Wavelet Vegetation Index to Improve the Inversion Accuracy of Leaf V25cmax of Bamboo Forests

Maximum carboxylation rate (Vcmax) is a key parameter to characterize the forest carbon cycle process. Hence, monitoring Vcmax of different types hot research topic at home and abroad, hyperspectral remote sensing an important technique for inversion. Moso bamboo unique type with high sequestration capacity in subtropical regions, but lack data major limitation accurately modeling cycling processes moso forests. Our study area was selected sink base Shanchuan Township, Anji County, Zhejiang Province, China, which has typical climate widely distributed In this study, reflectance V25cmax (Vcmax converted 25 °C) leaves newborn (I du bamboo) 2- 3-year-old (II were measured canopy positions, i.e., top, middle bottom, forest. Then, we applied discrete wavelet transform (DWT) obtained leaf construct vegetation index (WVI), analyzed relationship between WVI V25cmax, compared existing (HVI). The ability interpreted. Finally, partial least squares regression (PLSR) method used model invert leaves. We showed following: (1) There are significant differences I II bamboo, there also bottom positions bamboo. (2) Compared that HVI, detection wavelength expanded shortwave infrared region, thus had higher correlation V25cmax. absolute value coefficient SR2148,2188 constructed by cD1 0.75, DVI2069,407 cD2 0.67. highest three 13–21% than HVI. longest 2441 nm. (3) validation accuracies inversion models as variable all those HVI ages R2 0.97 reduction 20–60% root mean square error (RMSE) value. After decomposition leaves, low-frequency components contained no noise, high-frequency highlighted original spectral detail features. these increases range interpretation. Therefore, retrieval based on encompasses resolutions levels characteristics, can better reflect changes provide new forests sensing.