Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing
Light Detection and Ranging (LiDAR) technology can be used to assess canopy height in cotton (Gossypium hirsutum L.), but standardized data acquisition and processing guidelines are lacking. Accurate canopy height estimation is crucial in cotton for optimizing growth regulator application and maximi...
| Main Authors: | , , , , , , |
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| Format: | Artículo |
| Language: | Inglés |
| Published: |
MDPI
2025
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| Online Access: | http://hdl.handle.net/20.500.12123/22159 https://www.mdpi.com/2072-4292/17/9/1504 https://doi.org/10.3390/rs17091504 |
| _version_ | 1855486882505293824 |
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| author | Bhattarai, Anish Scarpin, Gonzalo Joel Jakhar, Amrinder Porter, Wesley Hand, Lavesta C. Snider, John L. Bastos, Leonardo M. |
| author_browse | Bastos, Leonardo M. Bhattarai, Anish Hand, Lavesta C. Jakhar, Amrinder Porter, Wesley Scarpin, Gonzalo Joel Snider, John L. |
| author_facet | Bhattarai, Anish Scarpin, Gonzalo Joel Jakhar, Amrinder Porter, Wesley Hand, Lavesta C. Snider, John L. Bastos, Leonardo M. |
| author_sort | Bhattarai, Anish |
| collection | INTA Digital |
| description | Light Detection and Ranging (LiDAR) technology can be used to assess canopy height in cotton (Gossypium hirsutum L.), but standardized data acquisition and processing guidelines are lacking. Accurate canopy height estimation is crucial in cotton for optimizing growth regulator application and maximizing yield. The main goal of this study was to determine the optimal unmanned aerial vehicle flight settings—altitude and speed—and assess specific processing parameters’ impact on data accuracy, processing time, and file size. Nine flight settings comprising three altitudes (12.2 m, 24.4 m, and 48.8 m) and three speeds (4.8 km/h, 9.6 km/h, and 14.4 km/h) were tested. LiDAR data were processed using DJI Terra software (v. 4.1.0), where two user-defined processing steps were examined: point-cloud thinning via grid size sub-sampling (0, 10, 20, 30, 40, and 50 cm) and slope classification (flat, gentle, and steep). The optimal flight altitude was 24.4 m, with no effect of flight speed. Grid sub-sampling up to 20 cm produced balanced accuracy, processing time, and file size. The choice of slope category had no significant effect on LiDAR-derived canopy height. These findings contribute to the development of standardized LiDAR data acquisition and processing guidelines for cotton to support crop management decision. |
| format | Artículo |
| id | INTA22159 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI |
| publisherStr | MDPI |
| record_format | dspace |
| spelling | INTA221592025-05-05T13:54:23Z Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing Bhattarai, Anish Scarpin, Gonzalo Joel Jakhar, Amrinder Porter, Wesley Hand, Lavesta C. Snider, John L. Bastos, Leonardo M. Teledetección Algodón Sistema Lidar Procesamiento de Datos Colección de Datos Vehículo Aéreo No Tripulado Remote Sensing Cotton Gossypium hirsutum LIDAR Data Processing Data Collection Unmanned Aerial Vehicles Light Detection and Ranging Light Detection and Ranging (LiDAR) technology can be used to assess canopy height in cotton (Gossypium hirsutum L.), but standardized data acquisition and processing guidelines are lacking. Accurate canopy height estimation is crucial in cotton for optimizing growth regulator application and maximizing yield. The main goal of this study was to determine the optimal unmanned aerial vehicle flight settings—altitude and speed—and assess specific processing parameters’ impact on data accuracy, processing time, and file size. Nine flight settings comprising three altitudes (12.2 m, 24.4 m, and 48.8 m) and three speeds (4.8 km/h, 9.6 km/h, and 14.4 km/h) were tested. LiDAR data were processed using DJI Terra software (v. 4.1.0), where two user-defined processing steps were examined: point-cloud thinning via grid size sub-sampling (0, 10, 20, 30, 40, and 50 cm) and slope classification (flat, gentle, and steep). The optimal flight altitude was 24.4 m, with no effect of flight speed. Grid sub-sampling up to 20 cm produced balanced accuracy, processing time, and file size. The choice of slope category had no significant effect on LiDAR-derived canopy height. These findings contribute to the development of standardized LiDAR data acquisition and processing guidelines for cotton to support crop management decision. EEA Reconquista Fil: Bhattarai, Anish. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Scarpin, Gonzalo Joel. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Scarpin, Gonzalo Joel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista; Argentina Fil: Jakhar, Amrinder. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Porter, Wesley. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Hand, Lavesta C. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Snider, John L. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Bastos, Leonardo M. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos 2025-05-05T13:52:02Z 2025-05-05T13:52:02Z 2025-05 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/22159 https://www.mdpi.com/2072-4292/17/9/1504 2072-4292 https://doi.org/10.3390/rs17091504 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf MDPI Remote Sensing 17 (9) : 1504. (May 2025) |
| spellingShingle | Teledetección Algodón Sistema Lidar Procesamiento de Datos Colección de Datos Vehículo Aéreo No Tripulado Remote Sensing Cotton Gossypium hirsutum LIDAR Data Processing Data Collection Unmanned Aerial Vehicles Light Detection and Ranging Bhattarai, Anish Scarpin, Gonzalo Joel Jakhar, Amrinder Porter, Wesley Hand, Lavesta C. Snider, John L. Bastos, Leonardo M. Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing |
| title | Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing |
| title_full | Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing |
| title_fullStr | Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing |
| title_full_unstemmed | Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing |
| title_short | Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing |
| title_sort | optimizing unmanned aerial vehicle lidar data collection in cotton through flight settings and data processing |
| topic | Teledetección Algodón Sistema Lidar Procesamiento de Datos Colección de Datos Vehículo Aéreo No Tripulado Remote Sensing Cotton Gossypium hirsutum LIDAR Data Processing Data Collection Unmanned Aerial Vehicles Light Detection and Ranging |
| url | http://hdl.handle.net/20.500.12123/22159 https://www.mdpi.com/2072-4292/17/9/1504 https://doi.org/10.3390/rs17091504 |
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