Paper
24 September 2013 Early warning of malaria at Bikaner, Rajasthan in India using AVHRR-based satellite data
Author Affiliations +
Abstract
A better understanding of the relationship between satellites observed vegetation health, and malaria epidemics could help mitigate the worldwide increase in incidence of mosquito-transmitted diseases. This research investigates last 17- years association between vegetation health (condition) index and malaria transmission in Bikaner, Rajasthan in India an arid and hot summer area. The vegetation health (condition) index, derived from a combination of Advanced Very High Resolution Radiometer (AVHRR) based Normalized Difference Vegetation Index (NDVI) and 10-μm to 11-μm thermal radiances, was designed for monitoring moisture and thermal impacts on vegetation health. We demonstrate that thermal condition is more sensitive to malaria transmission with different seasonal malaria activities. The weekly VH indices were correlated with the epidemiological data. A good correlation was found between malaria cases and Temperature Condition Index (TCI) one at least two months earlier than the malaria transmission season. Following the results of correlation analysis, Principal Component Regression (PCR) method was used to construct a model of less than 10% error to predict malaria as a function of the TCI.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Leonid Roytman, Mohammad Nizamuddin, Kawsar Akhand, Felix Kogan, and Mitchell Goldberg "Early warning of malaria at Bikaner, Rajasthan in India using AVHRR-based satellite data", Proc. SPIE 8871, Satellite Data Compression, Communications, and Processing IX, 88710F (24 September 2013); https://doi.org/10.1117/12.2022405
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Vegetation

Dysprosium

Satellites

Error analysis

Climatology

Radiometry

Humidity

Back to Top