Adriano Bressane

USE OF SELF-ORGANIZING MAPS IN THE IDENTIFICATION OF DIFFERENT GROUPS OF RECLAMATION SITES IN THE AMAZON FOREST-BRAZIL

Brazil has the third largest reserve of contained tin, around 12.3% of the amount produced in world, being a large part of these reserves located in the Amazon region. As a result of this mineral wealth, the Amazonian ecosystem has been suffering a rapid process of environmental degradation since the sixties. In this sense, given the mining adverse consequences to the environment, Brazilian Constitution obligate the land reclamation of degraded areas by mining and it has been performed by the majority of the mining companies. However, given the environment complexity and its relationship with the biological diversity, there is a great necessity of better understanding in assessment of evolution of these degraded areas in recovery. Thus, the present work had as objective identifying different groups of degraded areas in reclamation process by means of soil texture, biochemistry and vegetation indicators. The data was analyzed through Artificial Neural Networks (ANN) Self Organizing Maps (SOMs). The results showed four different groups and it was identified a relationship between the different textures soils as a result to the recovery method applied.

A system for evaluating the impact of noise pollution on the population's health

Abstract The aim of this study was to develop a support sys-tem for the evaluation of noise pollution, applied to the central urban area of Rio Claro, Sao Paulo State, Brazil. Data were obtained from noise measurements and interviews with the population, generating the following indicators: equivalent sound level ( L eq ), traf-fic noise index ( L TNI ), and a participatory diagnosis ( D p ), integrated through a fuzzy inference system ( FIS ). The proposed system allowed classifying the measure-ment points according to the degree of impact of noise pollution on the population’s health ( I PS ) in the study area. Impact was considered significant in 31.4% of the measurement points and very significant in 62.9%. The FIS can be adjusted to local conditions, allowing generalization and thus also supporting noise pollu-tion evaluation and respective environmental noise management in other geographic areas.Fuzzy Logic; Sound Contamination; Noise Effects Resumen El objetivo del trabajo fue desarrollar un sistema de apoyo a la evaluacion de la contaminacion acustica, aplicado en la zona central de Rio Claro, Sao Paulo, Brasil. Con este fin, se obtuvieron datos mediante me-diciones sonoras y entrevistas a la poblacion, generan-do como indicadores el nivel sonoro equivalente (O objetivo do trabalho foi desenvolver um sistema de apoio a avaliacao da poluicao sonora, aplicado na zona central de Rio Claro, Sao Paulo, Brasil. Para isso, dados foram obtidos por meio de medicoes sonoras e entrevistas com a populacao, gerando como indicadores o nivel sonoro equivalente (Leq ), o indice de ruido de trafego (LTNI ) e um diagnostico participativo (Dp ), integrados por intermedio de um sistema de inferencia fuzzy (SIF). Como resultado, o sistema proposto permitiu classificar os pontos avaliados quanto ao grau de impacto da poluicao sonora sobre a saude da populacao (IPS ) na area de estudo, que pode ser considerado significativo em 31,4% dos pontos e muito significativo em 62,9%. A possibilidade de adequar o SIF de acordo com as condicoes de estudo viabiliza a sua generalizacao e, desta forma, apoia a avaliacao e respectiva gestao do ruido ambiental em outras regioes.The aim of this study was to develop a support system for the evaluation of noise pollution, applied to the central urban area of Rio Claro, São Paulo State, Brazil. Data were obtained from noise measurements and interviews with the population, generating the following indicators: equivalent sound level (Leq ), traffic noise index (LTNI ), and a participatory diagnosis (Dp ), integrated through a fuzzy inference system (FIS). The proposed system allowed classifying the measurement points according to the degree of impact of noise pollution on the populations health (IPS ) in the study area. Impact was considered significant in 31.4% of the measurement points and very significant in 62.9%. The FIS can be adjusted to local conditions, allowing generalization and thus also supporting noise pollution evaluation and respective environmental noise management in other geographic areas.

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year. Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

Pattern recognition in trunk images based on co-occurrence descriptors: A proposal applied to tree species identification

Tree species identification is required for many applications. However, current techniques are dependent on the presence of morphological structures such as leaves, which restricts its use in certain situations and seasons. In this context, the use of trunk images can be an alternative. Therefore, the present study developed a pattern recognition based on co-occurrence descriptors, aiming evaluate its performance in the identification of 8 tree species from the Brazilian deciduous native forest, achieving promising results, with precision better than 0.8 for most of them, accuracy equivalent to 0.77 and average area under curve by Receiver Operating Characteristic of 0.88, during the tests with cross-validation sets.

