17 research outputs found
Environmental system modeling and landscape management
Environmental system modeling and landscape managemen
Analysis of Freight Trip Generation Model for Food and Beverage in Belo Horizonte (Brazil)
Today, one of the main challenges faced in urban logistics is the distribution of goods. In Brazil, mid to large cities have experienced consequences of unplanned urban sprawl and lack of adequate transportation infrastructure. The relationship between urban planning and transport stands out the attractiveness of some urban activities with direct impacts on the movement of people and goods and other component elements of urban space. The segment of bars and restaurants falls within this context, therefore is a vital activity responsible for significant percentage of jobs and revenue in a city. Altogether, foods & beverages commercial activities move daily large volumes of goods to meet the need of customers. This paper presents the results of a freight trip generation model developed for pubs and restaurants in Belo Horizonte (Brazil). Once performed the model determined the number of trips generated per day per establishment. In order to expand the discrete result to a continuous one, the results were geographically interpolated to a continuous surface and extrapolated within the city limits. The data for the freight trip generation model were obtained by survey. For this, we designed a structured questionnaire to obtain information about goods, frequency, operational time, place of performance of the loading/unloading of goods, establishment size and the number of employees. Besides these information, we investigated the acceptance of alternative practices in the delivery of goods, such as off-peak delivery. To accomplish the proposed models, we applied a simple linear regression, correlating the following variables: (i) Number of trips versus area of the establishment; (ii) Number of trips versus number of employees; (iii) Number of trips versus operation day of the establishment. With the results of the linear regression for travel generations, conducted the data interpolation based on the standard deviation of the results to define the sample classification bands. This interpolation method was chosen because it is one of the most suitable for analysis of spatially scattered points due to the straightforwardness of the model and because it does not consider extra noise such as slope and spatial constraints as barriers. In this method, interpolation is determined by the value assigned to each point (in this case the number of trips), wherein the closer the points the higher the correlation trend. Finally, the resulting trip generation surface was analysed together with other geographic data such as demographic data, road network density and socioeconomic data. Findings indicate the importance of a mathematic-geographic model for trip generation as a feasible approach for support transportation planning & operation for urban goods distribution. Critical information such as the high concentration of pubs and restaurants in the same region can reinforce the vocation of the city for trading. However, an elevated number of freight vehicles to meet a high and growing demand becomes a problem specially in areas where urban road network is not efficient (not properly designed and parking spaces not properly used). This study also highlights the need for an urban freight mobility plan and public policies, by offering sustainable alternatives for urban goods distribution, which improve the urban environment. By using geospatial analysis, the study delivered statistics data and maps to catch the attention of decision makers and transportation managers, therefore facilitate the discussion on transportation policies in the city of Belo Horizonte
The Role of Railway Infrastructures in Land Use and Cover Change in MATOPIBA, Brazil
Land use/cover change (LUCC) can both affect and result of complex natural and socio-economic processes. The highway system is a key component for LUCC, however the role of railway infrastructure as a driver of the changes has been hardly ever in debate. In Brazil the steadily rise on large scale agro husbandry production has been demanding for railway infrastructure in states such as Maranhão, Tocantins, Piaui and Bahia (MATOPIBA), where agro husbandry production is steadily rising. In this context, the objective of this work is to develop a spatially explicit model to explore the associations between railway infrastructure (tracks, rail yards e intermodal facilities) and LUCC in an area of 650.682 km² in MATOPIBA . The model used the Baysian method of Weights of Evidence to explore the spatial determinants of land use transitions and their spatial determinants as well its associations to railway infrastructure. The model was calibrated with 2000-2012 data. This modelling approach was able to identify which variables and its ranges that can be associated to LUCC in MATOPIBA and this model was further used to simulate future scenarios of land use change in the coming decades. Our results clearly show a clear trend of increasing agro husbandry production and a trend of decreasing in native vegetation. Our results also highlight that railway infrastructure can indeed be associated changes into spatial configuration of landscape mainly by attracting LUCC in the nodes of new railway infrastructures.As mudanças do uso e cobertura do solo afetam e são resultantes de complexos processos naturais e socioeconômicos. A infraestrutura rodoviária exerce grande influência nessa dinâmica, contudo o papel das ferrovias nesse processo tem sido pouco debatido. No Brasil, a expansão da agropecuária nas últimas décadas tem demandado investimentos em transporte. Isso inclui o planejamento e construção de ferrovias na região formada pelos estados do Maranhão, Tocantins, Piauí e Bahia (MATOPIBA), uma das áreas com maior crescimento e expansão da produção agropecuária. Considerando este contexto, este trabalho tem como objetivo desenvolver uma modelagem espacialmente explícita explorando as associações entre a infraestrutura ferroviária (trilhos, pátios ferroviários e terminais intermodais) e a dinâmica de uso e cobertura do solo em uma área de 650.682 km² no MATOPIBA. O modelo espacialmente explícito desenvolvido para o período 2000-2012 utilizou o método bayesiano dos pesos de evidência para explorar quais os determinantes espaciais das transições entre classes de cobertura do solo e o papel das infraestruturas ferroviárias de transporte nessas mudanças. Os resultados da modelagem forneceram subsídios para conhecer as variáveis e explicar as transições de uso e cobertura do solo no período investigado, também como compilar cenários preditivos do uso e cobertura do solo para as próximas décadas. A modelagem mostrou uma tendência no aumento das áreas destinadas para a produção agropecuária em detrimento das áreas com vegetação nativa . Os resultados também mostraram que as infraestruturas ferroviárias poderão alterar a configuração espacial na região, atraindo a produção agropecuária para os pontos nodais das novas infraestruturas
