Allocation of water reservoirs to fight forest fires according to the risk of occurrence.

Although forest fires are indispensable for some ecosystems, they can have profound economic, environmental, and social implications, especially when they reach high intensities. There are two crucial factors in fighting forest fires: the availability of water resources and the service network. The objective of this study was to propose an alternative methodology for allocating water reservoirs to fight forest fires. The research was divided into three stages: zoning of fire risk, delimitation of viable areas for the implementation of water reservoirs, and determining strategic locations for reservoir allocation. The variables analyzed were land use and occupation, provision of watercourses, relief orientation, slope, proximity to roads, temperature, and precipitation. Fuzzy logic, Euclidean distance, and network analysis were used as the modeling techniques. Scenarios with all risk classes and only the high- and very high-risk classes were analyzed. A total of 66% of the area was represented by the low- and moderate-risk fire classes and 53.16% had a low potential for reservoir allocation, influenced by the low availability of water resources in the area. The proposed model efficiently allocated the water collection points in the different scenarios, and allowed the determination of the areas most susceptible to the occurrence of forest fires and the optimal locations for the installation of reservoirs, with the allocation of 21 water reservoirs to attend the areas of high- and very high-risk of occurrence of fires at a safe speed (40 km h-1) and 47 reservoirs to meet all risk classes at the same speed. The proposed methodology is feasible, applicable, and adjustable and can be implemented in other conservation units and areas of economic interest.

Environmental risk assessment for sustainable pesticide use in coffee production.

The extensive use of pesticides in agricultural practices has been associated with human health problems and environmental contamination worldwide. Brazil is the largest consumer of pesticides in the world and Espírito Santo State stands out as the second Brazilian producer of coffee. However, there is no information about environmental impact of coffee producing at Itapemirim River Basin (IRB) region, Espírito Santo State, Brazil; hence a simple and quick method using open access softwares (AGROSCRE and ARAquá Web) to estimate surface entrainment and pesticide leaching potential was carried out. AGROSCRE evaluates the contamination risk of superficial and groundwater by Active Ingredients (AIs), using GOSS Method, GUS index and US EPA criteria, while ARAquá Web estimates AI concentrations in water resources, indicating their suitability based on water quality requirements for different uses. Regarding pesticides used in coffee plantations, there is 44.7% chance of surface water and 23.7% chance of groundwater contamination. Results showed that ametryne, cyproconazole, diuron, epoxiconazole, flutriafol, triadimenol and triazophos pose contamination risk to both surface water and groundwater in the IRB region. Of these, 10.5% of the total AIs are triazoles and fall under environmental classes II and III (Product Very/Dangerous to the Environment). The AIs ametryne, thiamethoxam, iprodione, flutriafol, triazophos, endosulfan, triadimenol, cyproconazole, diuron, pendimethalin, chlorpyrifos, copper II hydroxide, etion, epoxiconazole and paraquat dichloride, were found to be potentially toxic, presenting environmental concentrations ranging from 123.40 µg L-1 to 0.14 µg L-1, which are higher than the safety standard for potable water (0.1 µg L-1). With respect to these AIs, chlorpyrifos, ethion and triazophos showed concentrations higher than EC50 values for aquatic invertebrates and ametryne and diuron for algae. Thus, local residents and environment may be at high risk of pesticide exposure, when these AIs are used in coffee plantations next to surface water or groundwater.

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.

Fuzzy logic applied to prospecting for areas for installation of wood panel industries.

Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops.

GIS applied to location of fires detection towers in domain area of tropical forest.

In most countries, the loss of biodiversity caused by the fires is worrying. In this sense, the fires detection towers are crucial for rapid identification of fire outbreaks and can also be used in environmental inspection, biodiversity monitoring, telecommunications mechanisms, telemetry and others. Currently the methodologies for allocating fire detection towers over large areas are numerous, complex and non-standardized by government supervisory agencies. Therefore, this study proposes and evaluates different methodologies to best location of points to install fire detection towers considering the topography, risk areas, conservation units and heat spots. Were used Geographic Information Systems (GIS) techniques and unaligned stratified systematic sampling for implementing and evaluating 9 methods for allocating fire detection towers. Among the methods evaluated, the C3 method was chosen, represented by 140 fire detection towers, with coverage of: a) 67% of the study area, b) 73.97% of the areas with high risk, c) 70.41% of the areas with very high risk, d) 70.42% of the conservation units and e) 84.95% of the heat spots in 2014. The proposed methodology can be adapted to areas of other countries.