Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing

Autores
Bhattarai, Anish; Scarpin, Gonzalo Joel; Jakhar, Amrinder; Porter, Wesley; Hand, Lavesta C.; Snider, John L.; Bastos, Leonardo M.
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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
Fuente
Remote Sensing 17 (9) : 1504. (May 2025)
Materia
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
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/22159
Acceder
id INTADig_ed73dadac722b78355755b51a1ebe8db
oai_identifier_str oai:localhost:20.500.12123/22159
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data ProcessingBhattarai, AnishScarpin, Gonzalo JoelJakhar, AmrinderPorter, WesleyHand, Lavesta C.Snider, John L.Bastos, Leonardo M.TeledetecciónAlgodónSistema LidarProcesamiento de DatosColección de DatosVehículo Aéreo No TripuladoRemote SensingCottonGossypium hirsutumLIDARData ProcessingData CollectionUnmanned Aerial VehiclesLight Detection and RangingLight 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 ReconquistaFil: Bhattarai, Anish. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosFil: Scarpin, Gonzalo Joel. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosFil: Scarpin, Gonzalo Joel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista; ArgentinaFil: Jakhar, Amrinder. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosFil: Porter, Wesley. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosFil: Hand, Lavesta C. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosFil: Snider, John L. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosFil: Bastos, Leonardo M. University of Georgia. Department of Crop and Soil Sciences; Estados UnidosMDPI2025-05-05T13:52:02Z2025-05-05T13:52:02Z2025-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/22159https://www.mdpi.com/2072-4292/17/9/15042072-4292https://doi.org/10.3390/rs17091504Remote Sensing 17 (9) : 1504. (May 2025)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-09-04T09:51:02Zoai:localhost:20.500.12123/22159instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-04 09:51:03.028INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv 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
spellingShingle Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing
Bhattarai, Anish
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
title_short 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_sort Optimizing Unmanned Aerial Vehicle LiDAR Data Collection in Cotton Through Flight Settings and Data Processing
dc.creator.none.fl_str_mv Bhattarai, Anish
Scarpin, Gonzalo Joel
Jakhar, Amrinder
Porter, Wesley
Hand, Lavesta C.
Snider, John L.
Bastos, Leonardo M.
author Bhattarai, Anish
author_facet Bhattarai, Anish
Scarpin, Gonzalo Joel
Jakhar, Amrinder
Porter, Wesley
Hand, Lavesta C.
Snider, John L.
Bastos, Leonardo M.
author_role author
author2 Scarpin, Gonzalo Joel
Jakhar, Amrinder
Porter, Wesley
Hand, Lavesta C.
Snider, John L.
Bastos, Leonardo M.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv 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
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
dc.description.none.fl_txt_mv 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
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.
publishDate 2025
dc.date.none.fl_str_mv 2025-05-05T13:52:02Z
2025-05-05T13:52:02Z
2025-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 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
url http://hdl.handle.net/20.500.12123/22159
https://www.mdpi.com/2072-4292/17/9/1504
https://doi.org/10.3390/rs17091504
identifier_str_mv 2072-4292
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv 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)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Remote Sensing 17 (9) : 1504. (May 2025)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.623145

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