Application of a Multi-Chamber Fusion Algorithm Based on the Fick's Theorem to Quantify Soil Respiration
文献类型: 外文期刊
作者: Xie, Bao Liang 1 ; Zhu, Yihang 1 ; Zhang, Xiao Bing 1 ; Gu, Qing 1 ; Zheng, Ke Feng 1 ; Hu, Jun Guo 2 ;
作者机构: 1.Zhejiang Acad Agr Sci, Inst Digital Agr, Hangzhou 310021, Peoples R China
2.Zhejiang Agr & Forestry Univ, Sch Informat Engn, Hangzhou 311300, Peoples R China
关键词: Soil respiration; multi-chamber fusion; Fick's theorem; wavelet packet transform; the biggest-smallest approach degree; the Dempster-Shafer evidence theory
期刊名称:IEEE SENSORS JOURNAL ( 影响因子:3.301; 五年影响因子:3.441 )
ISSN: 1530-437X
年卷期: 2021 年 21 卷 3 期
页码:
收录情况: SCI
摘要: Reliable, low-cost and accurate monitoring of soil respiration is an important challenge that must be solved to fully understand the contribution of soil dynamics to climate change; however, accuracy obtained by single-chamber is insufficient. This article proposes a multi-chamber fusion method for integrating multi-source information measured using low-cost sensors. The proposed algorithm initially uses Fick's first diffusion law to calculate the soil carbon flux values for five chambers, followed by multi-layer decomposition of a wavelet packet transform (WPT) to eliminate high-frequency noise. Then, the basic probability assignment (BPA) of each sensor is calculated via the Biggest-smallest Approach Degree and used to assign the Dempster-Shafer (D-S) fusion subjected BPA to determine the distribution weight of each gas chamber. Finally, the decision layer fusion is defined as the product of the chamber weights and feature signals obtained by wavelet multi-layer decomposition. The performance of the proposed algorithm was evaluated against existing algorithms using real data collected using a low-cost prototype device in an evergreen broad-leaved forest environment and compared to the data generated by an expensive commercial device. The proposed algorithm significantly improved the accuracy of soil respiration monitoring for the low-cost prototype device.
- 相关文献
作者其他论文 更多>>
-
Yield prediction through UAV-based multispectral imaging and deep learning in rice breeding trials
作者:Zhou, Hongkui;Lou, Weidong;Gu, Qing;Ye, Ziran;Hu, Hao;Zhang, Xiaobin;Huang, Fudeng
关键词:UAV; Yield prediction; Multispectral imaging; Deep learning; Rice breeding
-
Quantifying tree-level peach flowering dynamics using UAV imagery and an optimized instance segmentation model
作者:Gu, Qing;Cheng, Jiayu;Lou, Weidong;Zhang, Xiaobin;Zhang, Minghao;Li, Xiongwei;Jackson, Robert;Ju, Lei;Zhou, Ji;Chen, Miaojin
关键词:Peach flowering; Phenotype; Unmanned aerial vehicle; Fruit breeding; Instance segmentation
-
Quantitative analysis of watermelon fruit skin phenotypic traits via image processing and their potential in maturity and quality detection
作者:Gu, Qing;Li, Tong;Gu, Qing;Li, Tong;Zhu, Yihang;Zhang, Xiaobin;Hu, Ziwei;Shi, Jun;Zhang, Leichen
关键词:Watermelon; Breeding; Phenotype; Fruit maturity; Fruit quality; Lacunarity
-
Spatiotemporal response of ecosystem services to tourism activities in urban forests
作者:Li, Jiadan;Zhang, Xian;Wang, Kai;Xu, Zhihao;Gu, Qing;Zhang, Zhongchu
关键词:ecosystem service value; land use and land cover; tourism activities; geographically weighted regression; internet big data; tourism management strategies; urban forest
-
Unmanned aerial vehicle-based assessment of rice leaf chlorophyll content dynamics across genotypes
作者:Gu, Qing;Lou, Weidong;Zhu, Yihang;Hu, Hao;Zhao, Yiying;Zhou, Hongkui;Zhang, Xiaobin;Huang, Fudeng
关键词:Oryza sativa L.; Chlorophyll content; Phenotype; Unmanned aerial vehicle; Variety classification
-
Visible/near-infrared Spectroscopy and Hyperspectral Imaging Facilitate the Rapid Determination of Soluble Solids Content in Fruits
作者:Zhao, Yiying;Zhang, Xiaobin;Gu, Qing;Zhu, Yihang;Zhou, Lei;Wang, Wei;Chen, Rongqin;Zhang, Chu
关键词:VIS/NIR spectroscopy; Hyperspectral imaging; Fruit SSC; Data acquisition and analysis; Internal and external interference; Compensation strategy
-
Biomass Estimation of Milk Vetch Using UAV Hyperspectral Imagery and Machine Learning
作者:Hu, Hao;Zhou, Hongkui;Lou, Weidong;Gu, Qing;Hu, Hao;Zhou, Hongkui;Lou, Weidong;Gu, Qing;Cao, Kai;Wang, Jianhong;Zhang, Guangzhi
关键词:UAV; milk vetch; above-ground biomass; hyperspectral imagery; machine learning



