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High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery

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Title High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery
 
Creator Devia, Carlos A.
Rojas, Juan P.
Petro Páez, Eliel Enrique
Martínez, Carol
Mondragon, Ivan F.
Patino, D.
Rebolledo, María Camila
Colorado, J.
 
Subject rice
phaseolus vulgaris
vegetation
biomass
 
Description This paper presents a high-throughput method for Above Ground Estimation of Biomass (AGBE) in rice using multispectral near-infrared (NIR) imagery captured at different scales of the crop. By developing an integrated aerial crop monitoring solution using an Unmanned Aerial Vehicle (UAV), our approach calculates 7 vegetation indices that are combined in the form of multivariable regressions depending on the stage of rice growth: vegetative, reproductive or ripening. We model the relationship of these vegetation indices to estimate the biomass of a certain crop area. The methods are calibrated by using a minimum sampling area of 1 linear meter of the crop. Comprehensive experimental tests have been carried out over two different rice varieties under upland and lowland rice production systems. Results show that the proposed approach is able to estimate the biomass of large areas of the crop with an average correlation of 0.76 compared with the traditional manual destructive method. To our knowledge, this is the first work that uses a small sampling area of 1 linear meter to calibrate and validate NIR image-based estimations of biomass in rice crops.
 
Date 2019
2019-03-19T15:00:14Z
2019-03-19T15:00:14Z
 
Type Journal Article
 
Identifier Devia, Carlos A.; Rojas, Juan P.; Petro, Eliel; Martinez, Carol; Mondragon, Ivan F.; Patino, D.; Rebolledo, Maria Camila & Colorado, J. (2019). High-Throughput Biomass Estimation in Rice Crops Using UAV Multispectral Imagery, Journal of Intelligent & Robotic Systems. 1-17 p.
0921-0296
https://hdl.handle.net/10568/100348
https://doi.org/10.1007/s10846-019-01001-5
 
Language en
 
Rights Other
Open Access
 
Format 1-17 p.
application/pdf
 
Publisher Springer
 
Source Journal of Intelligent and Robotic Systems