of soybeans based on the EEFlux application in the western region of the state of Bahia, Brazil. The water productivity (WP) for the fields was also obtained. Six cloud-free images from Landsat 7 and 8 satellites, acquired during the 2016/17 soybean growing season were used and processed on the EEFlux platform. The ETa from EEFlux was compared to that of the modified FAO (MFAO) approach using the following statistical metrics: Willmot’s index of agreement (d-index), root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The K_c from EEFlux was compared to the K_c used in the soybean field (K_c FAO-based) and to the K_c values obtained in different scientific studies using the d-index. A similar procedure was performed for WP. Our results reveal that EEFlux is able to provide accurate information about the variability of ETa and the K_c of soybean fields. The comparison between ETa EEFlux and ETa MFAO showed good agreement based on the d-index, with values of 0.85, 0.83 and 0.89 for central pivots 1, 2 and 3, respectively. However, EEFlux tends to slightly underestimate ETa. The K_c EEFlux showed good accordance with the K_c values considered in this study, except in phase II, where a larger difference was observed; the average WP of the three fields (1.14 kg m^-3) was higher than that in the majority of the previous studies, which is a strong indicator of the efficient use of water in the studied soybean fields. The study showed that EEFlux, an innovative and free tool for access spatiotemporal variability of ETa and Kc at global scale is very efficient to estimate the ETa and Kc on different growth stages of soybean crop.

Fire risk mapping is a basic planning and protection element. This study presents the application of fuzzy logic in a geographic information system (GIS) as an alternative multi-criteria analysis for determining the areas of highest risk of forest fire in natural forest remnants in the Brazil. In the decision-making process, a set of factors that are relevant to fire safety were identified in the study area. For each input variable chosen for the model, a pertinence function was defined that best described its influence on fire risk. Subsequently, the variables were combined for the presentation of the final fire risk map. Concluded in the study that an increased risk of fire occurs at the wildland - urban interface. A strong relationship was observed between the fire ignition points and proximity to roads and urban areas. The proposed model was efficient to integrate the variables and determine areas of greatest risk.

O planejamento e manejo da arborização viária são indispensáveis para o desenvolvimento urbano sustentável e requerem o conhecimento da situação existente. A identificação e a distribuição das espécies florestais presentes nas vias públicas são fundamentais para subsidiar o planejamento adequado da arborização viária. A partir dessas informações, pode-se realizar a caracterização geral do local de interesse e identificar áreas prioritárias para ações de manejo. Dessa maneira, o presente estudo teve como objetivo identificar áreas prioritárias para intervenções na arborização viária de São Pedro do Sul e verificar a influência das espécies vegetais exóticas no índice de diversidade. Realizou-se um censo quantitativo coletando-se informações sobre a posição geográfica das árvores e arbustos e identificação das espécies vegetais. Determinaram-se as frequências para famílias e espécies e calculou-se o índice de Shannon-Wiener (H’) para diversidade de espécies. A espacialização das árvores dentro dos limites dos bairros e vias foi realizada por meio de um mapa de Kernel. Por fim, obteve-se a densidade de indivíduos por quilômetro de via em cada bairro. Foram catalogados 3365 indivíduos, dos quais 98 não foram passíveis de identificação. Registrou-se a presença de 91 espécies, distribuídas em 34 famílias. A família Fabaceae obteve a maior densidade de indivíduos (19,55%). As espécies exóticas concentraram 63,98% da população, sendo a espécie Ligustrum lucidum a mais frequente (15,66%). O município obteve valores médios de 41,18 árvores por quilômetro de via e índice de diversidade de 3,22. O índice de atenção possibilitou identificar os bairros com maiores necessidades de adequação quanto à densidade da arborização viária. O mapa de Kernel possibilitou a visualização da distribuição da arborização viária. Observou-se também que a diversidade de espécies vegetais mensurada em cada bairro está representada essencialmente por espécies vegetais exóticas invasoras e que, à medida que os valores de diversidade aumentam, a composição da arborização com árvores de espécies invasoras se destaca.

The Penman-Monteith method (PM-FAO) is recommended as standard for calculation of reference evapotranspiration (ETo). However, its use requires a series of meteorological variables that is not normally available, restricting its application in many locations. A solution to the problem of unavailability of meteorological data was presented in FAO Bulletin 56, which contains methodologies for estimating wind speed, solar radiation and relative humidity. The objective of the present study was to evaluate the performance of the PM-FAO methodologies for missing data and Hargreaves-Samani as alternatives to the PM-FAO standard method at different time scales and seasons for the municipalities of Linhares and São Mateus, located in the northern region of the state of Espírito Santo. The comparison was performed using linear regression parameters (β₀ and β₁), coefficient of determination, standard error of estimation (SEE) and coefficient of performance. The best alternative to the standard PM-FAO standard method for estimating ETo in the studied area was the Penman-Monteith method with missing wind speed data, since the R² for this method always remained above 0.94 and the confidence coefficient was classified as great, for all seasons and scales. The Hargreaves-Samani method did not present satisfactory performance, with R² below 0.7, regardless of the time scale and time of the year, and it yielded the greatest SEE (1.0 mm d^-1) at spring on a two-day scale. Thus, its use in the northern region of the Espírito Santo state is not recommended.