A New Methodology for Application of Impact’s Identification Using Fuzzy Relation

The Environmental Impact Assessment (EIA) is a mechanism used by governments and private institutions to predict environmental damage and optimize positive impacts. One of the greatest challenges of the EIA process is to achieve an effective integration of the various tools and the analytical procedures. This paper proposes a new methodology for the application of impact’s identification and characterization matrices by the use of Fuzzy Logic, using specifically Fuzzy Relations Theory. Three Weight Matrices of State and Association, for each type of expertise (physical, biotic, and anthropic) were created. Fuzzy Relations to aggregate all these matrices were used, and a Weighted Response Matrix was obtained. The developed fuzzy methodology was applied to real cases of EIA, aiming to compare the results. The EIA Mario Covas Road Program—Modified Southern Section was used, and the fuzzy interaction matrix proves to be a successful tool. Because of the results, it was possible to infer that the new methodology, using fuzzy approach is an effective and practical tool in the Environmental Impact Assessment.

NEURO-FUZZY MODELING: A PROMISING ALTERNATIVE FOR RISK ANALYSIS IN URBAN AFFORESTATION MANAGEMENT

1 Received on 04.11.2016 accepted for publication on 12.12.2017. 2 Universidade Estadual Paulista, Departamento de Engenharia Ambiental, São José dos Campos, SP Brasil. E-mail: <adrianobressane@ymail.com> and <adriano.bressane@ict.unesp.br>. 3 Prefeitura Municipal de Nova Prata, Nova Prata, RS Brasil. E-mail: <florestal@novaprata.gov.br>. 4 Universidade Estadual Paulista, Campus de Sorocaba, Sorocaba, São Paulo Brasil. E-mail: <carloshbiagolini@ig.com.br>. 5 Universidade Estadual Paulista, Departamento de Engenharia Ambiental, Sorocaba, SP-Brasil. E-mail: <roveda@sorocaba.unesp.br> and <sandra@sorocaba.unesp.br>. 6 Universidade Católica de Campinas, Faculdade de Engenharia Ambiental, Campinas, SP Brasil. E-mail: <felipe_fengler@hotmail.com>. *Corresponding author.

Geo-environmental zoning using physiographic compartmentalization: a proposal for supporting sustainable decision-making

The geo-environmental zoning represents an important strategy in the territorial management. However, it requires a logical and structured procedure. Therefore, an approach using physiographic compartmentalization is proposed and applied as case study in a region covered by the topographic maps of São José dos Campos and Jacareí, Brazil. This region has great geological and geomorphological peculiarities, beyond being a place with large human interventions because of its quickly economic growth. The methodology is based on photointerpretation techniques and remote sensing in GIS environment. As a result, seven geo-environmental zones were obtained from a weighted integration by multicriteria analysis of physiographic units with land-use classes. In conclusion, taking into account potentialities and limitations, the proposed approach can be considered able to support sustainable decision-making, being applicable in other regions.

SISTEMA DE APOIO À GESTÃO DE ÁREAS VERDES NA PRESERVAÇÃO PERMANENTE DE CORPOS HÍDRICOS URBANOS

The conservation of urban green areas is among the key strategies for achieving healthy and sustainable cities. However, the multiplicity of the involved factors requires an integrated analysis by means of a logical and structured procedure. Therefore, this article aims to present the proposal for a decision support system for the management of green areas in public domain, in areas of permanent preservation of urban water bodies. For its development, guidelines of the plannning method through scenarios were adopted, by which the aspects related to the problem and routing solutions were analysed. The main used materials correspond to the works of technical literature and legislation, raised through search terms along with bibliographic and legislative seats. From the analysis of these materials, we studied the actual functions of these areas of permanent preservation and the factors affecting their performance and protection. As a result, we obtained a structured model in key decision for the selection of the location alternatives and their function-space capability.