Analysis of Freight Trip Generation Model for Food and Beverage in Belo Horizonte (Brazil)
Today, one of the main challenges faced in urban logistics is the distribution of goods. In Brazil, mid to large cities have experienced consequences of unplanned urban sprawl and lack of adequate transportation infrastructure. The relationship between urban planning and transport stands out the attractiveness of some urban activities with direct impacts on the movement of people and goods and other component elements of urban space. The segment of bars and restaurants falls within this context, therefore is a vital activity responsible for significant percentage of jobs and revenue in a city. Altogether, foods & beverages commercial activities move daily large volumes of goods to meet the need of customers. This paper presents the results of a freight trip generation model developed for pubs and restaurants in Belo Horizonte (Brazil). Once performed the model determined the number of trips generated per day per establishment. In order to expand the discrete result to a continuous one, the results were geographically interpolated to a continuous surface and extrapolated within the city limits. The data for the freight trip generation model were obtained by survey. For this, we designed a structured questionnaire to obtain information about goods, frequency, operational time, place of performance of the loading/unloading of goods, establishment size and the number of employees. Besides these information, we investigated the acceptance of alternative practices in the delivery of goods, such as off-peak delivery. To accomplish the proposed models, we applied a simple linear regression, correlating the following variables: (i) Number of trips versus area of the establishment; (ii) Number of trips versus number of employees; (iii) Number of trips versus operation day of the establishment. With the results of the linear regression for travel generations, conducted the data interpolation based on the standard deviation of the results to define the sample classification bands. This interpolation method was chosen because it is one of the most suitable for analysis of spatially scattered points due to the straightforwardness of the model and because it does not consider extra noise such as slope and spatial constraints as barriers. In this method, interpolation is determined by the value assigned to each point (in this case the number of trips), wherein the closer the points the higher the correlation trend. Finally, the resulting trip generation surface was analysed together with other geographic data such as demographic data, road network density and socioeconomic data. Findings indicate the importance of a mathematic-geographic model for trip generation as a feasible approach for support transportation planning & operation for urban goods distribution. Critical information such as the high concentration of pubs and restaurants in the same region can reinforce the vocation of the city for trading. However, an elevated number of freight vehicles to meet a high and growing demand becomes a problem specially in areas where urban road network is not efficient (not properly designed and parking spaces not properly used). This study also highlights the need for an urban freight mobility plan and public policies, by offering sustainable alternatives for urban goods distribution, which improve the urban environment. By using geospatial analysis, the study delivered statistics data and maps to catch the attention of decision makers and transportation managers, therefore facilitate the discussion on transportation policies in the city of Belo Horizonte
COMPARAÇÃO E VALIDAÇÃO DA MODELAGEM ESPACIAL DE RISCOS DE INCÊNDIOS CONSIDERANDO DIFERENTES MÉTODOS DE PREDIÇÃO
Os problemas ambientais decorrentes dos incêndios alteram a dinâmica do planeta modificando seus ciclos e destruindo ecossistemas. O homem é responsável por quase a totalidade das queimadas, sendo ele também protagonista das iniciativas de prevenção. Dessa maneira, torna-se necessário um planejamento de ações ao combate desses danos ambientais. Uma vez que alocalização geográfica é importante atributo, esta pesquisa objetiva apoiar medidas de prevenção e controle de incêndios gerando e validando mapas com modelos preditivos de riscos de incêndios no município de João Pessoa – PB. Os dados foram modelados, processados, manipulados e analisados no software ArcGIS v10.0 e Matlab, bem como a geração e overlay de mapas temáticosatravés de análise multicritério, ponderação das variáveis e lógica fuzzy. Foi realizada a validação dos modelos considerando dados reais, onde os resultados demonstraram que os modelos gerados com o auxílio da lógica fuzzy apresentaram um coeficiente de determinação acima de 85%. A variável pluviometria contribuiu significativamente para que os modelos apresentassem maior confiabilidade. Essa variável não foi utilizada e nem recomendada especificamente em outras metodologias comparadas nessa pesquisa. Os fatores que contribuíram para o alto grau de vulnerabilidade de risco de incêndios: alta declividade, presença de vegetação, áreas de alta concentração de pessoas, aglomerados subnormais e regiões dentro da influência da rede viária ehidrografia. Por fim, esse trabalho teve o intuito de contribuir na tomada de decisão dos gestores de meio ambiente, segurança e defesa social de forma rápida e precisa com recurso a poucas variáveis e baixo custo
Análise do balanceamento de imagens aplicado a fotogrametria.
