CAJ | 학술논문

为确定适合太湖水体叶绿素的反演算法，为同类卫星数据的建模和应用提供参考，本文根据太湖2007年11月、2009年4月和2011年8月实测水质参数以及同步光谱数据，结合水色遥感传感器MODIS、MERIS、GOCI及我国自主发射的HJ-1号卫星CCD传感器波段参数，基于差值模型、比值模型、三波段模型及APPEL模型，分别建立太湖水体叶绿素浓度反演模型，并分析模型的适宜性．结果显示，基于不同传感器数据APPEL模型的决定系数为0．7308～0．8107，模型相对误差为15％～24％，均方根误差为21％～32％；三波段模型基于不同传感器数据拟合的决定系数为0．6014～0．7610，相对误差为28％～36％，相对均方根误差为39％～46％；差值模型决定系数为0．4954～0．7244，相对误差为39％～53％，相对均方根误差为51％～72％；比值模型决定系数为0．4918～0．7098，相对误差为41％～55％，相对均方根误差为56％～75％．相比较而言，APPEL模型的稳定性较强，适合于不同传感器数据的太湖水体叶绿素浓度的反演．此外，相应不同传感器波段位置、波段宽度对模型反演的精度和稳定性的影响也不同，当波段位置接近叶绿素特征波长时，较窄的波宽有利于模型精度的提高，波段位置和叶绿素浓度特征波长相差较大时，合理增加波谱范围有利于叶绿素特征信息的获取．
위학정괄합태호수체협록소적반연산법，위동류위성수거적건모화응용제공삼고，본문근거태호2007년11월、2009년4월화2011년8월실측수질삼수이급동보광보수거，결합수색요감전감기MODIS、MERIS、GOCI급아국자주발사적HJ-1호위성CCD전감기파단삼수，기우차치모형、비치모형、삼파단모형급APPEL모형，분별건립태호수체협록소농도반연모형，병분석모형적괄의성．결과현시，기우불동전감기수거APPEL모형적결정계수위0．7308～0．8107，모형상대오차위15％～24％，균방근오차위21％～32％；삼파단모형기우불동전감기수거의합적결정계수위0．6014～0．7610，상대오차위28％～36％，상대균방근오차위39％～46％；차치모형결정계수위0．4954～0．7244，상대오차위39％～53％，상대균방근오차위51％～72％；비치모형결정계수위0．4918～0．7098，상대오차위41％～55％，상대균방근오차위56％～75％．상비교이언，APPEL모형적은정성교강，괄합우불동전감기수거적태호수체협록소농도적반연．차외，상응불동전감기파단위치、파단관도대모형반연적정도화은정성적영향야불동，당파단위치접근협록소특정파장시，교착적파관유리우모형정도적제고，파단위치화협록소농도특정파장상차교대시，합리증가파보범위유리우협록소특정신식적획취．
In order to determine the most suitable retrieval model for estimating chlorophyll concentration in Lake Taihu and provide a reference for the application of the satellite data, the difference model, the ratio model, the three-band model and APPEL model were built to estimate chlorophyll concentration based on the data of MODIS , MERIS, GOCI and HJ-1 CCD sensor.The dataset in-cluded the measured water quality parameters and the synchronous spectra data in November 2007, April 2009 and August 2011. The results of the analysis showed that the decision coefficient of the APPEL model was between 0.7308 and 0.8107 for the differ-ent satellite data, the relative error was between 15% and 24%, and the root mean square error was between 21% and 32%;The decision coefficient of the three-band model was between 0.6014 and 0.7610, the relative error was between 28% and 36%, and the root mean square error was between 39% and 46%; The decision coefficient of different models was between 0.4954 and 0.7244, the relative error was between 39% and 53%, and the root mean square error was between 51% and 72%;The decision coefficient of the ratio model was between 0.4918 and 0.7098, the relative error was between 41% and 55%, and the root mean square error was between 56% and 75%.To sum up, the APPEL model showed a strong stability and was suitable for the chloro-phyll concentration retrieval of Lake Taihu for different sensor data.In addition, different band widths and band positions had dif-ferent influences on the retrieval model for estimating chlorophyll concentration .When the band position was close to the character-istic wavelength of chlorophyll, narrow band width was beneficial for the accuracy of the model;while when the band position was far away from the position of the characteristic wavelength, the band width should be increased reasonably.