Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT w...Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.展开更多
【目的】建立快速、无损监测棉花冠层等效水厚度(canopy equivalent water thickness,CEWT)的估算模型,进一步提高利用高光谱遥感技术监测棉花CEWT的估算精度。【方法】通过在不同生育期设置灌溉梯度试验,于棉花蕾期和花铃期同步测定冠...【目的】建立快速、无损监测棉花冠层等效水厚度(canopy equivalent water thickness,CEWT)的估算模型,进一步提高利用高光谱遥感技术监测棉花CEWT的估算精度。【方法】通过在不同生育期设置灌溉梯度试验,于棉花蕾期和花铃期同步测定冠层光谱反射率、冠层等效水厚度等信息,综合分析棉花冠层等效水厚度与原始光谱反射率、一阶导数光谱反射率、全波段组合光谱指数、已有光谱指数的相关性,确定蕾期、花铃期及全生育期的最优光谱指数,并通过线性回归构建棉花CEWT的高光谱监测模型。【结果】冠层等效水厚度与原始光谱反射率在近红外波段(NIR)780—1130 nm和短波红外波段(SWIR)1450—1830 nm、1950—2450 nm附近均出现连续的敏感波段,一阶导数光谱在NIR波段内对CEWT的敏感程度较原始光谱有所加强,但在SWIR波段内敏感程度弱于原始光谱;利用原始光谱反射率构建的光谱指数与CEWT的相关性强于一阶导数光谱,且比值光谱指数(RSI)较归一化差分光谱指数(NDSI)更适合CEWT的监测。在全生育期内(R1135-5R1494)/R2003对CEWT的反演精度最佳(R2=0.7878,RRMSE=0.1803);在蕾期RSIb(1130,1996)对CEWT的估算效果最好(R2=0.7258,RRMSE=0.1444);在花铃期RSIa(904,1952)是估算CEWT的最优光谱指数(R2=0.7853,RRMSE=0.2454)。【结论】该研究在不同生育阶段内提出的新型高光谱指数均可用于棉花冠层等效水厚度的定量监测,研究结果可为高光谱技术在棉花冠层水分含量监测中的应用提供参考,为棉花精准灌溉提供技术依据。展开更多
基金funded by the National Natural Science Foundation of China(42071300)the Fujian Province Natural Science(2020J01504)+4 种基金the China Postdoctoral Science Foundation(2018M630728)the Open Fund of Fujian Provincial Key Laboratory of Resources and Environment Monitoring&Sustainable Management and Utilization(ZD202102)the Program for Innovative Research Team in Science and Technology in Fujian Province University(KC190002)the Open Fund of University Key Lab of Geomatics Technology and Optimize Resources Utilization in Fujian Province(fafugeo201901)supported by the Research Project of Jinjiang Fuda Science and Education Park Development Center(2019-JJFDKY-17)。
文摘Biochemical components of Moso bamboo(Phyllostachys pubescens)are critical to physiological and ecological processes and play an important role in the material and energy cycles of the ecosystem.The coupled PROSPECT with SAIL(PROSAIL)radiative transfer model is widely used for vegetation biochemical component content inversion.However,the presence of leaf-eating pests,such as Pantana phyllostachysae Chao(PPC),weakens the performance of the model for estimating biochemical components of Moso bamboo and thus must be considered.Therefore,this study considered pest-induced stress signals associated with Sentinel-2A/B images and field data and established multiple sets of biochemical canopy reflectance look-up tables(LUTs)based on the PROSAIL framework by setting different parameter ranges according to infestation levels.Quantitative inversions of leaf area index(LAI),leaf chlorophyll content(LCC),and leaf equivalent water thickness(LEWT)were derived.The scale conversions from LCC to canopy chlorophyll content(CCC)and LEWT to canopy equivalent water thickness(CEWT)were calculated.The results showed that LAI,CCC,and CEWT were inversely related with PPC-induced stress.When applying multiple LUTs,the p-values were<0.01;the R2 values for LAI,CCC,and CEWT were 0.71,0.68,and 0.65 with root mean square error(RMSE)(normalized RMSE,NRMSE)values of 0.38(0.16),17.56μg cm-2(0.20),and 0.02 cm(0.51),respectively.Compared to the values obtained for the traditional PROSAIL model,for October,R2 values increased by 0.05 and 0.10 and NRMSE decreased by 0.09 and 0.02 for CCC and CEWT,respectively and RMSE decreased by 0.35μg cm-2 for CCC.The feasibility of the inverse strategy for integrating pest-induced stress factors into the PROSAIL model,while establishing multiple LUTs under different pest-induced damage levels,was successfully demonstrated and can potentially enhance future vegetation parameter inversion and monitoring of bamboo forest health and ecosystems.
