Abstract
Remote sensing systems based on unmanned aerial vehicles (UAVs) are well suited for airborne monitoring of small to medium-sized farmland in agricultural applications. An imaging system is often used in the form of a multispectral multi-camera system to derive well-established vegetation indices (VIs) efficiently. This study investigates the potential of such a multi-camera system with a novel approach to extend spectral sensitivity from visible-to-near-infrared (VNIR) to short-wave infrared (SWIR) (400–1700 nm) for estimating forage mass from an aerial carrier platform. The system test was performed in a grassland fertilizer trial in Germany near Cologne in late July 2019. Within 37 min, a spectral response in four different wavelength bands in the NIR and SWIR range was acquired during two consecutive flights. Spectral image data were calibrated to reflectance using two different methods. The resulting reflectance data sets were processed to orthomosaics for each wavelength band. From these orthomosaics for both calibration methods, the four-band NIR/SWIR GnyLi VI and the two-band NIR/SWIR Normalized Ratio Index (NRI), were calculated. During both UAV flights, spectral ground truth data were recorded with a spectroradiometer on 12 plots in total for validation of camera-based spectral data. The camera and spectroradiometer data sets were directly compared in resulting reflectance and further analyzed with simple linear regression (SLR) models to predict dry matter (DM) yield. In the camera-based SLRs, the NRI performed best with R^2 of 0.73 and 0.75 (RMSE: 0.18 and 0.17) before the GnyLi with R^{2} of 0.71 and 0.73 (RMSE: 0.19 and 0.18). These results clearly indicate the potential of the camera system for applications in forage mass monitoring.
Highlights
Grassland ecosystems cover almost 30 % of the total land area and approx. 70 % of the global agricultural land is managed grasslands (Boval and Dixon 2012; Gibson 2009)
The three remaining bands were below this value, with 980 nm having the lowest root-meansquare error (RMSE) of 0.0012
The forage mass expressed in dry matter (DM) yield used in the study was obtained by destructive biomass sampling 14 days after the flight date
Summary
Grassland ecosystems cover almost 30 % of the total land area and approx. 70 % of the global agricultural land is managed grasslands (Boval and Dixon 2012; Gibson 2009). Grasslands are critical “as a feed source for livestock, as a habitat for wildlife, for environmental protection and for the in-situ conservation of plant genetic resources” (Suttie et al 2005) They are of high cultural and economic value (Nelson et al 2017), comprising pastureland, rangeland, and cropland for forage production such as grass, silage, or hay (Nelson et al 2017), and provide the base for meat, dairy, and wool production. In the 1960s, the development of socalled disk-meters started (Castle 1976) and led to the development of Rising Plate Meters (RPMs) (Earle and McGowan 1979), which are measuring compressed sward height as an estimator for forage mass (Sanderson et al 2001). Newer technologies to measure sward height are rapid pasture meters (King et al 2010) using light beams measurements as well as ultrasonic devices (Fricke and Wachendorf 2013)
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