|
|
|
|
|
|
| Sensitivity Analysis of Spectral Band Adjustment Factors For GF-1/WFV Sensor Cross-Calibration |
| ZHOU Ke1, 2, 3, 5, LIU Li4*, YU Tao1, 3, GU Xing-fa1, 3, ZHENG Feng-bin5, ZANG Wen-qian1, 3 |
1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. The Center for National Spaceborne Demonstration, Beijing 100101, China
4. China Center for Resources Satellite Data and Application, Beijing 100094, China
5. College of Computer &Information Engineering，Henan University, Kaifeng 475004, China |
|
|
|
|
Abstract Affected by the components aging and the space environment changing, the radiation performance of the first satellite , GaoFen series (GF-1) changes since it has been launched. The orbit calibration can track the performance changing during the sensor’s lifetime. Cross calibration using the high radiometric calibration precision can improve the calibration frequency and accuracy. Spectral band adjustment factors (SBAF) are important factors in cross calibration. Terra / MODIS is selected as reference sensor, GF-1 / WFV as target sensor, and the SBAF can be calculated based on the in situ measurement spectral data at Dunhuang radiometric calibration site, considering the observation angle, spectral response, atmospheric conditions and surface properties. Time series cross calibration coefficients can be obtained according to the SBAF. GF-1/WFV apparent radiances are obtained by the cross calibration coefficients, while Terra/MODIS apparent radiances are obtained by the digital number and calibration coefficients. The relative deviations of apparent radiances between the two sensor’s are compared by analysis. It shows that SBAF in different bands has same trends; The SBAF above 0.9 are 53.1%, 75%, 81.2%, 93.8% for blue, green, red, near-infrared bands, respectively; Time series calibration coefficients and SBAF are negatively correlated and the relative deviations of apparent radiances are smaller while the SBAF are closer to 1.
|
|
Received: 2015-03-13
Accepted: 2015-10-22
|
|
|
|
Corresponding Authors:
LIU Li
E-mail: liulicugb@126.com
|
|
[1] BAI Zhao-guang(白照广). Aerospace China (中国航天)，2013, 8: 5.
[2] Chander G, Hewison T J, Fox N, et al. IEEE Transactions on Geoscience and Remote Sensing，2013, 51(3): 1056.
[3] Teillet P M, Slater P N, Ding Y，et al. Remote Sensing of Environment. 1990, 31：105.
[4] Thome K J, Biggar S, Slater P. SPIE, 2001, 4540: 260.
[5] Cao C Y, Hui Xu, Jerry Sullivan，et al. Journal of Atmospheric and Oceanic Technology, 2005, 22: 381.
[6] YANG Zhong-dong，GU Song-yan，QIU Hong，et al(杨忠东, 谷松岩, 邱 红, 等). Journal of Remote Sensing(遥感学报), 2004, 8(2): 113.
[7] TONG Jin-jun，QIU Kang-mu，LI Xiao-wen，et al(童进军, 邱康睦, 李小文，等). Journal of Remote Sensing(遥感学报), 2005, 9(4): 349.
[8] LI Xiao-ying，GU Xing-fa，MIN Xiang-jun，et al(李小英, 顾行发, 闵祥军，等). Science China Information Sciences(中国科学：信息科学)，2005, 35(增刊Ⅰ): 41.
[9] GAO Hai-liang，GU Xing-fa，YU Tao, et al(高海亮，顾行发，余 涛, 等). Acta Geodaetica et Cartographica Sinica(测绘学报)，2011，40(2)：180.
[10] Xiong X X, William B. Advances in Atmospheric Sciences，2006，23(1): 69.
[11] Xiong X X, Sun J Q, Barnes W，et al. IEEE Transactions of Geoscience and Remote Sensing，2007，45(4): 879. |
| [1] |
XU Kai-jian1, 2, TIAN Qing-jiu1, 2*, XU Nian-xu1, 2, YUE Ji-bo1, 2, TANG Shao-fei1, 2. Classifying Forest Dominant Trees Species Based on High Dimensional Time-Series NDVI Data and Differential Transform Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(12): 3794-3800. |
| [2] |
GUO Jun-jie1, 2, 3, YAO Zhi-gang2, 3, 4*, HAN Zhi-gang2, 3, ZHAO Zeng-liang2, 3, YAN Wei1. Inter-Calibration for TG-2/MAI Visible Band Based on Metop-B/GOME-2[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(01): 56-64. |
| [3] |
SUN Gui-fen1, QIN Xian-lin1*, YIN Ling-yu1, LIU Shu-chao1, LI Zeng-yuan1, CHEN Xiao-zhong2, ZHONG Xiang-qing2. Changes Analysis of Post-Fire Vegetation Spectrum and Index Based on Time Series GF-1 WFV Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(02): 511-517. |
| [4] |
YANG Yan-jun1,2, HUANG Yan1,2, TIAN Qing-jiu1,2*, WANG Lei1,2, GENG Jun1,2, YANG Ran-ran1,2. The Extraction Model of Paddy Rice Information Based on GF-1 Satellite WFV Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(11): 3255-3261. |
| [5] |
XU Na1, 2, HU Xiu-qing1, 2*, CHEN Lin1, 2, ZHANG Yong1, 2 , HU Ju-yang1, 2, SUN Ling1, 2 . On-Orbit Radiometric Calibration Accuracy of FY-3A MERSI Thermal Infrared Channel[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(12): 3429-3434. |
| [6] |
ZHANG Xue-wen, FU Qiao-yan, HAN Qi-jin*, PAN Zhi-qiang, YANG Lei . The Field Radiometric Calibration and Validation of ZY-3 Multispectral Sensor [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(09): 2476-2480. |
| [7] |
ZHOU Guan-hua1,2, JIANG He1,2, ZHAO Hui-jie1,2*, JIA Fei1,2 . Imaging Spectrometry Radiometric Cross-Calibration Based on Precise Spectral Response Matching [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(12): 3416-3421. |
| [8] |
HU Xiu-qing1，2,LIU Jing-jing2,QIU Kang-mu2,FAN Tian-xi2,ZHANG Yu-xiang2,RONG Zhi-guo2,ZHANG Li-jun2 . New Method Study of Sites Vicarious Calibration for SZ-3/CMODIS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(05): 1153-1159. |
|
|
|
|
