We applied a robust framework for agricultural drought identification in the State of Espírito Santo, Brazil, by employing the Vegetation Condition Index (VCI) based on data obtained through the Enhanced Vegetation Index (EVI). By doing so, we analyzed the interrelationships between the VCI and anomalies in the Land Surface Temperature (LST), along with connections between the VCI and data considering water deficits in vulnerable areas. When it came to image processing, we focused on the use of analytics and GIS algorithms, while the Scott–Knott method elucidated the statistical analyses. Consequently, we identified drought areas followed by periods susceptible to their occurrence, indicating 2016 as the driest year. The North macroregion presented the lowest average values regarding VCI values in the most vulnerable periods, followed by the Central one. We also call attention to the highest LST averages observed in 2015 and 2016, as strong El Niño events marked the same timeframe periods. The methodological approach was efficient for the identification, analysis, and characterization of agricultural drought occurrences, enabling mitigation actions, as well as the management of the exploitation and protection of water resources. Moreover, further research should be conducted by incorporating other indices to enhance the understanding of agricultural drought and its effects on vegetation.

Environmental vulnerability refers to the susceptibility of a region to damage when it is subjected to natural or anthropogenic actions. The assessment of environmental vulnerability in lakes is an important tool to assist managers in planning and intervening for sustainable production and environmental preservation. The combination of geotechnologies, fuzzy logic and the analytic hierarchy process (AHP) has been applied by professionals and researchers to improve the work and research conducted in various areas and environments. In this context, the objective of this work was to map the environmental vulnerability of a lake and its surroundings through fuzzy logic and the AHP method. The study area comprises the Juparanã Lagoon Drainage Surface (JLDS), Espírito Santo state, Brazil. A survey of the physical characteristics of the watershed (drainage surface) that feeds the Juparanã Lagoon was carried out and also of the land use of this surface. To achieve the proposed objectives, the following methodological steps were implemented: (a) delimitation of watersheds, (b) spatialization of Permanent Preservation Areas (APP) based on the Brazilian Forestry Code (Law nº 12,651/2012), (c) application of logic fuzzy and AHP to spatialize the environmental vulnerability and (d) application of an evaluation of environmental vulnerability to the Preservation Areas (APP). Environmental vulnerability was modeled using Euclidean distance analysis, fuzzy logic and the AHP method, as proposed by Saaty (1977). For the development of this work, geotechnologies were used, with special emphasis on the use of the free software QGIS. The analysis revealed that 31.20%, 32.86% and 20.93% of the JLDS have very high, high and medium vulnerability, respectively. The evaluation of the environmental vulnerability of the APP showed that there is protection in the APP of the JLDS at rates of 47.35%, 34.05% and 14.5% for very high, high and medium vulnerability classes, respectively. The difficulties encountered were related to the lack of studies in the area of environmental vulnerability with a particular focus on lagoons. Here, for the first time, we perform a photointerpretation of the surroundings of Juparanã Lagoon. An important improvement measure would be the application of a temporal analysis to assess the dynamics of environmental vulnerability over time, considering socioeconomic, climatic and environmental changes. This would provide a more complete understanding of the distribution of environmental vulnerability in the study area. The methodology can be adapted to consider different scales of analysis, from local to regional, national and global scales, to assess environmental vulnerability at various scopes and levels of complexity. It can also be adapted to include local communities and governments.

Ecological corridors are effective strategies to address the environmental consequences of forest fragmentation by connecting fragmented areas through various techniques. This study aims to propose the implementation of an ecological corridor in the Itapemirim River basin in Espírito Santo, Brazil. The specific objectives of this study are as follows: delimiting the Permanent Preservation Areas (APPs) in the Itapemirim River watershed and comparing land use and land cover within these areas. The MapBiomas platform and Landsat 8 satellite images were utilized to map land use and land cover, while the criteria set by Law No. 12.651 were followed to define the APP boundaries. The calculation of the landscape ecology indices and the identification of the forest fragments with the highest potential for ecological corridor implementation were conducted using the Fuzzy logic. The QGIS 3.26 application, along with the LecoS 3.0.1 plugin and Fragstats 4.2, were employed to characterize and quantify landscape ecology indices. The costs assessment and determination of the optimal route for implementing the ecological corridor were performed, considering bothdistance and physical impediments. The least cost path algorithm was utilized, taking into account land use and land cover, APP, fragment potential, slope, and subnormal clusters. Evaluating land costs and expropriation expenses required to define the ecological corridor in the study area. The identified forest fragments for inclusion in the ecological corridor were the Caparaó National Park, the Serra das Torres State Natural Monument, and other selected fragments based on the application of Fuzzy logic to landscape ecology indices. The corridor route was determined using the least cost path algorithm, considering various factors. This study revealed that the predominant land use and land cover class in the area is pasture, and a significant portion (68.58%) of the designated Permanent Preservation Areas were in conflict with legal regulations. The bare land value per hectare for pasture was the second highest among the land use and land cover categories, accounting for 64.28% of the total. The priority area analysis indicated that 31.86% of the region had high or very high importance for forest restoration, while 42.97% had low or very low priority. The findings demonstrate that the least cost path algorithm, coupled with a multi-criteria decision-making approach using the Analytic Hierarchy Process (AHP), is a valuable tool for planning and implementing ecological networks. These methods effectively consider critical factors in decision-making processes related to the optimal location of the ecological corridor. In conclusion, this study provides insights into the implementation of an ecological corridor in the Itapemirim River basin, emphasizing the importance of considering multiple factors and utilizing appropriate methodologies for effective decision-making in ecological planning.

