Usage of Airborne Hyperspectral Imaging Data for Identifying Spatial Variability of Soil Nitrogen Content

Soil is a significant natural resource composed of organic and inorganic material. Nitrogen, one of the essential elements, is traditionally measured using laboratory methods. The development of hyperspectral imaging enables the cost-effective acquisition of both spectral and spatial information for detecting physical, chemical, and biological attributes of the soil samples. The presented work evaluates the suitability of airborne hyperspectral imaging for determining soil nitrogen content and producing a soil nitrogen map on a pixel-wise basis. The measurement of spatial variability of the soil nitrogen content was taken at two fields located at Rudice, in northeast Brno, Czech Republic, using laboratory methods and a handheld spectrometer. The soil reflectance was also recorded using airborne-mounted imaging spectroscopy sensors. A partial least squares regression was used to develop a model for the calibration of the data collected with a portable spectrometer and to predict the total nitrogen in the soils based on hyperspectral images from airborne sensors. The determination factor for the PLSR model presented in this paper reached an R-2 of 0.44. The model's performance could be improved by using a handheld spectrometer with a wider spectral range, using the same acquisition period for field data collection and hyperspectral imaging, and enlarging the sample size.

Automated summary

Soil is a significant natural resource composed of organic and inorganic material, with nitrogen being an essential element traditionally measured using laboratory methods. The development of hyperspectral imaging allows for cost-effective acquisition of both spectral and spatial information for detecting soil attributes. This study evaluates the suitability of airborne hyperspectral imaging for determining soil nitrogen content and producing a soil nitrogen map on a pixel-wise basis.