## 3 Results
### Evolution of Research Frontiers from Keyword Bursts  
Analyzing the evolution of emerging keywords reveals clear trends in the development of UAV-RS (Table 7). Since entering the scientific landscape in the early 21 st century, UAV-RS technology has undergone four major phases: platform diversification, sensor integration, intelligent data processing, and real-time application. Initially, a variety of flight platforms--multi-rotor, fixed-wing, and unmanned helicopters--emerged, leveraging high-precision satellite navigation and inertial navigation systems to achieve breakthroughs in long-endurance flights, high-precision autonomous positioning, and vision-assisted navigation [134; 135; 136; 137]. These advancements, coupled with integrated obstacle avoidance technologies combining LiDAR and visual sensors, significantly enhanced flight safety [138; 139; 140; 141]. Subsequently, progress in miniaturization and diversification of sensors accelerated. Optical cameras evolved into multispectral, hyperspectral, and thermal infrared systems, while lightweight LiDAR systems enabled UAVs to capture both high-resolution 2D imagery and 3D point cloud data [142; 143; 144]. To facilitate the fusion of heterogeneous datasets, sensor calibration algorithms and coordinate transformation methods were further refined, effectively addressing issues arising from varying resolutions and coordinate systems [145; 146]. \begin{table}
\begin{tabular}{c c c c} \hline \hline \begin{tabular}{c} **Serial** \\ **Number** \\ \end{tabular}  & **Cluster** & \multicolumn{2}{c}{**Keyword (Frequency)**} & \multicolumn{2}{c}{**Representative Research Direction**} \\ \hline \multirow{4}{*}{\#5} & \multirow{4}{*}{\ \begin{tabular}{c} Hyperspectral \\ Imaging \\ \end{tabular}  } & Algorithm, Retrieval, Calibration, & \multirow{4}{*}{ \begin{tabular}{c} Emerging sensor technologies: \\ Focused on algorithms and \\ calibration, but not yet widely \\ applied at scale. \\ \end{tabular}  } \\  & & & & \\ \cline{1-1}  & & & \\ \cl \begin{table}
\begin{tabular}{r r r r r r} \hline
**Keywords** & **Year** & **Strength** & **Begin** & **End** & **1993-2024** \\ \hline Aircraft & 2000 & 5.48 & 2000 & 2018 & \\ Imagery & 2001 & 18.4 & 2009 & 2018 & \\ Image processing & 2005 & 4.82 & 2005 & 2017 & \\ Aerial photography & 2006 & 5.86 & 2006 & 2016 & \\ Unmanned aerial vehicle & 2006 & 7.57 & 2010 & 2015 & \\ Crop & 2007 & 9.77 & 2007 & 2016 & \\ Features & 2008 & 4.49 & 2015 & 2018 & \\ Canopy temperature & 2009 & 3.51 & 2009 & 2017 & \\ Water stress & 2009 & 7.46 & 2016 & 2018 & \\ Scale & 2010 & 12.66 & 2010 & 2017 & \\ Unmanned aircraft & 2010 & 4.54 & 2010 & 2017 & \\ Accuracy & 2011 & 8.77 & 2011 & 2017 & \\ Camera & 2011 & 8.73 & 2011 & 2018 & \\ Classification & 2011 & 8.34 & 2011 & 2016 & \\ Chlorophyll fluorescence & 2014 & 5.31 & 2014 & 2018 & \\ Radiometric calibration & 2014 & 4.82 & 2014 & 2019 & \\ Hyperspectral imagery & 2014 & 3.96 & 2014 & 2019 & \\ Structure from motion & 2014 & 8.06 & 2015 & 2019 & \\ Fluorescence & 2015 & 6.29 & 2015 & 2019 & \\ Photosynthesis & 2015 & 5.86 & 2015 & 2018 & \\ Topography & 2016 & 7.26 & 2016 & 2018 & \\ Calibration & 2016 & 5.68 & 2016 & 2019 & \\ Point clouds & 2016 & 5.47 & 2016 & 2017 & \\ Digital surface model & 2016 & 5.13 & 2016 & 2019 & \\ Digital elevation model & 2016 & 4.07 & 2016 & 2019 & \\ High resolution & 2016 & 3.77 & 2016 & 2019 & \\ Stomatal conductance & 2017 & 4.76 & 2017 & 2020 & \\ Drought & 2017 & 3.74 & 2017 & 2020 & \\ Coastal & 2017 & 3.58 & 2017 & 2018 & \\ Winter-wheat & 2017 & 3.56 & 2017 & 2020 & \\ Maize & 2018 & 3.67 & 2018 & 2019 & \\ Water quality & 2020 & 4.25 & 2020 & 2021 & \\ Infrared thermography & 2020 & 3.82 & 2020 & 2021 & \\ Individual tree detection & 2020 & 3.82 & 2020 & 2021 & \\ \hline \end{tabular}
\end{table} 
Table 7: Top 40 emerging UAV-RS keywords.