Utilizing path analysis, we examined the interconnectedness among six meteorological variables. Among these, three pertain to energy conditions—air temperature, net solar radiation, and reference evapotranspiration (ET0)—while the others are associated with hydrological conditions: precipitation, relative humidity, and water deficiency. These variables were assessed across five distinct temporal delay levels to understand their influences on the normalized difference vegetation Index (NDVI) and enhanced vegetation index (EVI) within grassland areas situated in the state of Espírito Santo, southeastern Brazil. The images underwent processing using analytical algorithms and a geographic information system (GIS). The direct and indirect impacts of these variables on the NDVI and EVI exhibited remarkable similarity across varying temporal delays and geographic regions. Meteorological variables explained over 50% of the observed variation in both indices, occasionally even reaching levels of 70%. Temperature and relative humidity primarily exerted direct effects on the indices. Conversely, precipitation exhibited indirect effects on the indices, often in conjunction with other hydrological variables. ET0 demonstrated a direct effect on the vegetation indices, particularly after a delay of 32 days. Solar radiation and water deficiency displayed direct effects up to the 32-day mark, implying that vegetation responds more promptly to these variables. The proposed methodology enabled a consistent and stable assessment of the direct and indirect effects of meteorological variables on vegetation indices.

The objectives were to analyze the dynamics of land use and land cover of the Amazon biome over time through spatial modeling, and project its future scenario with the Land Change Modeler (LCM) module. This analysis was based on 1985, 2014 and 2017 land cover data from the MapBiomas project, which was associated with socioeconomic explanatory variables based on the Cramer-V test. Results showed that the Forest Formation class occupied 3,844,800.75 km² (91.20%) in 1985, and in 2014, there was a reduction to 3,452,129.25 km² (81.89%). The pasture class had an initial area of 71,046.50 km² (1.69%), and in 2014, there was an expressive increase to 437,670.00 km² (10.38%). The analysis made it possible to verify that Forest Formation and Pastures were the classes that suffered the most changes, followed by the Annual and Perennial Culture and Mosaic of Agriculture and Pasture. The projected land use and coverage for 2044 suggests that there will be a reduction in Forest Formation due to a significant increase in the Pasture class. The simulations foreseen in this work are an important tool that can provide subsidies for supporting territorial planning in the region, public policies, and encouragement of best practices with a reduced impact in pasture areas.

In Brazil, coffee leaf rust (CLR), caused by the fungus Hemileia vastatrix, was first detected in Coffea arabica in January of 1970 in southern Bahia. Now widespread across all cultivation areas, the disease poses a significant threat to coffee production, causing losses of 30–50%. In this context, the objective of this study was to identify and quantify the different classes of occurrence of CLR in areas apt and restricted to the cultivation of Arabica coffee in Brazil for a more informed decision regarding the cultivar to be implanted. The areas of climatic aptitude for Arabica coffee were defined, and then, the climatic favorability for the occurrence of CLR in these areas was evaluated based on climatic data from TerraClimate from 1992 to 2021. The apt areas, apt with some type of irrigation, restricted, and with some type of restriction for the cultivation of Arabica coffee add up to 16.34% of the Brazilian territory. Within this 16.34% of the area of the Brazilian territory, the class of climatic favorability for the occurrence of CLR with greater representation is the favorable one. Currently, the disease is controlled with the use of protective and systemic fungicides, including copper, triazoles, and strobilurins, which must be applied following decision rules that vary according to the risk scenario, and according to the use of resistant cultivars. This study provides a basis for choosing the most suitable cultivars for each region based on the degree of CLR resistance.