Contemporary urbanization has been reorganizing the territories and the socioeconomic relations in the Brazilian Amazon as a whole. We seek to identify a general typology of relationships between ...urbanization and deforestation in the Brazilian Amazon, in the light of the environmental Kuznets curve (EKC) theory. We have applied this approach to the 144 municipalities of Pará, in the Brazilian Amazon, in the inter-census interval from 2000 to 2010. The EKC approach included the spatial analysis method of geographically weighted regressions (GWR). Deforestation, measured by the PRODES program by Instituto Nacional de Pesquisas Espaciais (INPE), was used as a measure of environmental degradation and the urbanization has been restricted to a socioeconomic characterizing, based on a set of 22 variables from the national census database, aggregated at the municipalities level. The results showed two main typologies: (1) the decreasing monotonic and (2) "U" shape. The first one indicates municipalities with urban-based economies that have in their income composition an important share of an economy based on the historical structural diversity of the Amazon rural production systems. The second one indicates municipalities with urban-based economies in which the income composition points to an agrarian economy based on rural production systems supported by large, intensified, and homogeneous landscapes that have established a predatory relationship with natural resources. We argue that these two typologies found can be used to establish two city models: "cities of the forest," where it would be possible to combine the local traditional knowledge with scientific and technological advances, mediated by the city life, and "cities in the forest," where the urban-industrial development strategy that has been changing the relationship between society and nature since the 1950s is in place and still very much alive.
The Amazon is Brazil's greatest natural resource and invaluable to the rest of the world as a buffer against climate change. The recent election of Brazil's president brought disputes over ...development plans for the region back into the spotlight. Historically, the development model for the Amazon has focused on exploitation of natural resources, resulting in environmental degradation, particularly deforestation. Although considerable attention has focused on the long-term global cost of "losing the Amazon," too little attention has focused on the emergence and reemergence of vector-borne diseases that directly impact the local population, with spillover effects to other neighboring areas. We discuss the impact of Amazon development models on human health, with a focus on vector-borne disease risk. We outline policy actions that could mitigate these negative impacts while creating opportunities for environmentally sensitive economic activities.
Modeling interactions between social and natural systems is a hard task. It involves collecting data, building up a conceptual approach, implementing, calibrating, simulating, validating, and ...possibly repeating these steps again and again. There are different conceptual approaches proposed in the literature to tackle this problem. However, for complex problems it is better to combine different approaches, giving rise to a need for flexible and extensible frameworks for modeling nature–society interactions. In this paper we present TerraME, an open source toolbox that supports multi-paradigm and multi-scale modeling of coupled human-environmental systems. It enables models that combine agent-based, cellular automata, system dynamics, and discrete event simulation paradigms. TerraME has a GIS interface for managing real-world geospatial data and uses Lua, an expressive scripting language.
•TerraME is a toolbox for modeling and simulation of nature–society interactions.•Novel abstractions and services support multiscale spatiotemporal modeling.•It allows the combined use of several paradigms for model implementation.•It provides an extensible high-level modeling language.•GIS integration supports real-world case studies.
PM2.5 severely affects human health. Remotely sensed (RS) data can be used to estimate PM2.5 concentrations and population exposure, and therefore to explain acute respiratory disorders. However, ...available global PM2.5 concentration forecast products derived from models assimilating RS data have not yet been exploited to generate early alerts for respiratory problems in Brazil. We investigated the feasibility of building such an early warning system. For this, PM2.5 concentrations on a 4-day horizon forecast were provided by the Copernicus Atmosphere Monitoring Service (CAMS) and compared with the number of severe acute respiratory disease (SARD) cases. Confounding effects of the meteorological conditions were considered by selecting the best linear regression models in terms of Akaike Information Criterion (AIC), with meteorological features and their two-way interactions as explanatory variables and PM2.5 concentrations and SARD cases, taken separately, as response variables. Pearson and Spearman correlation coefficients were then computed between the residuals of the models for PM2.5 concentration and SARD cases. The results show a clear tendency to positive correlations between PM2.5 and SARD in all regions of Brazil but the South one, with Spearman’s correlation coefficient reaching 0.52 (p < 0.01). Positive significant correlations were also found in the South region by previously correcting the effects of viral infections on the SARD case dynamics. The possibility of using CAMS global PM2.5 concentration forecast products to build an early warning system for pollution-related effects on human health in Brazil was therefore established. Further investigations should be performed to determine alert threshold(s) and possibly build combined risk indicators involving other risk factors for human respiratory diseases. This is of particular interest in Brazil, where the COVID-19 pandemic and biomass burning are occurring concomitantly, to help minimize the effects of PM emissions and implement mitigation actions within populations.
Dengue is a disease of great complexity, due to interactions between humans, mosquitoes and various virus serotypes as well as efficient vector survival strategies. Thus, understanding the factors ...influencing the persistence of the disease has been a challenge for scientists and policy makers. The aim of this study is to investigate the influence of various factors related to humans and vectors in the maintenance of viral transmission during extended periods.
We developed a stochastic cellular automata model to simulate the spread of dengue fever in a dense community. Each cell can correspond to a built area, and human and mosquito populations are individually monitored during the simulations. Human mobility and renewal, as well as vector infestation, are taken into consideration. To investigate the factors influencing the maintenance of viral circulation, two sets of simulations were performed: (1(st)) varying human renewal rates and human population sizes and (2(nd)) varying the house index (fraction of infested buildings) and vector per human ratio. We found that viral transmission is inhibited with the combination of small human populations with low renewal rates. It is also shown that maintenance of viral circulation for extended periods is possible at low values of house index. Based on the results of the model and on a study conducted in the city of Recife, Brazil, which associates vector infestation with Aedes aegytpi egg counts, we question the current methodology used in calculating the house index, based on larval survey.
