Potential of Spectral Feature Analysis to Estimate Nitrogen Concen-tration in Mixed Canopies (original) (raw)

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 field-measured Nc. This study confirms that partitioning data into vegetation types yielded in higher R 2 . R 2 was largest for the homogeneous coniferous sample. A pre-classification 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.

ABSTRACT. Remote sensing technologies are recognized as an efficient tool for getting information about land covers and have a wide range of investigation and application fields. In agriculture, remotely sensed data are used for plant growth monitoring, precision agriculture running and yield prediction. The interpretation of airborne and satellite data require explicit apriory information about crop spectral behaviour under different conditions. Besides, the necessity to use various geoinformation technologies incorporating remote sensing and in-situ observations, ancillary data and etc., imposes data integration and sharing between different data sources. The paper is devoted to ground-level spectrometric studies as an integral part of remotely sensed data analysis.

A nitrogen status map reflecting the spatial variability of the nitrogen supply within a field is a useful tool for farmers to adjust their fertiliser input based on the actual needs of the plants. In particular, there is potential to accurately predict nitrogen need at each point in the field to reduce surplus nitrogen in the crop production system without reducing crop yield. Remote sensing collects spatially dense information that may contribute to nitrogen variable rate application within the precision farming concept. Plant spectral properties reflect crop nitrogen status and can be used for spectral determination of nitrogen content. The aim of this study is the analysis of the relationship between spectral reflectance measurements and nitrogen content of wheat canopies. For this purpose reflectance measurements of wheat canopies from four different fields have been acquired over a full phenological cycle using an ASD FieldSpec II spectroradiom eter. The nitrogen content of th...