Characterizing Open Water Bodies and Their Color Properties Through Optical Remote Sensing to Identify Areas of Vector-Borne Disease Risk

Abstract:

Predicting the risk of vector-borne disease outbreaks is a required step towards their control and eradication. Satellite observations can provide needed data to support agency decisions with respect to deployment of preventative measures and control resources.

The coverage and persistence of open water is one of the primary indicators of conditions suitable for mosquito breeding habitats. This is currently a poorly measured variable due to its spatial and temporal variability across landscapes, especially in remote areas. Here we develop a methodology for monitoring these conditions through optical remote sensing images from Landsat. We pansharpen the images and apply a decision tree classification approach using Random Forests to generate 15 meter resolution maps of open water. In addition, since some mosquitos breed in clear water while others in turbid water, we classify water bodies according to their water color properties and we validate the results using field knowledge. We focus in East Africa where we assses the usefulness of these products to improve prediction of malaria outbreaks.

Portions of this work were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.