O estudo da susceptibilidade a erosão laminar é pertinente na mesorregião da Zona da Mata de Minas Gerais, visto a predominância da cobertura de pastagem e pela expressiva degradação do solo. Neste estudo, objetivou-se compreender quais variáveis geodinâmicas são importantes na predição dos processos erosivos laminares e o melhor modelo preditivo entre oito, através de comparações multicritérios, possibilitando entender o fenômeno em uma bacia hidrográfica da mesorregião. Assim, utilizou-se o método de atribuição de notas pela Literatura (L) e Realidade de campo (RC), cuja ponderação de parcela dos processos erosivos (60%) laminares mapeados ponderou a nota das classes das variáveis pela área das mesmas. A integração das variáveis foi por testes de ponderação e integração total e parcial. A avaliação dos modelos gerados foi por estatística descritiva (Box-Plot), diferentes métodos de categorização (Manual, Natural Breaks e Geometrical Interval) e curva ROC com cálculo de eficiência AUC (40% das erosões mapeadas). Os resultados apontaram que a falta umidade é um fator importante para a ocorrência dos processos erosivos laminares, por outro lado, as variáveis morfométricas não foram importantes para a predição. Modelos baseados na RC (72,41% AUC médio) obteve eficiência consideravelmente maior do que a L (65,41% AUC médio), já quando comparado a integração de todas as variáveis geodinâmicas e somente as mais importantes e quando integrado com ponderação e sem ponderação, não houve considerável diferença estatística. O modelo mais eficiente obteve 76,3% AUC, considerado boa e estava adequado a realidade da área estudada. Study of Susceptibility to Sheet Erosion in a Watershed in Zona da Mata, Minas Gerais, BrazilABSTRACTThe study of susceptibility to surface erosion is relevant in the mesoregion of the Zona da Mata of Minas Gerais, given the predominance of pasture cover, the significant degradation of the soil and the stagnation of the agricultural sector. In this study, the objective was to understand which geodynamic variables are important in the prediction of surface erosive processes and the best predictive model among eight, through multicriteria comparisons, making it possible to understand the phenomenon in a watershed in the mesoregion. Thus, it was used the method of attributing grades by Literature (L) and Field Reality (RC), whose weighting of the mapped surface erosive (60%) processes weighted the grade of the variable classes by their area. The integration of the variables was through weighting tests and total and partial integration. The evaluation of the models generated was by descriptive statistics (Box-Plot), different methods of categorization (Manual, Natural Breaks and Geometrical Interval) and ROC curve with AUC efficiency calculation (40% of the mapped erosions). The results showed that the lack of moisture is an important factor for the occurrence of surface erosive processes, on the other hand, the morphometric variables were not important for the prediction. Models based on RC (72.41% average AUC) achieved considerably greater efficiency than L (65.41% average AUC), when compared to the integration of all geodynamic variables and only the most important ones and when integrated with weighting and without weighting, there was no considerable statistical difference. The most efficient model obtained 76.3% AUC, considered good and was adequate to the reality of the studied area.Key words: Geotechnologies; Comparison of Risk Models; Multicriteria Analysis
Among the various environments present on the planet that deserve due attention, as they have particularities and specificities of chemical, physical and biological orders, mangroves stand out. These ecosystems are mostly located in the intertropical zones where continental and oceanic waters meet, being crucial for a great diversity of animal species that find, in it, conditions that allow them to live and reproduce. In addition, this ecosystem is also for many local residents, such as traditional fishermen and crab farmers, a place for income generation, thus assuming an important socio-economic function. In addition, mangroves, through vegetation, help to protect the coast and act as important carbon sequestrants and stores. Among the less invasive methodologies that make it possible to analyze a series of dynamics of this environment, reducing costs with the field and the risks inherent to its natural characteristics, Remote Sensing stands out. Therefore, the general objective of this research was to evaluate the effectiveness of the NDVI, SAVI and LAI vegetation indices in recording the consequences of an extreme climatic event that occurred on June 1, 2016, in the mangroves of the Reserva de Desenvolvimento Sustentável Municipal Piraquê Açu-Mirim, located in Aracruz (ES), Southeast Coast Brazil. To achieve the objective, time series between February 2016 (before the event) and December 2020 were used. The results, which include maps and statistical graphs, allowed the delimitation of areas according to the intensities of the impacts and their consequences on the vegetation. While the vegetation of Piraquê-Açu underwent regeneration processes in all affected areas, in Piraquê-Mirim the area with the greatest impact remained destroyed. Given the socio-environmental importance of mangroves, it is necessary to implement projects aimed at their recovery. Both the methodology and the indices were efficient to achieve the objectives and can be reproduced in other mangroves.