Entende-se como balanceamento de imagens o procedimento capaz de atenuar as discrepâncias radiométricas entre regiões de uma mesma imagem, bem como entre imagens contíguas. De modo geral, as principais conseqüências sofridas são de caráter visual, em especial na composição de mosaicos, realçando as discrepâncias de coloração, brilho e contraste entre diferentes porções da imagem ou entre imagens distintas. O desenvolvimento da pesquisa contou inicialmente com o levantamento detalhado das causas e dos efeitos ocorridos nas imagens, seguido do levantamento das técnicas e dos instrumentos necessários a sua correção, envolvendo as técnicas analógicas, eletrônicas e a evolução para os procedimentos computacionais. Desta forma, foram relatadas as principais soluções digitais empregadas no balanceamento, tendo as técnicas de processamento digital de imagens como base do processo. O objetivo deste trabalho é apresentar o atual estado da arte", as necessidades e as principais soluções relacionadas ao balanceamento de imagens, desenvolvendo análises comparativas e descritivas entre diferentes técnicas e diferentes aplicativos. Como etapa final, a pesquisa contou com a avaliação qualitativa os benefícios obtidos pela adoção do balanceamento de imagens nas atividades da Fotogrametria, relatando melhorias significativas na composição de mosaicos e ortofotos a partir de imagens balanceadas, se comparados aos mosaicos compostos de imagens convencionais
Road detection over informal settlements in a suburban area of Sao Paulo city by using high resolution satellite image and a object-based classification approach.
O crescimento descontrolado ocorrido nas atuais metrópoles de países em desenvolvimento requer intensos mapeamentos para a atualização da base de dados geográfica. O intenso processo de urbanização vivido na cidade de São Paulo desde os anos 70 ilustra bem esse cenário. Apesar de existirem levantamentos aéreos e, mais recentemente, imagens de satélite com alta resolução espacial, a necessidade de informações geográficas precisas, rápidas e menos onerosas é, mais do que nunca, um fato. Nesse sentido, a classificação automatizada de imagens de alta resolução espacial tem demonstrado resultados insatisfatórios ao utilizar classificadores pixel a pixel, em especial para áreas urbanas. O crescente sucesso da classificação de imagens baseada em objetos tem estimulado pesquisadores a criar novos meios de superar a limitação das tradicionais técnicas de classificação de imagens. A idéia central da classificação de imagens orientada a objetos é extrair objetos primitivos a partir das imagens e utilizar suas informações para a composição de regras e estratégias a serem aplicadas no processo classificatório. Além da análise espectral, a classificação de imagens baseada em objetos permite envolver análises geométricas e contextuais. Este trabalho reporta o uso da classificação baseada em objetos para detecção da malha viária, aplicado na periferia urbana da cidade de São Paulo. Áreas de ocupação irregular compõem a maior parte da área selecionada para o estudo, sendo que a malha viária reflete bem o padrão de ocupação não planejada dessa região. As ruas são em geral geometricamente irregulares e com diferentes tipos de pavimentação. Detectar a malha viária com base nessas características foi o desafio maior deste trabalho, que teve, como hipótese, a viabilidade do emprego da classificação orientada a objetos para essa finalidade. A metodologia apresentada utiliza uma imagem multiespectral do satélite IKONOS II. Como primeiros passos, processou-se a segmentação e calcularam-se as componentes principais. Classes auxiliares como áreas impermeabilizadas e áreas de solo exposto foram computadas utilizando funções apropriadas. Em suma, a partir das informações geométricas dos objetos, como largura, comprimento, coeficiente de assimetria, área, entre outros, alguns objetos foram selecionados como representantes da malha viária, e então analisados perante a informação contextual, para que fossem classificados como vias pavimentadas e vias não pavimentadas. Os resultados foram analisados mediante três diferentes métodos: 1) inspeção visual, na qual foi analisada qualitativamente a aderência entre as vias extraídas e as vias reais; 2) acurácia da classificação, através de comparações entre a malha viária detectada e a de referência, que forneceu parâmetros estatísticos de qualidade da classificação, como os erros de comissão e omissão ; 3) análise linear comparativa, a qual forneceu parâmetros como integridade (ou completeza) e precisão da malha viária detectada utilizando linhas referenciais e linhas extraídas dos polígonos das vias detectadas, obtidos por morfologia matemática. Considerando o alto grau de heterogeneidade das feições presentes na área de estudo, a acurácia geral alcançada foi boa. Embora a metodologia não tenha produzido um mapa viário, no sentido próprio da palavra, o uso combinado de imagens multispectrais de alta resolução espacial e da classificação baseada em objetos mostrou que a metodologia pode ser utilizada para minerar dados relativos a malha viária e produzir informações significantes para auxiliar a tomada de decisões.Uncontrolled sprawl occurring in large cities of developing countries requires intensive mapping efforts to update geodatabases. The intense