The Time of Day Is Key to Discriminate Cultivars of Sugarcane upon Imagery Data from Unmanned Aerial Vehicle

被引:9
作者
Barbosa Junior, Marcelo Rodrigues [1 ]
Tedesco, Danilo [1 ]
Carreira, Vinicius dos Santos [1 ]
Pinto, Antonio Alves [1 ]
de Almeida Moreira, Bruno Rafael [1 ]
Shiratsuchi, Luciano Shozo [2 ]
Zerbato, Cristiano [1 ]
da Silva, Rouverson Pereira [1 ]
机构
[1] Sao Paulo State Univ Unesp, Sch Agr & Veterinarian Sci, Dept Engn & Math Sci, BR-14884900 Jaboticabal, SP, Brazil
[2] Louisiana State Univ, AgCtr, Sch Plant Environm & Soil Sci, Baton Rouge, LA 70808 USA
关键词
flight time; NDVI; principal component analysis; reflectance; remote sensing; Saccharum spp; spectral band; UAV; vegetation index; VEGETATION INDEXES; VARIETIES;
D O I
10.3390/drones6050112
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Remote sensing can provide useful imagery data to monitor sugarcane in the field, whether for precision management or high-throughput phenotyping (HTP). However, research and technological development into aerial remote sensing for distinguishing cultivars is still at an early stage of development, driving the need for further in-depth investigation. The primary objective of this study was therefore to analyze whether it could be possible to discriminate market-grade cultivars of sugarcane upon imagery data from an unmanned aerial vehicle (UAV). A secondary objective was to analyze whether the time of day could impact the expressiveness of spectral bands and vegetation indices (VIs) in the biophysical modeling. The remote sensing platform acquired high-resolution imagery data, making it possible for discriminating cultivars upon spectral bands and VIs without computational unfeasibility. 12:00 PM especially proved to be the most reliable time of day to perform the flight on the field and model the cultivars upon spectral bands. In contrast, the discrimination upon VIs was not specific to the time of flight. Therefore, this study can provide further information about the division of cultivars of sugarcane merely as a result of processing UAV imagery data. Insights will drive the knowledge necessary to effectively advance the field's prominence in developing low-altitude, remotely sensing sugarcane.
引用
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页数:12
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