Estimating nitrogen in mixed forests from HyMap data using band-depth analysis and branch-and-bound algorithm

Spatial information of nitrogen concentration (Nc) is of great interest because of its role in photosynthesis, ecosystem productivity and thus influences global cycling of carbon and oxygen. Imaging spectroscopy offers a means to assess this compound. Nc was estimated in mixed forests in Switzerland from airborne HyMap data using band-depth analysis. Instead of stepwise regression, an exhaustive search algorithm has been applied to select significant wavebands in order to build relationships between transformed reflectance and fieldmeasured Nc. This study confirms that partitioning data into vegetation types yielded in higher R2. R2 was largest for the homogeneous coniferous sample. A preclassification of the HyMap images is therefore recommended. The tested branch-and-bound algorithm performed well in selecting important known nitrogen absorption wavebands. A comparison with other subset selection methods is planned