Created in 2014, the Serra da Gandarela National Park (SGNP), is repeatedly affected by wildfires. This Conservation Unit is located in the Iron Quadrangle (MG), in a transition zone between the Cerrado and the Atlantic Forest biomes, and is characterized by a complex mosaic of phytophysiognomies. The aim of this investigation was to compare the performance of two risk mapping models for forest fire in the SGNP and its surroundings, based on two different approaches, being one by multicriteria analysis, AHP method and the other a simple probability method, called Hot Spot History, which provided information on the areas of highest and lowest risk and their environmental and human characteristics. Spatial data from remote sensing and GIS were used to simulate, in sequence, the fire ignition, the fire spread and, finally, the risk of wildfire. The validation of the risk models was performed by the Kappa coefficient (K). The results showed that the model based on the History of Hot Points obtained greater accuracy (0.61) than the model generated by the AHP method (0.54). The Brazilian Savanna, Rupestrian Fields and Field coverings were the most susceptible to wildfire, as they are formed by herbaceous vegetations and are located very close to urban agglomerations and roads. The slopes oriented to the North and West were important for the prediction of wildfires slope and, on the other hand, the slope of the terrain was not important to discretize the areas of greater and lesser fragility to the referred ecological disturbance.
O presente artigo busca analisar as paralisações de caminhoneiros no Brasil, sob uma perspectiva socioespacial, conferindo ênfase à circulação de mercadorias e, mais especificamente, da dependência do país em relação ao transporte rodoviário. O que nos levou a considerar o papel fundamental desempenhado por tecnologias comunicacionais no processo de mobilização desse segmento de trabalhadores, destacando-se a utilização do aplicativo WhatsApp. A pesquisa salienta, ainda, os impactos do movimento nos diversos setores da economia. Nos valemos, nesse sentido, de dados de associações dos setores envolvidos, além de notícias divulgadas nos meios de comunicação nacionais e internacionais.
Dentre os variados ambientes presentes no planeta, que merecem a devida atenção, por possuírem particularidades e especificidades de ordens químicas, físicas e biológicas, faz-se um destaque para os manguezais. Os manguezais são ecossistemas tropicais localizados em locais específicos das planícies costeiras onde há o encontro de águas continentais e oceânicas. São fornecedores de diversos serviços ecossistêmicos, que variam da escala local à global. Devido a sua localização e especificidade esses ecossistemas também se colocam numa posição de fragilidade e, portanto, sensíveis às mudanças bruscas como, por exemplo, as causadas por alterações significativas das condições de tempo e clima, que também podem estar relacionadas ao aquecimento global. Diante disso, essa pesquisa teve como objetivo geral avaliar a eficácia dos índices Normalized Difference Vegetation Indexd (NDVI), Soil-adjusted vegetation índex (SAVI), Leaf area index (LAI), CO 2 flux, Normalizeed Difference Watter Index (NDWI) e Land Surface Temperature (LST) no registro das consequências do evento climático extremo, tempestade de granizo, ocorrido no dia 1 de junho de 2016 nos mangues da Reserva de Desenvolvimento Sustentável Municipal Piraquê Açu-Mirim, localizada em Aracruz (ES) no Brasil. Para isso, foi utilizado imagens de sensores orbitais para o período de 2015 e 2020 de modo a fazer comparações entre o antes e o depois do evento. Os resultados são compostos tanto por mapas temáticos de cada índice como, também, por gráficos de estatística descritiva, que foram gerados a partir de pontos amostrais. Desse modo, após gerar esses produtos fez-se investidas a campo com o intuito de verificar se os resultados obtidos com os índices eram correlatos com a realidade dos locais. Esse processo, foi fundamental para o escopo da pesquisa, pois além de confirmar a capacidade dos índices em registrar o impacto, em diferentes graus (menor, média e maior), possibilitou identificar quais índices obtiveram maior precisão. Palavras-chave: Manguezais. Índices de vegetação. Ecossistema costeiro. Sensoriamento remoto. Mudança na paisagem.
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