Gross primary production (GPP) is the total amount of atmospheric carbon (CO<sub>2</sub>) assimilated by vegetation. In this
article, a regional terrestrial ecosystem GPP estimation model REG-PEM(REGion Production Efficiency Model) is
developed based on light use efficiency theory, and 8-day composite and annual GPP are calculated using REG-PEM
model in Jiangxi province. The REG-PEM model was designed on the basis of the production efficiency concept in
which gross primary production is calculated from the products of the photosynthetically active radiation (PAR)
absorbed by the vegetation(APAR) and light use efficiency, and all the input data get from remote sensing method. GPP
are calculated using MODIS 8-day composite products and total ozone mapping spectrometer (TOMS) reflectance data
in Jiangxi province in 2003 and 2004. GPP increases in spring, reaches maximum in summer and decreases in autumn,
and fluctuates in the year. The results indicate that the REG-PEM model is capable of tracking seasonal dynamics and
interannual variations in GPP at a 8-day temporal resolution.
Land cover data are essential to most global change research objectives, including the assessment of current environmental conditions and the simulation of future environmental scenarios that ultimately lead to public policy development. Chinese Academy of Sciences generated a nationwide land cover database in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in 1990s. In order to improve the reliability of the database, we will update the database anytime. But it is difficult to obtain remote sensing data to extract land cover change information in large-scale. It is hard to acquire optical remote sensing data in Chengdu plain, so the objective of this research was to evaluate multitemporal ENVISAT advanced synthetic aperture radar (ASAR) data for extracting land cover change information. Based on the fieldwork and the nationwide 1:100000 land cover database, the paper assesses several land cover changes in Chengdu plain, for example: crop to buildings, forest to buildings, and forest to bare land. The results show that ENVISAT ASAR data have great potential for the applications of extracting land cover change information.