Evaluating satellite sensor-derived indices for lyme disease risk prediction
Date of Original Version
The wetness and greenness indices created using Landsat Thematic Mapper (TM) data from June 1995 and 1997 and July 2002 were tested for their ability to predict the location of sites with different levels of nymphal blacklegged tick, Ixodes scapularis Say, abundance in Rhode Island. In 1995, there were statistically significant differences in the mean of greenness and wetness indices between sites classified as low and moderate tick abundance areas (P = 0.005 and P = 0.041, respectively). In 1997, there also were statistically significant differences in the mean of the greenness and wetness indices, but these differences were between the grouping of low/moderate tick abundance and the high tick abundance category (P = 0.023 and P = 0.015, respectively). The same indices from the 2002 image were not significant predictors of tick abundance. It may be that Landsat TM-derived indices can be used to predict nymphal blacklegged tick abundance in years (e.g., 1995 and 1997) when tick abundance is lower than average but not in years when it is higher (e.g., 2002). Thus, it seems unlikely that these remotely sensed indices will be very useful for modeling nonperidomestic Lyme disease risk over a large region in Rhode Island. © 2006 Entomological Society of America.
Publication Title, e.g., Journal
Journal of Medical Entomology
Rodgers, Sarah E., and Thomas N. Mather. "Evaluating satellite sensor-derived indices for lyme disease risk prediction." Journal of Medical Entomology 43, 2 (2006). doi: 10.1603/0022-2585(2006)043[0337:ESSIFL]2.0.CO;2.