There is interest in mapping open water bodies using remote sensing data. Coverage and persistence of open water is currently a poorly measured variable due to its spatial and temporal variability across landscapes, especially in remote areas. The presence and persistence of open water is one of the primary indicators of conditions suitable for mosquito breeding habitats. Predicting the risk of mosquito caused disease outbreaks is a required step towards their control and eradication. Satellite observations can provide needed data to support agency decisions for deployment of preventative measures and control resources. This study, which will try to map open water bodies with satellite data, will be carried out using a decision tree based open source software algorithm called Random Forests to find correlations between the remote sensing data and open water bodies and their color properties. Software has been written in R to ingest data from the Landsat 7 satellite, convert it into an R data frame, input it into the Random Forest Software algorithm and output a classification of open water bodies and their color properties. Knowledge of the location and color properties of open water bodies and their dynamic nature can be used as early warning indicators for mosquito caused disease outbreaks