This study contributed to a better understanding of the dynamics of dengue subsistence. Using basic concepts of metapopulations, we concluded that low infestation rates in a few neighborhoods ensure the persistence of dengue in large cities and suggested that better strategies should be implemented to obtain measures of house index values, in order to improve the dengue monitoring and control system.
Urbanization has altered the distribution of diseases of public health importance along gradients of human occupation. Adopting dichotomous urban/rural categories to explain differences in the risk ...of exposure, as well as the prevention of diseases is insufficient. In this paper, we present the potential of representations based on the gradient perspective to characterize the living spaces of municipalities where malaria is endemic in northwest Acre. Inventoried data in 40 localities in the Mâncio Lima and Rodrigues Alves municipalities and information on land use and land cover obtained from the TerraClass Database were used to characterize the urban spatial forms and their social content. Results showed a gradient of intensities: from municipal seats to the most connected localities through the road network to riverine communities. Based on the results, we hope to advance the discussion about the use of normative definitions of "urban" and "rural" for public policies and actions to control and eliminate malaria, considering the position of each locality in its own locally referenced urban gradient.
A base de dados do Cadastro Ambiental Rural (CAR), de cadastro autodeclarado, tem sido utilizada para diversas finalidades, entre elas, estudos científicos. Entretanto, como a maior parte dos ...cadastros ainda não foi validada pelos órgãos ambientais competentes, esses dados podem apresentar inconsistências, tais como a sobreposição geométrica entre os imóveis rurais, o que dificulta sua utilização em Sistemas de Informação Geográfica (SIGs), principalmente em operações com maior exigência de ajustes topológicos. Com isso, o artigo apresenta uma proposta metodológica para analisar e remover os diferentes tipos de sobreposições existentes a partir dos dados brutos do Sistema Nacional de Cadastro Ambiental (SICAR). O ponto de partida é a classificação dos imóveis por tamanho, conforme o módulo fiscal do município. Após a remoção dos imóveis cancelados e das geometrias duplicadas, propõese a remoção de sobreposição de imóveis de classes distintas adotando a estratégia de se atribuir a área sobreposta a apenas uma das classes de imóveis, com base em uma hierarquia de classes. O artigo demonstra uma das possibilidades de atribuição de áreas, que prioriza a manutenção dos imóveis de assentamentos rurais, de povos e comunidades tradicionais e imóveis de menor área em detrimento dos de maiores áreas, como alternativa metodológica às estratégias de remoção de sobreposição que levam em consideração a segurança jurídica dos imóveis. Entretanto, a proposta metodológica é adaptável para diferentes contextos e finalidades acadêmicas. Ao final é apresentado um breve estudo de caso utilizando-se a metodologia para os imóveis declarados no município de São José dos Campos, SP.
Recent technological advances in geospatial data gathering have created massive data sets with better spatial and temporal resolution than ever before. These large spatiotemporal data sets have ...motivated a challenge for Geoinformatics: how to model changes and design good quality software. Many existing spatiotemporal data models represent how objects and fields evolve over time. However, to properly capture changes, it is also necessary to describe events. As a contribution to this research, this article presents an algebra for spatiotemporal data. Algebras give formal specifications at a high‐level ion, independently of programming languages. This helps to develop reliable and expressive applications. Our algebra specifies three data types as generic ions built on real‐world observations: time series, trajectory and coverage. Based on these ions, it defines object and event types. The proposed data types and functions can model and capture changes in a large range of applications, including location‐based services, environmental monitoring, public health, and natural disasters.
Access to drinking water is recognized as a human right, meaning that it is necessary to guarantee its universal and equitable access. Since analyzing only the average access rates to drinking water ...may obscure inequalities, studies have adapted socioeconomic inequalities indices to assess disparities. This research evaluated the Safe Drinking Water Access Index (SDWA) and inequalities access in all Brazilian municipalities using microdata from the 2010 Demographic Census. The inequalities were analyzed adapting indices derived from the Lorenz curve (Gini index, concentration coefficient and dissimilarity index). The results showed that the lowest SDWA rates and the highest inequality index values occurred in the north and northeast regions. The municipalities with significant inequality indexes values were rural with reduced gross domestic product (GDP) per capita. It was possible to punctuate municipalities that do not fit these rules but still need attention to safe water access guarantee. The amplitude of inequality index results reveals significant inequalities in the same regions or SDWA ranges. The inequalities in safe drinking water access were made more evident by the adapted Gini Index. This research contributes to the literature with an unprecedented analysis of Brazil and could be adapted to other countries and replicated to assess inequalities in sanitation access.
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•The first ecoregion mapping using Machine Learning for the Amazon.•An ecoregion map is crucial when there are biodiversity information gaps.•14 ecoregions indicating high landscape ...heterogeneity for the Purus-Madeira interfluve.
An ecoregion is a region with similar environmental conditions. However, many ecoregions represent regional habitat heterogeneity, and areas with little fieldwork information can benefit from ecoregion mapping by providing information about their biodiversity distribution. This work presents the procedure adopted to map the terrestrial ecoregions of the Purus-Madeira interfluve, in the Brazilian Amazon using Machine Learning techniques. A methodological approach with Self-Organizing Map and K-means algorithms is proposed for the ecoregion mapping and the resulting model is discussed. The final ecoregion map was built up from a set of variables including altitude, slope, drainage density, percentage of tree cover and a vegetation map. Discriminant analysis identified the extent to which the variables are similar or different between the ecoregions, with a Kappa index of 0.86. This indicates that the methodological approach is reliable and thus can reproduce valid results over different areas. We produced a map with 14 ecoregions to account for the environmental diversity in the Purus-Madeira interfluve. This map can be used for the planning of biodiversity conservation.
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