Foliar chemistry estimation with imaging spectroscopy and LiDAR data
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Imaging spectroscopy (IS) and light detection and ranging (LiDAR) data were used to model the foliar N:P ratio, macronutrients (N, P, K, Ca, Mg) and chlorophyll in a boreal forest canopy in northern Ontario, Canada.Measurement of both foliar macronutrients and foliar chlorophyll provides critical information about plant physiological and nutritional status, stress, as well as ecosystem processes such as carbon (C) exchange (photosynthesis and net primary production), decomposition and nutrient cycling.Results show that airborne and spaceborne IS data explained approximately 70% of the variance...
Imaging spectroscopy (IS) and light detection and ranging (LiDAR) data were used to model the foliar N:P ratio, macronutrients (N, P, K, Ca, Mg) and chlorophyll in a boreal forest canopy in northern Ontario, Canada.Measurement of both foliar macronutrients and foliar chlorophyll provides critical information about plant physiological and nutritional status, stress, as well as ecosystem processes such as carbon (C) exchange (photosynthesis and net primary production), decomposition and nutrient cycling.Results show that airborne and spaceborne IS data explained approximately 70% of the variance in the canopy N:P ratio with prediction errors of less than 8% in two consecutive years.LiDAR models explained more than 50% of the variance in the canopy N:P ratio with similar prediction errors.Predictive models using spaceborne Hyperion IS data were developed with adjusted R2 values of 0.73, 0.72, 0.62, 0.25, and 0.67 for N, P, K, Ca and Mg, respectively and the LiDAR model explained 80%of the variance in canopy Ca concentration.Two IS derivative indices (D705/D722 and Dmax(680-750))/D703) emerged as good predictors of chlorophyll concentration across time and space.
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