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Vegetation productivity models and many others for hydrology and biogeochemistry studies require biophysical variables such as the leaf area index (LAI). LAI is part of the 13 essential terrestrial variables to monitor climate change. The index can be retrieved by various methods from optical satellite data and is a standard product in the MODIS processing chain at 1km spatial resolution. This study...
This paper proposes a novel approach for leaf area index (LAI) estimation based on vehicle-based laser scanning (VLS), which occurs as a state-of-the-art mapping technique. The method is advanced from the traditional terrestrial laser scanning (TLS), which has been primarily validated capable of predicting LAI. The associated schematic is to explore the correlations between VLS and TLS collections...
In this research, three field surveys were carried out in a typical semi-arid steppe in northern China, respectively on early July, late July and late August in 2008. During each survey, 80 plots established according to the cyclic sampling design were investigated, and three bio-parameters including LAI (Leaf Area Index), CWC (Canopy Water Content) and DW (Dry Weight) were measured. Temporalspecific...
In this study, optical remote sensing data were used for leaf area index (LAI) estimation. The LAI is an important measure to increase the yield and adjust the quantity of manure. LAI extracted from remotely sensed data may contribute to grasp the yield of rice at an early stage. Therefore, the purpose of this study is to estimate the LAI through remote sensing. For the purpose of our work, we proposed...
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