Maize height estimation using combined unmanned aerial vehicle oblique photography and LIDAR canopy dynamic characteristics-Reference-Cited by-同舟云学术

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Maize height estimation using combined unmanned aerial vehicle oblique photography and LIDAR canopy dynamic characteristics

Published:2024-03 Issue: Volume:218 Page:108685
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Liu Tao,Zhu Shaolong,Yang Tianle,Zhang Weijun,Xu Yang,Zhou Kai,Wu Wei,Zhao Yuanyuan,Yao Zhaosheng,Yang Guanshuo,Wang Ying,Sun Chengming,Sun Jianjun

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference68 articles.

1. A review of remote sensing methods for biomass feedstock production;Ahamed;Biomass Bioenergy,2011

2. Monitoring maize growth and calculating plant heights with Synthetic Aperture Radar (SAR) and optical satellite images;Arslan;Agriculture-Basel,2022

3. Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data;Ashapure;Isprs J. Photogramm. Remote Sens.,2020

4. Assessing the influence of UAV altitude on extracted biophysical parameters of young oil palm;Avtar;Remote Sens. (Basel),2020

5. Referencing laser and ultrasonic height measurements of barley cultivars by using a herbometre as standard;Barmeier;Crop Pasture Sci.,2016

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1. High‐throughput phenotyping platforms for pulse crop biofortification;PLANTS, PEOPLE, PLANET;2024-08-28

2. Estimating Maize Crop Height and Aboveground Biomass Using Multi-Source Unmanned Aerial Vehicle Remote Sensing and Optuna-Optimized Ensemble Learning Algorithms;Remote Sensing;2024-08-28

3. Parameter estimation of an unmanned aerial vehicle using dandelion algorithm;Unmanned Systems Technology XXVI;2024-06-07

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