Louisiana State University Agriculture Center, School of Plant, Environmental and Soil Sciences, Baton Rouge, LA 70803, USA.
Sensors (Basel). 2024 Aug 17;24(16):5322. doi: 10.3390/s24165322.
This study documented the contribution of precise positioning involving a global navigation satellite system (GNSS) and a real-time kinematic (RTK) system in unmanned aerial vehicle (UAV) photogrammetry, particularly for establishing the coordinate data of ground control points (GCPs). Without augmentation, GNSS positioning solutions are inaccurate and pose a high degree of uncertainty if such data are used in UAV data processing for mapping. The evaluation included a comparative assessment of sample coordinates involving RTK and an ordinary GPS device and the application of precise GCP data for UAV photogrammetry in field crop research, monitoring nitrogen deficiency stress in maize. This study confirmed the superior performance of the RTK system in providing positional data, with 4 cm bias as compared to 311 cm with the non-augmented GNSS technique, making it suitable for use in agronomic research involving row crops. Precise GCP data in this study allow the UAV-based Normalized Difference Red-Edge Index (NDRE) data to effectively characterize maize crop responses to N nutrition during the growing season, with detailed analyses revealing the causal relationship in that a compromised optimum canopy chlorophyll content under limiting nitrogen environment was the reason for reduced canopy cover under an N-deficiency environment. Without RTK-based GCPs, different and, to some degree, misleading results were evident, and therefore, this study warrants the requirement of precise GCP data for scientific research investigations attempting to use UAV photogrammetry for agronomic field crop study.
本研究记录了全球导航卫星系统 (GNSS) 和实时动态 (RTK) 系统在无人机 (UAV) 摄影测量中精确定位的贡献，特别是在建立地面控制点 (GCP) 的坐标数据方面。如果在无人机数据处理中使用这些数据进行制图，没有增强的 GNSS 定位解决方案是不准确的，并且存在高度的不确定性。该评估包括对涉及 RTK 和普通 GPS 设备的样本坐标的比较评估，以及在田间作物研究中应用精确 GCP 数据进行无人机摄影测量，监测玉米缺氮胁迫。本研究证实了 RTK 系统在提供位置数据方面的卓越性能，与非增强型 GNSS 技术相比，偏差为 4 厘米，非常适合涉及行作物的农艺研究。本研究中的精确 GCP 数据允许基于无人机的归一化差异红边指数 (NDRE) 数据有效地描述玉米作物对生长季节氮营养的响应，详细分析揭示了这种因果关系，即在限制氮环境下，最佳冠层叶绿素含量受损是导致在氮缺乏环境下冠层覆盖减少的原因。如果没有基于 RTK 的 GCP，不同的、在某种程度上是误导性的结果是显而易见的，因此，本研究需要精确的 GCP 数据来支持试图使用无人机摄影测量进行农艺田间作物研究的科学研究调查。
