Unverified paper record
Assessment of Temporal Variations in Crop Growth Dynamics Using UAV Imagery
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences · 30 Apr 2026 · 10.5194/isprs-archives-xlviii-m-10-2025-27-2026
Abstract
Abstract. Effective crop monitoring is essential for optimizing agricultural practices and promoting sustainable production. This study explores the use of temporal Unmanned Aerial Vehicle (UAV) imagery to assess variations in crop growth dynamics across different developmental stages. UAV images were captured at five-day intervals, enabling the analysis of temporal changes in phenological parameters and plant health. Key vegetation indices and canopy height were derived at multiple time points and statistically evaluated to determine their effectiveness in monitoring crop development. The multi-temporal analysis identified the most informative vegetation indices and image processing techniques for assessing crop conditions. Results demonstrate that UAV-based temporal imaging offers valuable insights into crop growth patterns that are difficult to obtain through conventional monitoring approaches. The findings highlight the potential of UAV imagery as a practical tool for improving crop management by enabling timely and informed decision-making, ultimately contributing to enhanced yield and resource use efficiency.
Plant phenotyping relevance
UAV画像を用いて作物の生育動態を時系列で評価し、植生指数と群落高を抽出・比較することが研究の中心であり、植物形質の取得手法として実質的です。
abstractUAV images were captured at five-day intervals, enabling the analysis of temporal changes in phenological parameters and plant health.
abstractKey vegetation indices and canopy height were derived at multiple time points and statistically evaluated to determine their effectiveness in monitoring crop development.
abstractThe multi-temporal analysis identified the most informative vegetation indices and image processing techniques for assessing crop conditions.
Code and data availability
The paper describes UAV imagery collection, vegetation index computation, and statistical analysis, but contains no data availability statement, no public dataset or image deposit, and no author code repository or URL. All URLs in the text are citations to prior work, not paper-specific assets.
No evidence-backed public reproduction asset is currently recorded.
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