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      Classificação orientada a objeto de imagens de sensoriamento remoto em estudos epidemiológicos sobre leishmaniose visceral em área urbana Translated title: Object-oriented remote sensing image classification in epidemiological studies of visceral leishmaniasis in urban areas Translated title: Clasificación orientada a objetos procedentes de imágenes satélite en los estudios epidemiológicos sobre leishmaniasis visceral en zonas urbanas

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          Abstract

          Neste estudo, explorou-se o uso da classificação orientada a objeto de imagens de sensoriamento remoto em estudos epidemiológicos sobre leishmaniose visceral (LV) em áreas urbanas. A classificação orientada a objeto foi aplicada a cenas Landsat 5 TM da cidade de Teresina, Piauí, Brasil, para obtenção de informações ambientais e temperatura. Para o período de 1993-1996, a taxa de incidência de LV nos setores censitários da cidade foi positivamente correlacionada com a área do setor censitário coberta por vegetação densa, rasteira e solo exposto e negativamente com a área coberta por água e áreas densamente ocupadas. No período de 2001-2006, foram encontradas correlações positivas com vegetação densa, rasteira, solo exposto e áreas densamente ocupadas e negativas com áreas urbanas com alguma vegetação. A temperatura da superfície terrestre foi negativamente associada à incidência de LV nos dois períodos. A classificação orientada a objeto pode ser útil para caracterizar paisagens associadas à ocorrência da LV em áreas urbanas e delimitar áreas de risco para definição de prioridades na implementação de intervenções.

          Translated abstract

          This study explored the use of object-oriented classification of remote sensing imagery in epidemiological studies of visceral leishmaniasis (VL) in urban areas. To obtain temperature and environmental information, an object-oriented classification approach was applied to Landsat 5 TM scenes from the city of Teresina, Piauí State, Brazil. For 1993-1996, VL incidence rates correlated positively with census tracts covered by dense vegetation, grass/pasture, and bare soil and negatively with areas covered by water and densely populated areas. In 2001-2006, positive correlations were found with dense vegetation, grass/pasture, bare soil, and densely populated areas and negative correlations with occupied urban areas with some vegetation. Land surface temperature correlated negatively with VL incidence in both periods. Object-oriented classification can be useful to characterize landscape features associated with VL in urban areas and to help identify risk areas in order to prioritize interventions.

          Translated abstract

          Este estudio investigó el uso de la clasificación orientada a objetos de imágenes satélite en estudios epidemiológicos acerca de la leishmaniasis visceral (LV) en zonas urbanas. Se aplicó la clasificación orientada a objetos en escenas Landsat 5 TM de la ciudad de Teresina, Piauí, Brasil, para obtener información ambiental y temperatura. De 1993 a 1996, la tasa de incidencia de LV en los sectores censales de la ciudad se correlacionó positivamente con el área del sector censal cubierto por vegetación densa, pastos y suelo desnudo, y negativamente con el área cubierta por agua y zonas densamente pobladas. De 2001 a 2006 se han encontrado correlaciones positivas con vegetación densa, vegetación tipo maleza, suelo desnudo y zonas densamente pobladas; y negativas con áreas urbanas con poca vegetación. La temperatura se asoció negativamente con la incidencia de la LV en ambos períodos. La clasificación orientada a objetos puede ser útil para caracterizar los paisajes asociados a la ocurrencia de la LV en áreas urbanas y delimitar zonas de riesgo para establecer prioridades de intervención.

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          Object based image analysis for remote sensing

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            Introductory digital image processing: Remote sensing perspective

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              Multilevel modelling of the incidence of visceral leishmaniasis in Teresina, Brazil.

              Epidemics of visceral leishmaniasis (VL) in major Brazilian cities are new phenomena since 1980. As determinants of transmission in urban settings probably operate at different geographic scales, and information is not available for each scale, a multilevel approach was used to examine the effect of canine infection and environmental and socio-economic factors on the spatial variability of incidence rates of VL in the city of Teresina. Details on an outbreak of greater than 1200 cases of VL in Teresina during 1993-1996 were available at two hierarchical levels: census tracts (socio-economic characteristics, incidence rates of human VL) and districts, which encompass census tracts (prevalence of canine infection). Remotely sensed data obtained by satellite generated environmental information at both levels. Data from census tracts and districts were analysed simultaneously by multilevel modelling. Poor socio-economic conditions and increased vegetation were associated with a high incidence of human VL. Increasing prevalence of canine infection also predicted a high incidence of human VL, as did high prevalence of canine infection before and during the epidemic. Poor socio-economic conditions had an amplifying effect on the association between canine infection and the incidence of human VL. Focusing interventions on areas with characteristics identified by multilevel analysis could be a cost-effective strategy for controlling VL. Because risk factors for infectious diseases operate simultaneously at several levels and ecological data usually are available at different geographical scales, multilevel modelling is a valuable tool for epidemiological investigation of disease transmission.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Journal
                csp
                Cadernos de Saúde Pública
                Cad. Saúde Pública
                Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz (Rio de Janeiro )
                1678-4464
                August 2014
                : 30
                : 8
                : 1639-1653
                Affiliations
                [1 ] Universidade do Estado do Rio de Janeiro Brazil
                [2 ] Universidade Federal do Rio de Janeiro Brazil
                [3 ] Secretaria de Vigilância em Saúde de Nova Iguaçu Brazil
                Article
                S0102-311X2014000801639
                10.1590/0102-311X00059414
                6d3b1a24-bffb-4098-984c-0bb1333b41c2

                http://creativecommons.org/licenses/by/4.0/

                History
                Product

                SciELO Brazil

                Self URI (journal page): http://www.scielosp.org/scielo.php?script=sci_serial&pid=0102-311X&lng=en
                Categories
                Health Policy & Services

                Public health
                Remote Sensing Technology,Satellite Imagery,Visceral Leishmaniasis,Tecnología de Sensores Remotos,Imágenes Satelitales,Leishmaniasis Visceral,Tecnologia de Sensoriamento Remoto,Imagens de Satélites,Leishmaniose Visceral

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