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FY-1C CAVHRR归一化植被指数(NDVI)衰减订正方法研究
引用本文:谷松岩,范天锡,张文建,闫静.FY-1C CAVHRR归一化植被指数(NDVI)衰减订正方法研究[J].应用气象学报,2003,14(5):562-567.
作者姓名:谷松岩  范天锡  张文建  闫静
作者单位:1.北京大学物理学院大气科学系, 北京 100871
基金项目:国家自然科学基金项目 ( 90 1 0 2 0 1 0 )资助
摘    要:利用FY-1C连续3年的CAVHRR资料,以敦煌辐射校正场为分析区,分析了CAVHRR可见光、近红外通道的通道衰减特征,开展了归一化植被指数(NDVI)衰减订正方法研究及衰减订正试验。分析结果表明,FY-1C可见光通道1的衰减使FY-1C全球及区域NDVI的分布特征出现不合理。以敦煌辐射校正场为参考目标,借助敦煌目标区通道反射率长时间变化特征分析,可以建立NDVI的时变订正模型,有效订正通道衰减引起的NDVI的不合理性。利用敦煌NDVI值稳定不变的特性得到的FY-1C扫描辐射计通道1更新定标系数,与2000年9月中国辐射校正场外定标试验结果一致。研究结果有助于提高FY-1C可见光、近红外通道遥感资料在环境遥感监测方面的定量应用精度。

关 键 词:通道衰减    NDVI    订正
收稿时间:2002-08-08
修稿时间:2002年8月8日

Improved NDVI of FY-1C CAVHRR
Gu Songyan , Fan Tianxi Zhang Wenjian Yan Jing.Improved NDVI of FY-1C CAVHRR[J].Quarterly Journal of Applied Meteorology,2003,14(5):562-567.
Authors:Gu Songyan  Fan Tianxi Zhang Wenjian Yan Jing
Institution:1.Atmospheric Department of Peking University, Beijing, 1008712.National Satellite Meteorology Center, Beijing, 100081
Abstract:An analysis of the NDVI and the calibration coefficients used to describe sensor degradation in Channel 1 of the Chinese Advanced Very High Resolution Radiometer (CAVHRR) boarding on the FY 1C spacecraft are presented. The radiometrically stable permanent sand of Dunhuang is used as a target to characterize sensor performance, and remote sensing data of CAVHRR over Dunhuang during 3 years was used. The analysis results show that the degradation in Channel 1 of FY 1C made the distribution of FY 1C NDVI all over the world fuzzy and cannot show the situation of canopy growing. Corrected model for NDVI and calibration formulae for Channel 1 of FY 1C CAVHRR constructed from Dunhuang reflectivity and NDVI database can improve the FY 1C global NDVI distribution. The relationship improving with time for NDVI and calibration coefficients for Channel 1 of FY 1C was derived from this researching work. The improved new calibration coefficients for CAVHRR Channel 1 have a great correspondence with the results of CRCS in 2000. It is recommended that the derived model and coefficients are helpful to improve the quantity application of FY 1C global remote sensing data.
Keywords:Sensor degradation  NDVI  Improved calibration coefficients
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