Scientific investigations indicate that global change information can be derived from the 1 km advanced very high resolution radiometer （AVHRR） data from NOAA satellite series. This paper describes the processing chain of China territory 1-km AVHRR dataset and its applications. Twelve years of AVHRR raw data from 1991 to 2003 have been collected. A dataset of over 9000 AVHRR raw images has been archived. These images cover China territory and the sensor includes AVHRR/2 and AVHRR/3 from NOAA-12 to NOAA-16. The processing algorithms are solicited and applied to the dataset to produce prototype and operational high level products for regional geo-science research. The processing chain uses an improved calibration method

which accounts for sensor degradation

and uses the SMAC （Simplified Method for Atmospheric Correction） method for atmospheric correction of the reflectance measured in AVHRR channels 1 and 2. The ozone data comes from TOMS （Total Ozone Mapping Spectrometer） daily measurements

the daily water vapor and surface pressure are obtained from the CMA （China Meteorological Administration） and the daily aerosol optical depth at a wavelength of 550 nm is retrieved from the ground visibility using a parameterization method. The BRDF correction in AVHRR imagery is performed and the parameters required is derived from the 1∶1

000

000 scale land cover types of China. For cloud detection

the CLAVR algorithm is applied but some parameters are modified for China territory

it uses all five AVHRR channels to estimate cloud cover through a series of tests and the tests are done sequentially using threshold values. LST （Land Surface Temperature） is determined using semi-empirical method （the split window method） and separatively accounting for atmospheric attenuation and soil emissivity. Daily data are composed with MVC （Maximum NDVI Composite of 10 days NDVI data）. The processing chain outputs are surface reflectance in channel 1 and 2

brightness temperature in channels 3-5

cloud （contaminated pixel） mask associated with each pixel

land surface temperature

and NDVI. The dataset products have been used for various studies like crop condition monitoring.