Sudden death syndrome (SDS) is a soil borne disease, caused by the pathogen Fusarium virguliforme (Aoki and O’Donnell). This disease can be extremely detrimental to the soybean crop by decreasing yields and causing premature plant death. The most evident symptomology is the interveinal chlorosis and subsequent necrosis in the trifoliate leaves. This study is will determine the most efficient way to capture multispectral and color imagery by utilizing an Unmanned Aerial Vehicle (UAV). The objectives of this research are to quantify the changes in color and pattern associated with the symptoms of plant disease, to determine the correlation between vegetation reflectance and disease severity, and evaluate the advantages and disadvantages of using high resolution and multispectral imagery to assess disease. During the growing season, SDS disease ratings were collected to determine the incidence and severity. Sensors were used to capture imagery throughout the growing season. The multispectral imagery was used to create indices to determine which had the highest correlation to the ground disease ratings. ArcGIS indices were created to determine which index correlates best with the disease ratings in the field.