Nitrogen concentration estimation with hyperspectral LiDAR
Other literature type
(issn: 2194-9050, eissn: 2194-9050)
Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands
require more efficient and accurate methods. The first prototype of a full waveform hyperspectral Light Detection and Ranging
(LiDAR) instrument has been developed at the Finnish Geodetic Institute (FGI). The instrument efficiently combines the benefits of
passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point
which offers great potential in the field of remote sensing of environment. This study investigates the performance of the
hyperspectral LiDAR instrument in nitrogen estimation.
The investigation was conducted by finding vegetation indices sensitive to nitrogen concentration using hyperspectral LiDAR data
and validating their performance in nitrogen estimation. The nitrogen estimation was performed by calculating 28 published
vegetation indices to ten oat samples grown in different fertilization conditions. Reference data was acquired by laboratory nitrogen
concentration analysis. The performance of the indices in nitrogen estimation was determined by linear regression and leave-one-out
The results indicate that the hyperspectral LiDAR instrument holds a good capability to estimate plant biochemical parameters such
as nitrogen concentration. The instrument holds much potential in various environmental applications and provides a significant
improvement to the remote sensing of environment.