As a newly launched earth observing satellite of China

the GF-1 satellite is intended to be applied for land resource

agriculture

and environment protection. This satellite contains four wide field viewing cameras that have a spatial resolution of16 m at nadir. For the application of 16 m cameras

the aerosol monitoring research need to be processed as soon as possible. This study investigated the application of dark dense vegetation to the 16 m camera of GF-1.First

blue-only algorithm was compared with blue and red algorithm with simulation retrieval based on the ground-based measurements of the typical vegetation surface spectrum. A linear relationship exists between blue and red vegetation surfaces. Thus

compared with the blue-only algorithm

the blue and red algorithm can remove land surface influence better from the top of the atmosphere reflectance. During retrieval

atmosphere correction needs to be performed to remove false dark targets

which are caused by the decrease of Normalized Difference Vegetation Index with the increase of Aerosol Optical Depth（ AOD）.Tianjin

which is located in the north of China

was selected as the area of the retrieval experiment

which was conducted from August 2013 to October 2013. The result shows that aerosol distribution can be monitored efficiently by using GF-1 16 m cameras.However

the result is partly affected by cloud and haze

which restrict the capability of these cameras. The algorithm is validated by ground-based measurements of a handheld sun photometer in the west of Tianjin and the Beijing site of AERONET. Satelliteretrieved measurements demonstrate good agreement with ground-based measurements

and the correlation coefficient is greater than0. 8.Error analysis shows that:（ 1） If the viewing zenith angles of the entire image are set to the same value

the retrieved AOD error can be maximized to 0. 3;（ 2） Calibration accuracy influences retrieved accuracy

and when the calibration error is lower than 3%

the retrieved error is lower than 10%;（ 3） Urban aerosol can cause a large retrieval error.