红外与毫米波学报, 2013, 32 (4): 372, 网络出版: 2013-08-28  

浑浊II类水体叶绿素a浓度遥感反演(II):MERIS遥感数据的应用

Remote sensing retrieval for chlorophyll-a concentration in turbid case II waters (II): application on MERIS image
作者单位
1 中国科学院南京地理与湖泊研究所 湖泊与环境国家重点实验室,江苏 南京210008
2 中国科学院研究生院,北京100049
摘要
基于2004~2010年太湖4次野外观测数据,结合MERIS遥感资料,评价两波段、三波段、改进三波段和四波段4个模型在浑浊II类水体叶绿素a浓度估算的精度,并利用太湖(13个有效样点)以及巢湖(21个有效样点)进行模型验证.结果表明,改进三波段模型反演叶绿素a浓度较高,更适于浑浊II类水体叶绿素a浓度的遥感反演,决定系数R2在0.34~0.94之间变化,RMSE变化范围为: 3.17~8.70 μg/L.分季节率定改进三波段模型参数,并建立太湖水体春、夏、秋、冬季的模型输入参数查找表,最终将改进三波段模型应用于MERIS遥感影像(8、9、10波段),获取太湖水体叶绿素a浓度的空间分布和年内、年际变化.
Abstract
Based on four filed cruises from 2004 to 2010 in Tai Lake, four models were investigated in the present study, including two-ration-model (TRM), three-band-model (TBM), enhanced three-band-model (ETM) and four-band model (FBM) using in situ measurements and MERIS image data. The validation was performed using samples from Taihu (n=13) and Chaohu Lake (n=21). The results demonstrated that the ETM was the most appropriate to estimate chlorophyll a concentration in highly turbid waters with higher R2(0.34~0.94) and lower RMSE (3.17~8.70 μg/L). Furthermore, the lookup table of the molding input parameters was determined for the four seasons in Taihu Lake. The resultant model was applied to MERIS images (8, 9 and 10 waveband) to detect the temporal and spatial variations of chlorophyll a concentration in Tai Lake.

姜广甲, 周琳, 马荣华, 段洪涛, 尚琳琳, 饶加旺, 赵晨露. 浑浊II类水体叶绿素a浓度遥感反演(II):MERIS遥感数据的应用[J]. 红外与毫米波学报, 2013, 32(4): 372. JIANG Guang-Jia, ZHOU Lin, MA Rong-Hua, DUAN Hong-Tao, SHANG Lin-Lin, RAO Jia-Wang, ZHAO Chen-Lu. Remote sensing retrieval for chlorophyll-a concentration in turbid case II waters (II): application on MERIS image[J]. Journal of Infrared and Millimeter Waves, 2013, 32(4): 372.

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