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1.
Eng. sanit. ambient ; 18(1): 55-64, jan.-mar. 2013. ilus
Artículo en Portugués | LILACS | ID: lil-676958

RESUMEN

A água tem importante papel na sociedade humana, especialmente no Brasil. Seus usos são múltiplos, incluindo o abastecimento, produção energética e lazer, entre outros. A própria Política Nacional de Recursos Hídricos (Lei nº 9.433/97) traz entre seus artigos a sua importância segundo os seus usos múltiplos, priorizando o abastecimento humano e a dessedentacão de animais. Neste enfoque é importante considerar a qualidade físico-química da água para atender a estas demandas, escopo do enquadramento dos corpos d'água segundo seus usos preponderantes, com o objetivo de garantir qualidade compatível com os usos mais exigentes a que for destinada e diminuir os custos de combate à poluição mediante ações preventivas permanentes. Entre os vários parâmetros que buscam analisar a qualidade físico-química da substância busca-se entender a distribuição espacial da turbidez na superfície do lago, uma vez que a variação dos componentes que alteram este parâmetro pode ser detectada por meio do sensoriamento remoto passivo. A aplicação do Modelo linear de mistura espectral permitiu, de forma satisfatória, identificar a distribuição espacial da turbidez no espelho de água.


The water has an important role in human society, especially in Brazil. Its uses are multiple, including supply, energy production, recreation and others. The National Policy for Water Resources (Law Nº 9.433/97) states in its articles the importance of water use in accordance to their multiple uses, prioritizing the supply for humans and animals. In this approach, it is important to consider the physical and chemical quality of water to meet these demands, scope of the legal framework applied to the Brazilian water bodies according to their main uses, in order to guarantee the water quality compatible with the most demanding uses and to reduce the costs of pollution control through ongoing preventive actions. Among the various parameters that seek to analyze the physical and chemical quality of water it is intended to understand the spatial distribution of turbidity in the lake's surface, since the variation of the components that alter this parameter can be detected by means of passive remote sensing. The application of the Linear spectral mixture model allowed, satisfactorily, the identification of turbidity spatial distribution patterns in the lake.

2.
Mem. Inst. Oswaldo Cruz ; 105(4): 512-518, July 2010. ilus, tab
Artículo en Inglés | LILACS | ID: lil-554823

RESUMEN

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.


Asunto(s)
Animales , Humanos , Biomphalaria , Vectores de Enfermedades , Sistemas de Información Geográfica , Plantas , Esquistosomiasis mansoni , Brasil , Densidad de Población , Dinámica Poblacional , Prevalencia , Estaciones del Año
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