|
Registro Completo |
|
Biblioteca(s): |
Embrapa Pantanal. |
|
Data corrente: |
03/10/2001 |
|
Data da última atualização: |
30/03/2017 |
|
Autoria: |
BAVIA, M. E.; MALONE, J. B.; HALE, L.; DANTAS, A.; MARRONI, L.; REIS, R. |
|
Afiliação: |
Universidade Federal da Bahia. Faculdade de Medicina Veterinaria (Salvador, BA); Louisiana State University (Baton Rouge, LA); Louisiana Dep. of Natural Resources (Baton Rouge, LA); FNS (Salvador, BA); INPE. |
|
Título: |
Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schitosomiasis in Bahia, Brazil. |
|
Ano de publicação: |
2001 |
|
Fonte/Imprenta: |
Acta Tropica, v.79, n.1, p.79-85, 2001. |
|
Idioma: |
Inglês |
|
Conteúdo: |
A geographic information system (GIS) was constructed using maps of regional agroclimatic features, vegetation indices and earth surface temperature data from environmental satellites, together with Schistosoma mansoni prevalence records from 270 municipalities including snail host distributions in Bahia, Brazil to study the spatial and temporal dynamics of infection and to identify environmental factors that influence the distribution of schistosomiasis. In an initial analysis, population density and duration (months) of the annual dry period were shown to be important determinants of disease. In cooperation with the National Institute of Spatial Research in Brazil (INPE), day and night imagery data covering the state of Bahia were selected at approximately bimonthly intervals in 1994 (six day-night pairs) from the data archives of the advanced very high resolution radiometer (AVHRR) sensor of the National Oceanic and Atmospheric Administration (NOAA)-11 satellite. A composite mosaic of these images was created to produce maps of: (1) average values between 0 and +1 of the normalized difference vegetation index (NDVI); and (2) average diurnal temperature differences (dT) on a scale of values between 0 and 15 degrees C. For each municipality, NDVI and dT were calculated for a 3x3 pixel (9 km(2) area) grid and analyzed for relationships to prevalence of schistosomiasis. Results showed a statistically significant relationship of prevalence to dT (rho=-0.218) and NDVI (rho=0.384) at the 95% level of confidence by the Spearman rank correlation coefficient. Results support use of NDVI, dT, dry period climatic stress factors and human population density for development of a GIS environmental risk assessment model for schistosomiasis in Brazil. MenosA geographic information system (GIS) was constructed using maps of regional agroclimatic features, vegetation indices and earth surface temperature data from environmental satellites, together with Schistosoma mansoni prevalence records from 270 municipalities including snail host distributions in Bahia, Brazil to study the spatial and temporal dynamics of infection and to identify environmental factors that influence the distribution of schistosomiasis. In an initial analysis, population density and duration (months) of the annual dry period were shown to be important determinants of disease. In cooperation with the National Institute of Spatial Research in Brazil (INPE), day and night imagery data covering the state of Bahia were selected at approximately bimonthly intervals in 1994 (six day-night pairs) from the data archives of the advanced very high resolution radiometer (AVHRR) sensor of the National Oceanic and Atmospheric Administration (NOAA)-11 satellite. A composite mosaic of these images was created to produce maps of: (1) average values between 0 and +1 of the normalized difference vegetation index (NDVI); and (2) average diurnal temperature differences (dT) on a scale of values between 0 and 15 degrees C. For each municipality, NDVI and dT were calculated for a 3x3 pixel (9 km(2) area) grid and analyzed for relationships to prevalence of schistosomiasis. Results showed a statistically significant relationship of prevalence to dT (rho=-0.218) and NDVI (rho=0.3... Mostrar Tudo |
|
Palavras-Chave: |
Esquitosomose; GIS. |
|
Thesagro: |
Epidemiologia; Schistosoma Mansoni; Sensoriamento Remoto. |
|
Thesaurus Nal: |
epidemiology; remote sensing; schistosomiasis. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 02539naa a2200277 a 4500
001 1809084
005 2017-03-30
008 2001 bl --- 0-- u #d
100 1 $aBAVIA, M. E.
245 $aUse of thermal and vegetation index data from earth observing satellites to evaluate the risk of schitosomiasis in Bahia, Brazil.
260 $c2001
520 $aA geographic information system (GIS) was constructed using maps of regional agroclimatic features, vegetation indices and earth surface temperature data from environmental satellites, together with Schistosoma mansoni prevalence records from 270 municipalities including snail host distributions in Bahia, Brazil to study the spatial and temporal dynamics of infection and to identify environmental factors that influence the distribution of schistosomiasis. In an initial analysis, population density and duration (months) of the annual dry period were shown to be important determinants of disease. In cooperation with the National Institute of Spatial Research in Brazil (INPE), day and night imagery data covering the state of Bahia were selected at approximately bimonthly intervals in 1994 (six day-night pairs) from the data archives of the advanced very high resolution radiometer (AVHRR) sensor of the National Oceanic and Atmospheric Administration (NOAA)-11 satellite. A composite mosaic of these images was created to produce maps of: (1) average values between 0 and +1 of the normalized difference vegetation index (NDVI); and (2) average diurnal temperature differences (dT) on a scale of values between 0 and 15 degrees C. For each municipality, NDVI and dT were calculated for a 3x3 pixel (9 km(2) area) grid and analyzed for relationships to prevalence of schistosomiasis. Results showed a statistically significant relationship of prevalence to dT (rho=-0.218) and NDVI (rho=0.384) at the 95% level of confidence by the Spearman rank correlation coefficient. Results support use of NDVI, dT, dry period climatic stress factors and human population density for development of a GIS environmental risk assessment model for schistosomiasis in Brazil.
650 $aepidemiology
650 $aremote sensing
650 $aschistosomiasis
650 $aEpidemiologia
650 $aSchistosoma Mansoni
650 $aSensoriamento Remoto
653 $aEsquitosomose
653 $aGIS
700 1 $aMALONE, J. B.
700 1 $aHALE, L.
700 1 $aDANTAS, A.
700 1 $aMARRONI, L.
700 1 $aREIS, R.
773 $tActa Tropica$gv.79, n.1, p.79-85, 2001.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Pantanal (CPAP) |
|
