References
- Berni, J. A., P. J. Zarco-Tejada, L. Suarez and E. Fereres, 2009. Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47(3):722-738. https://doi.org/10.1109/TGRS.2008.2010457
- Corre-Hellou, G., A. Dibet, H. Hauggaard-Nielsen, Y. Crozat, M. G ooding, P . Ambus and E. S. Jensen. 2011. The competitive ability of pea-barley intercrops against weeds and the interactions with crop productivity and soil N availability. Field Crops Research 122(3):264-272. https://doi.org/10.1016/j.fcr.2011.04.004
- Garcia-Ruiz, F., S. Sankaran, J. M. Maja, W. S. Lee, J. Rasmussen and R. Ehsani. 2013. Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees. Computers and Electronics in Agriculture 91:106-115. https://doi.org/10.1016/j.compag.2012.12.002
- Hunt, E. R., W. D. Hively, S. J. Fujikawa, D. S. Linden, C.S. Daughtry and G.W. McCarty. 2010. Acquisition of NIR-green-blue digital photographs from unmanned aircraft for crop monitoring. Remote Sensing 2(1):290-305. https://doi.org/10.3390/rs2010290
- Jimenez, P. L. and D. Agudelo 2015. Validation and calibration of a high resolution sensor in unmanned aerial vehicles for producing images in the IR range utilizable in precision agriculture. In: Proceedings of the AIAA SciTech, Paper No. 2015-0988. Kissimmee, FL: AIAA Infotech @ Aerospace.
- Kaufman, Y. J. and L. A. Remer. 1994. Detection of forests using mid-IR reflectance: an application for aerosol studies. IEEE Transactions on Geoscience and Remote Sensing 32(3):672-683. https://doi.org/10.1109/36.297984
- Kobayashi, H., S. Miura and A. Oyanagi. 2004. Effects of winter barley as a cover crop on the weed vegetation in a no-tillage soybean. Weed Biology and Management 4(4):195-205. https://doi.org/10.1111/j.1445-6664.2004.00138.x
- Lu, Y. C., K. B. Watkins, J. R. Teasdale and A. A. Abdul-Bakil. 2000. Cover crops in sustainable food production. Food Reviews International 16(2):121-157. https://doi.org/10.1081/FRI-100100285
- Poggio, S. L. 2005. Structure of weed communities occurring in monoculture and intercropping of field pea and barley. Agriculture, Ecosystems and Environment 109(1):48-58. https://doi.org/10.1016/j.agee.2005.02.019
- Pena, J. M., J. Torres-Sanchez, A. I. de Castro, M. Kelly, and F. Lopez-Granados. 2013. Weed mapping in earlyseason maize fields using object-based analysis of unmanned aerial vehicle (UAV) images. PLoS One 8(10):e77151. https://doi.org/10.1371/journal.pone.0077151
- Pereira, J. M., A. C. Sa, A. M. Sousa, J. M. Silva, T. N. Santos, and J. M. Carreiras. 1999. Spectral characterization and discrimination of burnt areas. In: Remote sensing of large wildfires, pp. 123-138. Springer-Berlag Berlin Heidelberg.
- Smith, G. M., and E. J. Milton. 1999. The use of the empirical line method to calibrate remotely sensed data to reflectance. International Journal of remote sensing, 20(13):2653-2662. https://doi.org/10.1080/014311699211994
- Todd, A. P., C. B. Orvin, and H. O. James. 1999. Increasing crop competitiveness to weeds through crop breeding. Journal of Crop Production 2(1):59-76. https://doi.org/10.1300/J144v02n01_04
- Torres-Sanchez, J., J. M. Pena, A. I. de Castro, and F. Lopez-Granados. 2014. Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV. Computers and Electronics in Agriculture 103:104-113. https://doi.org/10.1016/j.compag.2014.02.009
- Wang, C. and S. W. Myint, 2015. A simplified empirical line method of radiometric calibration for small unmanned aircraft systems-based remote sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(5):1876-1885. https://doi.org/10.1109/JSTARS.2015.2422716
- Woebbecke, D. M., G. E. Meyer, K. Von Bargen, and D. A. Mortensen, 1995. Color indices for weed identification under various soil, residue, and lighting conditions. Transactions of the ASAE 38(1):259-269. https://doi.org/10.13031/2013.27838
Cited by
- Commercial Off-the-Shelf Digital Cameras on Unmanned Aerial Vehicles for Multitemporal Monitoring of Vegetation Reflectance and NDVI vol.55, pp.9, 2017, https://doi.org/10.1109/TGRS.2017.2655365
- Mapping the Spatial Distribution of IRG Growth Based on UAV vol.49, pp.5, 2016, https://doi.org/10.7745/KJSSF.2016.49.5.495
- A Comparative Study of Image Classification Method to Classify Onion and Garlic Using Unmanned Aerial Vehicle (UAV) Imagery vol.49, pp.6, 2016, https://doi.org/10.7745/KJSSF.2016.49.6.743
- What good are unmanned aircraft systems for agricultural remote sensing and precision agriculture? 2018, https://doi.org/10.1080/01431161.2017.1410300
- Cost-effective reflectance calibration method for small UAV images pp.1366-5901, 2018, https://doi.org/10.1080/01431161.2018.1516307
- Modeling and Testing of Growth Status for Chinese Cabbage and White Radish with UAV-Based RGB Imagery vol.10, pp.4, 2018, https://doi.org/10.3390/rs10040563