Dust storms are a common phenomenon faced by people in arid and semi-arid areas. They are responsible for not only increased air pollution, but also several environmental, health, economic, industrial, agricultural, and plant-related problems. In order to deal with this destructive phenomenon, the sources of dust and the unique characteristics of dust-prone areas should first be determined. Therefore, this study used combinations of remotely-sensed indices, e.g. normalized difference vegetation index (NDVI), land surface temperature (LST), vegetation dryness index (TDVI), normalized difference water index (NDWI), and rain use efficiency (RUE), and slope, wind erosion, and soil texture maps to identify the sources of dust in Isfahan Province, Iran. Remotely- sensed data were collected from MODIS aboard Aqua and Terra satellites during May 9 to October 8, 2013. After performing the required corrections, the RUE, NDVI, LST, TDVI, and NDWI were calculated. In order to detect dust, the 5.7.2009 event was selected and transformed into apparent temperature using thermal-infrared dust index (TDI) and Ackerman and Miller indices. These indices, determined based on a standard fuzzy method, ranged between zero and one and values closer to one indicated more undesirable conditions (in all maps). Finally, all maps were combined using five fuzzy methods, namely Gamma, Sum, And, Or, and Product. Gamma was the most effective method in the identification of dust-prone areas. According to the obtained results, dust centers in the province are located in Isfahan, Nain, Aran and Bidgol, Ardestan, Borkhar, and Khor and Biabanak. These areas are covered with a variety of geological features including desert lands, sand dunes, low-density gravel plains, poor rangelands, and abandoned agricultural lands. For instance, 11% of the identified sources include gypsum-clay pans, clay plains, salt marshes, and sand dunes in Isfahan, particularly Segzi region. Moreover, based on the assessment of meteorological data, the highest number of dusty days belonged to spring and summer. During these times, wind roses in some weather stations showed the direction of the dominant winds in the province as west. Overall, this study suggested the high potential of remote-sensing methods. Therefore, using a combination of remotely-sensed and meteorological data facilitated the exact identification of sources of dust. A comparison between the obtained results and MEDALUS desertification intensity maps showed a high correlation between the outputs (R = 0.71). There was also high consistency between our findings and the dust atlas of Isfahan Province. Following the identification of dust sources, relevant biological, chemical, and mechanical measures should be designed to tackle dust storms and prevent the expansion of the existing sources. Since increasing dust has turned into a major problem many provinces of Iran, the simple and accurate method proposed in this study can also be used for determining the sources of dust in other provinces. Keywords : Dust source identification, NDVI, LST, TVDI, RUE, Isfahan Province