基于ZY-102D卫星影像非光合/光合植被覆盖度同步估算方法

Simultaneous Non-Photosynthetic Vegetation and Photosynthetic Vegetation Fractional Cover Estimation Using ZY-102D Satellite Imagery

以河北林-草交错带为研究区,借助地物光谱数据库非光合植被(Non-Photosynthetic Vegetation,NPV)、裸土(Bare Soil,BS)和光合植被(Photosynthetic Vegetation,PV)反射光谱数据,基于PV、NPV和BS三者在可见光-近红外(Visible and Near-Infrared,VNIR)范围光谱曲线形态差异,利用“资源一号”02D卫星高光谱相机(Advanced Hyperspectral Imager,AHSI)两个窄近红外谱段、多光谱相机(Visible Near-Infrared Camera,VNIC)两个宽近红外谱段(B8和B9),分别构建了NPV、PV和BS三者的光谱分离指数(Normalized Spectral Separation Index,NSSI),进一步结合归一化植被指数(Normalized Difference Vegetation Index,NDVI)构建的三角特征空间进行混合像元分解,实现NPV、PV和BS三组分覆盖度同步估算,并结合纤维素/木质素光谱指数(Cellulose Absorption Index,CAI),与基于AHSI短波红外谱段(Shortwave Infrared spectral bands,SWIR)估算非光合植被覆盖度能力进行对比分析。研究表明,结合NSSI可用于摆脱易受水分影响的短波红外谱段参与,可广泛应用于干旱和湿润地区植被遥感覆盖度估算。

In the study area of the forest-grass ecotone in Weichang County,Hebei Province,spectral reflectance data of non-photosynthetic vegetation(NPV),bare soil(BS),and photosynthetic vegetation(PV)were utilized from spectral libraries.Based on the spectral curve shape differences of PV,NPV,and BS in the visible and near-infrared(VNIR)range,two narrow near-infrared spectral bands from the ZY-102D satellite's Advanced Hyperspectral Imager(AHSI),as well as two wide near-infrared spectral bands(B8 and B9)from the multispectral camera,Visible Near-Infrared Camera(VNIC),were employed to construct the Normalized Spectral Separation Index(NSSI)for NPV,PV,and BS,respectively.Subsequently,by combining the triangular space constructed based on the Normalized Difference Vegetation Index(NDVI),pixel unmixing was conducted to simultaneously estimate the coverage of NPV,PV,and BS components.Additionally,NSSI was compared with Cellulose Absorption Index(CAI)to evaluate the capability of ZY-1 AHSI in estimating the coverage of non-photosynthetic vegetation in the Shortwave Infrared spectral bands(SWIR).The study demonstrates that the combination of NSSI can be utilized to overcome the influence of the shortwave infrared spectral band,which is easily being affected by water,in calculating non-photosynthetic vegetation coverage,thereby being widely applicable to vegetation remote sensing coverage estimation in both arid and humid regions.