## 4 Conclusions and Outlook  
In this case study, we presented a successful approach of how to use the combination of UAV-based high resolution remote sensing data and ground truth measurements for the estimation of the total C export by harvest of lucerne. The image pre-processing of the 12-band multispectral images has led to a considerable reduction of noise and vignetting effects. Together with the subsequent mosaicking and band alignment, the workflow is operational and will reduce the pre-processing time in future UAV missions. The conversion of recorded digital numbers to at-surface reflectance was only successful for the six NIR bands (b\({}_{761}\)-b\({}_{953}\)) and the R band b\({}_{658}\). However, these were the most important bands for the calculation of the VIs used in this study. Nevertheless, improvements of the experimental design \begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline  & & & \multicolumn{2}{c}{**Monitoring 2014**} & \multicolumn{4}{c}{**UAV Mission (14-08-27)**} \\ \hline Case & Terrain position & Soil type (FAO) & \multicolumn{2}{c}{Dry phytomass} & factor & \multicolumn{2}{c}{Dry phytomass} & \multicolumn{2}{c}{C export} \\  & & & 4. harvest & per year & & 4. harvest & 4. harvest & per year & \\  & & & [g:m\({}^{-2}\)] & [g:m\({}^{-2}\)] & & [g:m\({}^{-2}\)] & [g:m\({}^{-2}\)] & [g:m\({}^{-2}\)] & CV [\%] \\ \hline C1 & Steep slope & Calcaric Regosol & 280 & 1409 & 5.03 & 288 & 124 & 624 & 21 \\ C2 & Flat hilltop & Alibc Cutanic Luvisol & 316 & 1452 & 4.60 & 363 & 156 & 718 & 17 \\ C3 & Midslope/hollow & Calcic Cutanic & 361 & 1556 & 4.32 & 376 & 161 & 697 & 14 \\  & & Luvisol/Endogeyle & & & & & & \\  & & Collivic Regosol & & & & & & \\ C4 & Midslope & & Calcic Cutanic & 307 & 1456 & 4.75 & 339 & 146 & 693 & 14 \\  & & Luvisol- manipulated & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Yearly estimates of dry phytomass production and C export from four different Terrain/Soil type combinations (C1–C4) calculated from UAV imagery and ground based monitoring data. Figure 19: Temporal decline of above ground dry phytomass of lucerne between the first and fourth harvest in 2014.  
to obtain the empirical lines for absolute radiometric calibration of the remaining bands in the VIS are necessary. The strong correlation between fresh phytomass of lucerne and the EVI (\(R^{2}\) = 0.88) using the NIR band b899 demonstrated the power of this VI even in the case of a dense green vegetation canopy. The map of the total C export revealed the potential of high spatial image resolution to: (i) map high small-scale variability within and across the different plots (75 g\(\cdot\)m\({}^{-2}\) and 225 g\(\cdot\)m\({}^{-2}\)); and (ii) identify the spatial pattern as a result of different terrain positions and associated soil types. Future UAV missions should include important annual crops such as winter wheat or corn. The temporal flexibility of the UAV should be exploited for intra- and inter-annual studies of the temporal carbon dynamics, coupled with research campaigns focus on other components of the carbon budget (e.g., gas exchange measurements). The fixed-wing Carolo P360 proved to be a valuable instrument for mapping vegetation parameters over small experimental areas. The high cruising speed and the potential flight endurance of at least 30 min. have the potential to map larger areas which cover the full spectrum of terrain position/soil type combinations in this heterogeneous soil landscape under equal imaging conditions. Finally, the respective results should be coupled with other available sources of spatially consistent proximal and remote sensing data and assimilated in state of the art models to gain improved insight into the processes controlling the carbon budget of agricultural landscapes. The authors would like to thank [PERSON] and the staff of the ZALF Research Station in Dedelow for providing total carbon content data and yield data of lucerne, respectively.