PROSPECT5耦合4SAIL模型的亚热带典型森林冠层反射率时间序列模拟

冠层反射率在森林植被类型精确解译、森林碳同化关键参数如叶面积指数(LAI)、叶绿素等遥感反演等方面具有重要意义.本研究以亚热带毛竹林、雷竹林和常绿落叶阔叶混交林3种典型森林类型为研究对象,通过耦合PROSPECT5和4SAIL模型模拟其冠层反射率时间序列.首先,对PROSPECT5和4SAIL模型参数进行敏感性分析,探讨模型参数对冠层反射率的影响;其次,利用实测反射率对不敏感参数进行优化,并确定其参数值;最后,耦合PROSPECT5和4SAIL模型模拟3种亚热带森林冠层反射率,并与MODIS反射率进行对比.结果表明:LAI对第1、2、3、5、7波段最敏感,各波段的总敏感指数分别为0.80、0.83、0.94、0.66、0.47;叶绿素含量对第4波段最敏感,总敏感指数为0.59;叶片含水量对第6波段的敏感性最大,总敏感性指数为0.54;叶子结构参数、类胡萝卜素、热点参数、干物质含量和土壤干湿比等参数对各个波段都不敏感或敏感性较小.优化后的PROSPECT5和4SAIL模型模拟得到的冠层反射率能够真实反映3种典型森林的季节性变化规律,通过与MODIS反射率对比分析发现,模拟冠层反射率和MODIS反射率之间具有较高的决定系数,分别为0.86、0.90、0.93,均方根误差(RMSE)也较小,分别为0.09、0.07、0.05,且模拟反射率能在一定程度上解决MODIS反射率数据冬季易受雨雪、混合像元影响等问题.

Simulating canopy reflectance time series for typical subtropical forest by coupling PROSPECT5 and 4SAIL models

Canopy reflectance has important meanings in the aspects of accurate interpretation of forest vegetation type and key parameter (leaf area index, chlorophyll content, etc.) retrieval of forest carbon assimilation. In this study, the canopy reflectance time series of three typical subtropical forests (moso bamboo forest, MBF; lei bamboo forest, LBF; evergreen and deciduous broadleaf forest, EDBF) was simulated by coupling PROSPECT5 and 4SAIL models. First, the sensitivity of parameters in PROSPECT5 and 4SAIL model was analyzed to discuss the effects of parameters on the canopy reflectance simulation. Second, unsensitive parameters were optimized using the observed reflectance. Finally, the canopy reflectances of three typical subtropical forests were simulated using PROSPECT5 and 4SAIL models, and compared with MODIS reflectance dataset. The results showed that leaf area index was most sensitive to bands 1, 2, 3, 5 and 7, with the total-order sensitivity indexes of 0.80, 0.83, 0.49, 0.66 and 0.47, respectively. Chlorophyll content was most sensitive to band 4, with the total-order sensitivity index of 0.59. Leaf water content was most sensitive to band 6, with the total-order sensitivity index of 0.54. Leaf structure, carotenoids content, dry matter content, hot parameter and soil factors were not/low sensitive to these bands. Canopy reflectance simulated using the optimized PROSPECT5 and 4SAIL models had the capability in reflecting the real seasonal changes of three typical subtropical forests. The simulated canopy reflectance significantly correlated with MODIS reflectance, with high R² of 0.86, 0.90, 0.93, and low root mean square of 0.09, 0.07, 0.05 for MBF, LBF, and EDBF, respectively. The simulated canopy reflectance solved to some extent the problems of influence on MODIS reflectance products by precipitation and snow in winter, and mixed pixels.