An algorithm for detection of yellow sand aerosols has been developed with infrared bands. This algorithm is a hybrid algorithm that has used two methods combined. The first method used the differential absorption in brightness temperature difference between $11{mu}m;and;12{mu}m;(BTD1)$. The radiation at $11{mu}m$ is absorbed more than at $12{mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{mu}m;and;11{mu}m(BTD2)$. This technique is sensitive to dust loading, which the BTD2 is enhanced by reflection of $3.7{mu}m$ solar radiation. First the Principle Component Analysis (PCA), a form of eigenvector statistical analysis from the two methods, is performed and the aerosol pixel with the lowest 10% of the eigenvalue is eliminated. Then the aerosol index (AI) from the combination of BTD 1 and 2 is derived. We applied this method to Multi-functional Transport Satellite-l Replacement (MTSAT-1R) data and obtained that the derived AI showed remarkably good agreements with Ozone Mapping Instrument (OMI) AI and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth.