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Evaluation of forest ecosystem services is a hot topic, both in China and at abroad, but it has not yet obtained a consistency of evaluation indicator systems and evaluation methods. Under the framework of evaluation criteria to be implemented for forest ecosystem services, years of consecutive observation data from Long Term Ecological Research Stations affiliated to Chinese Forest Ecosystem Research Network (CFERN), forest resource inventory and public data were applied to carry out a detailed and dynamic evaluation on the physical quantity and value of ecosystem services of Chinese pine forests in China. The results showed that the above services had the total value and unit value of 1144.9640 billion (1.1449640x10(12)) RMB and 52.074 thousand RMB per hectare per year, respectively during the 9th Five-year Plan (1996-2000), and of 1190.5461 billion RMB and 52.101 thousand RMB per hectare per year, respectively, during the 10th Five-year Plan (2001-2005). For Chinese pine forests, water conservation was 40.40 hundred million cubic meters annually, soil conservation was 67 million tons and C fixation 9 million tons annually, production of healthful negative ions was 1.96x10(20), absorption of SO(2) was 5.02 hundred million kilograms and dust-catching was 759.10 hundred million kilograms. Among the 15 provinces of China with Chinese pine forests, the biggest beneficiary from ecosystem services was Liaoning Province; while Hunan Province was the smallest beneficiary between the 9th Five-year Plan.

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The Chinese Gaofen-3 (GF-3) mission was launched in August 2016, equipped with a full polarimetric synthetic aperture radar (SAR) sensor in the C-band, with a resolution of up to 1 m. The absolute positioning accuracy of GF-3 is of great importance, and in-orbit geometric calibration is a key technology for improving absolute positioning accuracy. Conventional geometric calibration is used to accurately calibrate the geometric calibration parameters of the image (internal delay and azimuth shifts) using high-precision ground control data, which are highly dependent on the control data of the calibration field, but it remains costly and labor-intensive to monitor changes in GF-3’s geometric calibration parameters. Based on the positioning consistency constraint of the conjugate points, this study presents a geometric cross-calibration method for the rapid and accurate calibration of GF-3. The proposed method can accurately calibrate geometric calibration parameters without using corner reflectors and high-precision digital elevation models, thus improving absolute positioning accuracy of the GF-3 image. GF-3 images from multiple regions were collected to verify the absolute positioning accuracy after cross-calibration. The results show that this method can achieve a calibration accuracy as high as that achieved by the conventional field calibration method.