Procedimento Para Compatibilizar Mapas Em Diferentes Escalas E O Problema Da Mudança De Suporte Espacial

Libório, Matheus Pereira; Martinuci, Oséias da Silva; Hadad, Renato Moreira; Silva, José Frankneile De Melo

doi:10.14393/rcg217449943

Cited by 3 publications

(3 citation statements)

References 18 publications

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“…5 (IBGE, 2010b). Census tracts are the smallest unit of census information collection and are the most reliable data source on Brazilian cities' urban infrastructure (Libório, da Silva Martinuci, et al, 2020; Libório, Laudares, et al, 2020).…”

Section: Real Data: Mapping the Spatial Heterogeneity Of Public Urban...mentioning

confidence: 99%

“…The concept of heterogeneity is associated with the idea that sub‐indicators influence the composite indicator's score non‐homogeneously and mainly vary from one unit to another. Let us see the example of a composite indicator built to represent the public infrastructure of a city (Libório, da Silva Martinuci, et al, 2020; Libório, Laudares, et al, 2020). The absence of asphalt in a wealthy neighborhood is more important in representing urban public infrastructure than in a poor neighborhood.…”

Section: Introductionmentioning

confidence: 99%

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Harnessing Spatial Heterogeneity in Composite Indicators through the Ordered Geographically Weighted Averaging (OGWA) Operator

Fusco,

Libório,

Rabiei‐Dastjerdi

et al. 2023

Geographical Analysis

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Spatially heterogeneous weights and a non‐compensatory aggregation scheme, are two important properties needed to construct a composite indicator capable of summarizing properly the multidimensional phenomenon of local spatial units. Such a composite indicator takes into account, on the one hand, the latent characteristics of the specific units related to their location in the territory, and on the other hand, the relative importance of sub‐indicators highlighting both positive and negative aspects of the studied phenomena. Under these premises, this article proposes a new method called Ordered Geographically Weighted Averaging (OGWA), which can consider different degrees of non‐compensability between sub‐indicators and, at the same time, the spatial heterogeneity for continuous, ordinal, and mixed data. The properties of the method are evaluated through a simulation study. Finally, the method is applied to construct a composite indicator to map the urban public infrastructure of São Sebastião do Paraíso, a city located in the southeastern region of Brazil.

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Section: Real Data: Mapping the Spatial Heterogeneity Of Public Urban...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Harnessing Spatial Heterogeneity in Composite Indicators through the Ordered Geographically Weighted Averaging (OGWA) Operator

Fusco,

Libório,

Rabiei‐Dastjerdi

et al. 2023

Geographical Analysis

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“…Uma das principais funcionalidades dos Sistemas de Informações Geográficas (SIGs) é a integração de dados em diversos formatos e escalas (CÂMARA, SOUZA;FREITAS, 1996). O avanço nas tecnologias de SIGs, envolvendo o problema da variabilidade de escala e resolução e da generalização cartográfica, amplamente difundidos por Allen;Starr (1982); Ruas; Lagrange (1995); Goodchild;Quattrochi (1997), estão cada vez mais robustas na análise espacial (MERCHANT; NARUMALANI, 2009;LIBÓRIO et al, 2020). Como as resoluções espaciais das imagens multiespectrais do Landsat-8 e do MDE são de 30 por 30 metros, a área mínima mapeável é de 30m2 e a escala é de 1:100.000 (MIRANDA, 2005;SILVA, 2003).…”

Section: Materials E Métodounclassified

Processamento analítico hierárquico no mapeamento da fragilidade ambiental à erosão do solo

2020

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Para análise espacial da vulnerabilidade à erosão do solo, as geotecnologias maximizam o tempo e minimizam os custos, dentre as quais se destacam o sensoriamento remoto e o geoprocessamento. O objetivo do presente estudo foi aplicar a análise multicriterial para determinar a fragilidade ambiental potencial e emergente e obter um diagnóstico para a tomada de decisão frente aos processos erosivos da Bacia Hidrográfica do Rio Japaratuba no estado de Sergipe. O principal procedimento técnico empregado foi o Processo Analítico Hierárquico (AHP), cujos critérios utilizados para a avaliação das fragilidades potencial e emergente foram: dissecação do relevo, precipitação, hipsometria, declividade e uso e cobertura do solo. Os resultados obtidos possibilitaram concluir que 13,44%, 71,45% e 15,11% da área de estudo apresentaram baixa, média e alta fragilidade ambiental emergente à erosão, respectivamente. A baixa fragilidade ambiental encontra-se em pequenas áreas esparsas compostas por florestas, mangues, praias e dunas e a média estende-se por toda a bacia. A alta fragilidade ambiental concentra-se na porção centro-norte das regiões semiárida e agreste em decorrência da conversão da vegetação natural em atividades agropecuárias. O produto cartográfico gerado retratou a gravidade decorrente da acentuada interferência humana quanto aos processos erosivos na área de estudo.

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Time–Space Analysis of Multidimensional Phenomena: A Composite Indicator of Social Exclusion Through k-Means

et al. 2021

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Composite Indicators are one-dimensional measurements that simplify the interpretation of multidimensional phenomena that facilitate public policies' elaboration. The literature on composite indicators is abundant, diversified, and inserted in practically all knowledge areas. Part of this literature aims to reduce uncertainties that propagate through the structure of the composite indicator during the process of normalization, weighting, and aggregation of indicators. Even if no composite indicator is exempt from criticism, the current literature is already sufficiently large and deep to guide researchers in constructing reliable composite indicators. However, most related works are concerned with representing multidimensional phenomena in time or space. Although some studies are interested in representing multidimensional phenomena that co-occur in time-space, the portion of the literature that addresses composite indicators is still not comprehensive, therefore leaving several open questions: What are the additional challenges in representing multidimensional phenomena in time-space? What methods can be used? Which method is most appropriate for this type of representation? What are the shortcomings of this method? How to reduce these shortcomings? This research aims at answering these questions in order to advance the time-space analysis of multidimensional phenomena. As a general contribution, the work presents a scheme of procedures that reduce subjectivities and uncertainties in the representations of multidimensional phenomena in time-space. As a specific contribution, it provides accurate and reliable information on the trajectory of social exclusion in the analyzed region. KeywordsComposite indicators • Multidimensional phenomena • Cluster analysis • Principal component analysis • Time-in-space analysis • Urban geography

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Procedimento Para Compatibilizar Mapas Em Diferentes Escalas E O Problema Da Mudança De Suporte Espacial

Cited by 3 publications

References 18 publications

Harnessing Spatial Heterogeneity in Composite Indicators through the Ordered Geographically Weighted Averaging (OGWA) Operator

Harnessing Spatial Heterogeneity in Composite Indicators through the Ordered Geographically Weighted Averaging (OGWA) Operator

Processamento analítico hierárquico no mapeamento da fragilidade ambiental à erosão do solo

Time–Space Analysis of Multidimensional Phenomena: A Composite Indicator of Social Exclusion Through k-Means

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