Используемая литература
1. Эльсгольц Л. Э. Дифференциальные уравнения и вариационное исчисление. М.: Наука, 1974. 432 с.
2. Chen R., Chu T., Landivar J. A., Yang C., Maeda M. M. Monitoring cotton (Gossypium hirsutum L) germination using ultrahigh-resolution UAS images. Precis. Agric., 2017, https://doi.org/10.1007/s11119-017-9508-7.
3. Geipel J, Link J, Claupein W. Combined spectral and spatial modeling of corn yield based on aerial images and crop surface models acquired with an unmanned aircraft system. Remote Sens., 2014, 11:10335–55, https:// doi.org/10.3390/rs61110335.
4. Holman F. H., Riche A. B., Michalski A., Castle M., Wooster M. J., Hawkesford M. J. High throughput field phenotyping of wheat plant height and growth rate in field plot trials using UAV based remote sensing. Remote Sens., 2016, https://doi.org/10.3390/rs8121031.
5. Jin X., Liu S., Baret F., Hemerle M., Comar A. Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery. Remote Sens. Environ., 2017, https://doi.org/10.1016/j.rse.2017.06.007.
6. Lelong C., Burger P., Jubelin G., Roux B., Labbe S., Baret F. Assessment of unmanned aerial vehicles imagery for quantitative monitoring of wheat crop in small plots. Sensors, 2008, https://doi.org/10.3390/s8053557.
7. Liebisch F., Kirchgessner N., Schneider D., Walter A., Hund A. Remote aerial phenotyping of maize traits with a mobile multi-sensor approach. Plant method, 2015, https://doi.org/10.1186/s13007-015-0048-8.
8. Liu T., Li R., Jin X., Ding J., Zhu X., Sun C., Guo W. Evaluation of seed emergence uniformity of mechanically sown wheat with UAV RGB imagery. Remote Sens., 2017, https://doi.org/10.3390/rs9121241.
9. Maimaitijiang M., Ghulam A., Sidike P., Hartling S., Maimaitiyiming M., Peterson K., Shavers E., Fishman J., Peterson J., Kadam S., Burken J., Fritschi F. Unmanned aerial system (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine. ISPRS J Photogramm remote sens., 2017, Pp. 43-58, https://doi.org/10.1016/j.isprsjprs.2017.10.011.
10. Roth L. Roth, A. Hund, and H. Aasen. PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems. Plant Methods, 14(116), 2018, doi: 10.1186/s13007-018-0376-6, URL https://shiny.usys.ethz.ch/ PhenoFlyPlanningTool/.
11. Roth L., Aasen H., Walter A., Liebisch F. Extracting leaf area index using viewing geometry effects—a new perspective on high-resolution unmanned aerial system photography. ISPRS j Photogramm remote sens., 2018, https://doi.org/10.1016/j.isprsjprs.2018.04.012.
12. Roth L., Streit B. Predicting cover crop biomass by lightweight UAS-based RGB and NIR photography: an applied photogrammetric approach. Precis Agric., 2018, Pp. 93-114, https://doi.org/10.1007/s11119-017-9501-1.
13. Torres-Sanchez J., Pena J. M., de Castro A., Lopez-Granados F. Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV. Comput Electron Agric., 2014, https://doi.org/10.1016/j.compag.2014.02.009.