Hyperspectral indices and forest characteristics

The quantification of forest characteristics at different scales is key to understanding how forest ecosystems function. Hyperspectral imagery may provide information to quantitatively estimate some biochemical (e.g. chlorophyll or nitrogen content), structural (e.g. leaf area index) or physiological (e.g. light use efficiency) forest characteristics at different scales, but this information is not easily retrievable. The simple reflectance index concept has been inherited from a long history of multispectral data analysis, and is commonly transposed to hyperspectral data. The design and use of such hyperspectral indices is questioned in this study.