Estimating Nitrogen from Structural Crop Traits at Field Scale—A Novel Approach Versus Spectral Vegetation Indices

• Main Authors: Nora Tilly, Georg Bareth
• Format: Article
• Language: English
• Published: MDPI AG 2019-09-01
• Series: Remote Sensing
• Subjects: terrestrial laser scanning; spectrometer; plant height; vegetation indices; biomass; nitrogen concentration; precision agriculture
• Online Access: https://www.mdpi.com/2072-4292/11/17/2066

A sufficient nitrogen (N) supply is mandatory for healthy crop growth, but negative consequences of N losses into the environment are known. Hence, deeply understanding and monitoring crop growth for an optimized N management is advisable. In this context, remote sensing facilitates the capturing of crop traits. While several studies on estimating biomass from spectral and structural data can be found, N is so far only estimated from spectral features. It is well known that N is negatively related to dry biomass, which, in turn, can be estimated from crop height. Based on this indirect link, the present study aims at estimating N concentration at field scale in a two-step model: first, using crop height to estimate biomass, and second, using the modeled biomass to estimate N concentration. For comparison, N concentration was estimated from spectral data. The data was captured on a spring barley field experiment in two growing seasons. Crop surface height was measured with a terrestrial laser scanner, seven vegetation indices were calculated from field spectrometer measurements, and dry biomass and N concentration were destructively sampled. In the validation, better results were obtained with the models based on structural data (R² < 0.85) than on spectral data (R² < 0.70). A brief look at the N concentration of different plant organs showed stronger dependencies on structural data (R²: 0.40−0.81) than on spectral data (R²: 0.18−0.68). Overall, this first study shows the potential of crop-specific across‑season two-step models based on structural data for estimating crop N concentration at field scale. The validity of the models for in-season estimations requires further research.