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 corre-
lation 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.
