This tool produces maps of estimated vegetation using data from NASA's MODIS sensor.
In some semi-arid regions of eastern Africa, precipitation has been found to have a 2-3 month lagged correlation with malaria incidence. Due to the lack of station data and because of the lagged nature of precipitation yielding lagged plant growth, vegetation indicies have been used as a proxy measure to forecast malaria.
Two vegetation indices are provided: NDVI, EVI in addition to the reflectance values for the blue, red, near infrared and middle infrared channels. Each index is derived from data provided from The Moderate Resolution Imaging Spectrometer (MODIS), a key instrument aboard NASA's Terra and Aqua satellites.
NDVI and EVI are useful to estimate the presence of vegetation, but are subject to intrinsic commission and omission errors which lead to potential misrepresentation of land surfaces. To improve the retrieval of vegetation properties, reflectance values in the Blue, Red, near-Infrared (NIR) and Middle Infrared (MIR) channels can be used.
Images are available for western Africa, eastern Africa and southern Africa.
Ceccato, P., et al. (2007). Malaria stratification, climate, and epidemic early warning in Eritrea.. International Geoscience and Remote Sensing Symposium (IGARSS) pp. 178-180 American Journal of Tropical Medicine and Hygiene, 2007.
Contact help@iri.columbia.edu with any technical questions or problems with this Map Room, for example, the forecasts not displaying or updating properly.
The MODIS interface provides the ability to make graphs at a user-selected location across different resolutions of spatial averaging. The interface consists of a clickable map that allows users to generate customized time series graphs. When a desired location is clicked, 2 time series graphs will provide vegetation analyses of the past year and in comparison to the 5 most recent years.
By placing current vegetation in recent historical context, comparisons can be made to past outbreaks and useful early warning information can be developed for epidemic prone regions.