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首页> 外文期刊>Ecological indicators >Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system
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Remote estimation of canopy height and aboveground biomass of maize using high-resolution stereo images from a low-cost unmanned aerial vehicle system

机译：使用来自低成本无人机系统的高分辨率立体图像远程估算玉米冠层高度和地上生物量

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摘要

Canopy height (H-canopy) and aboveground biomass (AGB) of crops are two basic agro-ecological indicators that can provide important indications on the growth, light use efficiency, and carbon stocks in agro-ecosystems. In this study, hundreds of stereo images with very high resolution were collected to estimate Hcanopy and AGB of maize using a low-cost unmanned aerial vehicle (UAV) system. Millions of point clouds that are related to the structure from motion (SfM) were produced from the UAV stereo images through a photogrammetric workflow. Metrics that are commonly used in airborne laser scanning (ALS) were calculated from the SfM point clouds and were tested in the estimation of maize parameters for the first time. In addition, the commonly used spectral vegetation indices calculated from the UAV orthorectified image were also tested. Estimation models were established based on the UAV variables and field measurements with cross validation, during which the performance of the UAV variables was quantified. Finally, the following results were achieved: (1) the spatial patterns of maize Hcanopy and AGB were predicted by a multiple stepwise linear (SWL) regression model (R-2 = 0.88, rRMSE = 6.40%) and a random forest regression (RF) model (R-2 = 0.78, rRMSE = 16.66%), respectively. (2) The UAV-estimated maize parameters were proved to be comparable to the field measurements with a mean error (ME) of 0.11 m for H-canopy, and 0.05 kg/m(2) for AGB. (3) The SfM point metrics, especially the mean point height (H-mean) greatly contributed to the estimation model of maize Hcanopy and AGB, which can be promising indicators in the detection of maize biophysical parameters. To conclude, the variations in spectral and structural attributes for maize canopy should be simultaneously considered when only simple RGB images are available for estimating maize AGB. This study provides some suggestions on how to make full use of the low-cost and high-resolution UAV stereo images in precision agro-ecological applications and management. (C) 2016 Elsevier Ltd. All rights reserved.
机译：作物的冠层高度（H冠层）和地上生物量（AGB）是两个基本的农业生态指标，可以为农业生态系统的生长，光利用效率和碳储量提供重要指示。在这项研究中，使用低成本的无人机（UAV）系统收集了数百个高分辨率的立体图像，以估算玉米的Hcanopy和AGB。通过摄影测量工作流程，从无人机立体图像中产生了数以百万计的与运动（SfM）结构相关的点云。机载激光扫描（ALS）中常用的度量是根据SfM点云计算的，并首次在玉米参数估计中进行了测试。此外，还对从无人机正射影像计算得到的常用光谱植被指数进行了测试。基于无人机变量和交叉验证的野外测量建立了估计模型，在此期间对无人机变量的性能进行了量化。最后，获得了以下结果：（1）利用多重逐步线性回归模型（R-2 = 0.88，rRMSE = 6.40％）和森林随机回归（RF）预测玉米Hcanopy和AGB的空间格局。 ）模型（R-2 = 0.78，rRMSE = 16.66％）。 （2）事实证明，UAV估算的玉米参数与实地测量具有可比性，H冠层的平均误差（ME）为0.11 m，AGB为0.05 kg / m（2）。 （3）SfM点指标，特别是平均点高（H-mean）大大促进了玉米Hcanopy和AGB的估计模型，这可能是检测玉米生物物理参数的有希望的指标。总之，当仅简单的RGB图像可用于估算玉米AGB时，应同时考虑玉米冠层的光谱和结构属性的变化。这项研究为如何在精确的农业生态应用和管理中充分利用低成本和高分辨率的无人机立体图像提供了一些建议。 （C）2016 Elsevier Ltd.保留所有权利。

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  • 来源
    《Ecological indicators》 |2016年第8期|637-648|共12页
  • 作者

    Li Wang; Niu Zheng; Chen Hanyue; Li Dong; Wu Mingquan; Zhao Wei;

  • 作者单位

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,20 Datun Rd,Olymp Sci &Technol Pk CAS, Beijing 100101, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,20 Datun Rd,Olymp Sci &Technol Pk CAS, Beijing 100101, Peoples R China;

    Fujian Agr & Forestry Univ, Coll Resource & Environm Sci, Fuzhou 350002, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Airborne Remote Sensing Ctr, Beijing 100101, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,20 Datun Rd,Olymp Sci &Technol Pk CAS, Beijing 100101, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, POB 9718,20 Datun Rd,Olymp Sci &Technol Pk CAS, Beijing 100101, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Unmanned aerial vehicle; Stereo images; Point clouds; Canopy height; Maize biomass;

    机译：无人机;立体图像;点云;机壳高度;玉米生物量;

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