Sistema de apoyo a la evaluación del impacto del ruido sobre la salud pública

Abstract The aim of this study was to develop a support sys-tem for the evaluation of noise pollution, applied to the central urban area of Rio Claro, Sao Paulo State, Brazil. Data were obtained from noise measurements and interviews with the population, generating the following indicators: equivalent sound level ( L eq ), traf-fic noise index ( L TNI ), and a participatory diagnosis ( D p ), integrated through a fuzzy inference system ( FIS ). The proposed system allowed classifying the measure-ment points according to the degree of impact of noise pollution on the population’s health ( I PS ) in the study area. Impact was considered significant in 31.4% of the measurement points and very significant in 62.9%. The FIS can be adjusted to local conditions, allowing generalization and thus also supporting noise pollu-tion evaluation and respective environmental noise management in other geographic areas.Fuzzy Logic; Sound Contamination; Noise Effects Resumen El objetivo del trabajo fue desarrollar un sistema de apoyo a la evaluacion de la contaminacion acustica, aplicado en la zona central de Rio Claro, Sao Paulo, Brasil. Con este fin, se obtuvieron datos mediante me-diciones sonoras y entrevistas a la poblacion, generan-do como indicadores el nivel sonoro equivalente (O objetivo do trabalho foi desenvolver um sistema de apoio a avaliacao da poluicao sonora, aplicado na zona central de Rio Claro, Sao Paulo, Brasil. Para isso, dados foram obtidos por meio de medicoes sonoras e entrevistas com a populacao, gerando como indicadores o nivel sonoro equivalente (Leq ), o indice de ruido de trafego (LTNI ) e um diagnostico participativo (Dp ), integrados por intermedio de um sistema de inferencia fuzzy (SIF). Como resultado, o sistema proposto permitiu classificar os pontos avaliados quanto ao grau de impacto da poluicao sonora sobre a saude da populacao (IPS ) na area de estudo, que pode ser considerado significativo em 31,4% dos pontos e muito significativo em 62,9%. A possibilidade de adequar o SIF de acordo com as condicoes de estudo viabiliza a sua generalizacao e, desta forma, apoia a avaliacao e respectiva gestao do ruido ambiental em outras regioes.The aim of this study was to develop a support system for the evaluation of noise pollution, applied to the central urban area of Rio Claro, São Paulo State, Brazil. Data were obtained from noise measurements and interviews with the population, generating the following indicators: equivalent sound level (Leq ), traffic noise index (LTNI ), and a participatory diagnosis (Dp ), integrated through a fuzzy inference system (FIS). The proposed system allowed classifying the measurement points according to the degree of impact of noise pollution on the populations health (IPS ) in the study area. Impact was considered significant in 31.4% of the measurement points and very significant in 62.9%. The FIS can be adjusted to local conditions, allowing generalization and thus also supporting noise pollution evaluation and respective environmental noise management in other geographic areas.

Sistema de apoio à avaliação de impactos da poluição sonora sobre a saúde pública

Abstract The aim of this study was to develop a support sys-tem for the evaluation of noise pollution, applied to the central urban area of Rio Claro, Sao Paulo State, Brazil. Data were obtained from noise measurements and interviews with the population, generating the following indicators: equivalent sound level ( L eq ), traf-fic noise index ( L TNI ), and a participatory diagnosis ( D p ), integrated through a fuzzy inference system ( FIS ). The proposed system allowed classifying the measure-ment points according to the degree of impact of noise pollution on the population’s health ( I PS ) in the study area. Impact was considered significant in 31.4% of the measurement points and very significant in 62.9%. The FIS can be adjusted to local conditions, allowing generalization and thus also supporting noise pollu-tion evaluation and respective environmental noise management in other geographic areas.Fuzzy Logic; Sound Contamination; Noise Effects Resumen El objetivo del trabajo fue desarrollar un sistema de apoyo a la evaluacion de la contaminacion acustica, aplicado en la zona central de Rio Claro, Sao Paulo, Brasil. Con este fin, se obtuvieron datos mediante me-diciones sonoras y entrevistas a la poblacion, generan-do como indicadores el nivel sonoro equivalente (O objetivo do trabalho foi desenvolver um sistema de apoio a avaliacao da poluicao sonora, aplicado na zona central de Rio Claro, Sao Paulo, Brasil. Para isso, dados foram obtidos por meio de medicoes sonoras e entrevistas com a populacao, gerando como indicadores o nivel sonoro equivalente (Leq ), o indice de ruido de trafego (LTNI ) e um diagnostico participativo (Dp ), integrados por intermedio de um sistema de inferencia fuzzy (SIF). Como resultado, o sistema proposto permitiu classificar os pontos avaliados quanto ao grau de impacto da poluicao sonora sobre a saude da populacao (IPS ) na area de estudo, que pode ser considerado significativo em 31,4% dos pontos e muito significativo em 62,9%. A possibilidade de adequar o SIF de acordo com as condicoes de estudo viabiliza a sua generalizacao e, desta forma, apoia a avaliacao e respectiva gestao do ruido ambiental em outras regioes.The aim of this study was to develop a support system for the evaluation of noise pollution, applied to the central urban area of Rio Claro, São Paulo State, Brazil. Data were obtained from noise measurements and interviews with the population, generating the following indicators: equivalent sound level (Leq ), traffic noise index (LTNI ), and a participatory diagnosis (Dp ), integrated through a fuzzy inference system (FIS). The proposed system allowed classifying the measurement points according to the degree of impact of noise pollution on the populations health (IPS ) in the study area. Impact was considered significant in 31.4% of the measurement points and very significant in 62.9%. The FIS can be adjusted to local conditions, allowing generalization and thus also supporting noise pollution evaluation and respective environmental noise management in other geographic areas.