Dark Dense Vegetation(DDV)method is most widely used for retrieving the atmospheric aerosol optical thickness from remote sensing images in recent years,in which automatically detecting the dark dense vegetation pixels is the primary basis.However,it is quite difficult to detect DDV pixels for the visible and near-infrared(VIS-NIR)images without the mid-infrared band.A new method was named red band histogram threshold method that was proposed in this paper to automatically detect the DDV pixels from VIS-NIR images at typical mountainous areas.Using the low reflectance of forest pixels in visible bands, the method searched for the first peak of red band reflectance histogram,and detected the DDV pixels by threshold value defined by the first peak.Results of the proposed method were presented for omlyLandsat- 5Thematic Mapper(TM)imagery using only the first four bands.The performance of the method was compared with mid-infrared threshold method and multiple thresholds method,which were widely used in the imagery with mid-infrared band and VIS-NIR imagery respectively.Then the proposed method in this paper was applied to HJ satellite CCD imagery to detect DDV pixels and retrieve aerosol optical thickness. Results show that the proposed method evidently is better than the multiple threshilds method,and its accuracy is very close to the Mid-infrared threshold method.The proportion of DDV pixels whose similarity index is less than 2 and less than 3 were 83.12% and 93.48% respectively.It is a new robust method applicable for automatic detection of DDV pixels for VIS-NIR images at typical mountainous areas,and meets the need for the DDV method to retrieve aerosol optical thickness.