Estimating Dry Matter Content of Poplar Leaf by Hyperspectral Data

doi:10.3969/j.issn.1000-6362.2017.01.006

Abstract

Abstract: In order to explore estimating the dry matter content of poplar leaves accurately, rapidly and accurately and nondestructive with hyperspectral data. Simulated values of poplar leave hyperspectral data which were leaf scales and canopy scales were obtained by PROSPECT and PROSAIL models which input parameters were measured by the physical and chemical data and soil background spectral data. At the same time, the dry matter content, equivalent water thickness and hyperspectral data were obtained from the measured leaf scales and canopy scales. Finally, the statistical methods were used to analyze the dry matter content in two scales of poplar leaves. The results showed that, the best band combination of the normalized difference vegetation index of dry matter was respectively band combination between 1685nm and 1704nm and band combination between 1551nm and 2143nm, respectively in leaf scales and canopy scales. Dry matter content models of leaf and canopy scales were built respectively by NDMI (1685,1704) and NDMI(1551,2143). The model validation accuracy of the leaf scale dry matter content was R2=0.663, RMSE=0.001g·cm-2, and the model validation accuracy of the canopy scale dry matter content was R2=0.91, RMSE=16.7g·m-2. Obviously, the hyperspectral technique has a high precision for estimating the dry matter content of poplar leaves, which can provide reference for the rapid and nondestructive estimation of dry matter content of poplar leaves.

Key words: Technology of hyperspectrum, Poplar, Dry matter content, Estimation model

CHENG Zhi-qing, ZHANG Jin-song, MENG Ping, LI Yan-quan, ZHENG Ning. Estimating Dry Matter Content of Poplar Leaf by Hyperspectral Data[J]. Chinese Journal of Agrometeorology, 2017, 38(01): 52-60.

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