Stephen Reames

Detecting Disease: by Unifying Two Methods of Remote Sensing Stephen Reames

There is currently no effective tool available to quickly and economically measure a change in landmass in the setting of biomedical professionals and environmental specialists. The purpose of this study is to structure and demonstrate a statistical change- detection method using remotely sensed data that can detect the presence of an infectious land borne disease. Data sources included the Texas Department of Health database, which provided the types of infectious land borne diseases and indicated the geographical area to study. A method was developed to identify statistically the severity of changes of the landmass over a three-year period. Data analysis included using a unique statistical detection procedure to measure the severity of change in landmass when a disease was not present and when the disease was present. The statistical detection method was applied to two different remotely sensed platform types and again to two like remotely sensed platform types. The results indicated that when the statistical change detection method was used for two different types of remote sensing mediums (i.e.- digital orthophoto quadrangle and aerial videography)