urbanization process experienced since the 70\'s in Sao Paulo city illustrates very well the reported scenario. Despite aerial data and, more recent, high spatial resolution satellite data which have been employed as basis for mapping, the need for precise, faster and cheaper mapping efforts is real. In this sense, automated classification of high resolution imagery has demonstrated unsatisfactory results when traditional per-pixel classifiers are used, especially for urban areas. The increasing success of object-based classification has stimulated researchers to create new methodologies to overcome this shortcoming of traditional approaches. The object-based image classification\'s idea is extract object-primitives from images and then use their information to compose rules and strategies to be applied on the classification process. Beyond the spectral analysis, geometric, and contextual analysis are also addressed on object-based classification. This work reports the use of object-based image classification applied on road detection over the suburban area of Sao Paulo city. Informal settlements compose the most part of the study area and the transportation network reflects the unplanned occupation. Roads are geometrically irregular and with different kind of pavements. Detecting roads based on these characteristics was the biggest challenge faced here, and this work hypothesizes object-based classification can be used to. The methodology presented employs an IKONOS II data. At first, principal components and segmentation were computed and then auxiliary data for impervious surface and bare soil areas were previously calculated from customized features. In short, based on geometric information as width, length, asymmetry, area, and more, objects were elected as road and then analyzed through contextual information as paved road or unpaved road. Results were analyzed under three different ways: 1) visual inspection, where the adherence between extracted road and real ones provided a good indicator for qualitative analysis ; 2) classification accuracy, by comparing detected road areas and referential ones, which provided statistical parameters for quality as omission and commission error ; 3) linear comparative analysis, which provided parameters as correctness and completeness using referential lines and lines arose from extracted areas based on mathematical morphology tools. Regarding the high degree of heterogeneity of features present on study area, the overall accuracy reached is good. Despite the methodology did not produce a road map, the results shown the combined use of high resolution multi-spectral imagery and object-based classification can effectively mine road features, producing significant information to support decision makers
Emprego de técnicas digitais para a concepção da base cartográfica da bacia hidrográfica do Córrego Cabuçu de Baixo, São Paulo, SP
The use of appropriate cartography database is extremely important to support projects of planning and land management. However, the absence of maps, or the amount of obsolete maps, has been leading to the adoption of alternative methodologies aiming to faster and less onerous solutions for the development of cartography databases, without compromising quality. Regarding this problem, the present paper reports on the viability of constructing a cartographic database designed for applications in hydrology, more specifically, as a base for a Decision Support System for Urban Basin Management - DSSURM. The methodology combines techniques of manual terrain features extraction, as well as automatic techniques of photogrammetry. Digital orthophotos and contour maps were generated. The coarser 5 meters interval was used for the mountainous regions and forest, and the finer 1 meter interval for other regions, floodplains were prioritized for mapping flooding areas. The final analyses show the viability of the methodology as well as the high quality of the cartographic products
Proposição de rotina morfológica para detecção de malha viária em imagens orbitais
The outdating of cartographic products affects planning. It is important to propose methods to help detect changes in surface. Thus, the combined use of remote sensing image and techniques of digital image processing has contributed significantly to minimize such outdating. Mathematical morphology is an image processing technique which describes quantitatively geometric structures presented in the image and provides tools such as edge detectors and morphological filters. Previous studies have shown that the technique has potential on the detection of significant features. Thus, this paper proposes a routine of morphological operators to detect a road network. The test area corresponds to an excerpt Quickbird image and has as a feature of interest an avenue of the city of Presidente Prudente, SP. In the processing, the main morphological operators used were threshad, areaopen, binary and erosion. To estimate the accuracy with which the linear features were detected, it was done the analysis of linear correlation between vectors of the features detected and the corresponding topographical map of the region. The results showed that the mathematical morphology can be used in cartography, aiming to use them in conventional cartographic updating processes