Neural network identifications of spectral signatures

摘要

We have investigated the application of neural nets to the determination of fundamental leaf canopy parameters from synthetic spectra. We describe some preliminary runs in which we separately determine leaf chemistry, leaf structure, leaf area index, and soil characteristics, and then we perform a simultaneous determination of all these parameters in a single neural network run with synthetic six-band Landsat data. We find that neural nets offer considerable promise in the determination of fundamental parameters of agricultural and environmental interest from broad-band multispectral data.