| | | Document Type | : | Latin Dissertation | | Language of Document | : | English | | Record Number | : | 53963 | | Doc. No | : | TL23917 | | Call number | : | 3159247 | | Main Entry | : | Atiqur Rahman | | Title & Author | : | Use of remote sensing for analysis and estimation of vector -borne diseaseAtiqur Rahman | | College | : | City University of New York | | Date | : | 2005 | | Degree | : | Ph.D. | | student score | : | 2005 | | Page No | : | 214 | | Abstract | : | An epidemiological data of malaria cases were correlated with satellite-based vegetation health (VH) indices to investigate if they can be used as a proxy for monitoring the number of malaria cases. Mosquitoes, which spread malaria in Bangladesh, are very sensitive to environmental conditions, especially to changes in weather. Therefore, VH indices, which characterize weather conditions, were tested as indicators of mosquitoes' activities in the spread of malaria. Satellite data were presented by the following VH indices: Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI). They were derived from radiances and measured by the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA afternoon polar orbiting satellites. Assessment of sensitivity of the VH was performed using correlation and regression analysis. Estimation models were validated using of Jackknife Cross-Validation procedure. Results show that the VH indices can be used for detection, and numerical estimate of the number of malaria cases. During the cooler months (January–April) when mosquitoes are less active, the correlation is low and increases considerably during the warm and wet season (April–November), for TCI in early October and for VCI in mid September. All analysis and estimation model developed here are based on data obtained for Bangladesh. | | Subject | : | Health and environmental sciences; Applied sciences; Bangladesh; Malaria; Vector-borne disease; Electrical engineering; Remote sensing; Public health; Analysis; 0799:Remote sensing; 0573:Public health; 0544:Electrical engineering | | Added Entry | : | L. Roytman | | Added Entry | : | City University of New York |
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