• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Remote Sensing >A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera
【24h】

A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera

机译：使用无人机安装的快照高光谱传感器和高清数码相机的图像进行作物参数估计的比较

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Timely and accurate estimates of crop parameters are crucial for agriculture management. Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this work because they can obtain remote-sensing images with higher temporal, spatial, and ground resolution than satellites. In this study, we evaluated (i) the performance of crop parameters estimates using a near-surface spectroscopy (350~2500 nm, 3 nm at 700 nm, 8.5 nm at 1400 nm, 6.5 nm at 2100 nm), a UAV-mounted snapshot hyperspectral sensor (450~950 nm, 8 nm at 532 nm) and a high-definition digital camera (Visible, R, G, B); (ii) the crop surface models (CSMs), RGB-based vegetation indices (VIs), hyperspectral-based VIs, and methods combined therefrom to make multi-temporal estimates of crop parameters and to map the parameters. The estimated leaf area index (LAI) and above-ground biomass (AGB) are obtained by using linear and exponential equations, random forest (RF) regression, and partial least squares regression (PLSR) to combine the UAV based spectral VIs and crop heights (from the CSMs). The results show that: (i) spectral VIs correlate strongly with LAI and AGB over single growing stages when crop height correlates positively with AGB over multiple growth stages; (ii) the correlation between the VIs multiplying crop height and AGB is greater than that between a single VI and crop height; (iii) the AGB estimate from the UAV-mounted snapshot hyperspectral sensor and high-definition digital camera is similar to the results from the ground spectrometer when using the combined methods (i.e., using VIs multiplying crop height, RF and PLSR to combine VIs and crop heights); and (iv) the spectral performance of the sensors is crucial in LAI estimates (the wheat LAI cannot be accurately estimated over multiple growing stages when using only crop height). The LAI estimates ranked from best to worst are ground spectrometer, UAV snapshot hyperspectral sensor, and UAV high-definition digital camera.
机译：及时准确地估算作物参数对农业管理至关重要。搭载复杂相机的无人机（UAV）与这项工作非常相关，因为它们可以获得比卫星更高的时间，空间和地面分辨率的遥感图像。在这项研究中，我们评估（i）使用近地光谱仪（350〜2500 nm，700 nm处3 nm，1400 nm处8.5 nm，2100 nm处6.5 nm）进行作物参数估计的性能快照高光谱传感器（450〜950 nm，532 nm时为8 nm）和高清数码相机（可见，R，G，B）; （ii）作物表面模型（CSM），基于RGB的植被指数（VI），基于高光谱的VI及其结合的方法，可以对作物参数进行多时相估计并绘制参数。通过使用线性和指数方程，随机森林（RF）回归和偏最小二乘回归（PLSR）结合基于无人机的光谱VI和作物高度，可以获得估计的叶面积指数（LAI）和地上生物量（AGB） （来自CSM）。结果表明：（i）当作物高度与多个生长期的AGB正相关时，光谱VI与单个生长期的LAI和AGB密切相关; （ii）VI乘以作物高度和AGB之间的相关性大于单个VI与作物高度之间的相关性; （iii）当使用组合方法时（例如，使用VI乘以作物高度，RF和PLSR来组合VI和使用VI）时，安装在无人机上的快照高光谱传感器和高清数码相机的AGB估算值与地面光谱仪的结果相似。作物高度）; （iv）传感器的光谱性能在LAI估算中至关重要（当仅使用作物高度时，无法在多个生育阶段准确估算小麦的LAI）。对LAI的评估从最佳到最差，分别是地面光谱仪，无人机快照高光谱传感器和无人机高清数码相机。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号