Retrieval of soil salinity based on multi-source remote sensing data and differential transformation technology

Fei, Zhang; Li, Xingyou; Zhou, X. H.; Chan, Ngai Weng; Tan, Mou Leong; Kung, Hsiang‐te; Shi, Jingchao

doi:10.1080/01431161.2023.2179900

Cited by 6 publications

(2 citation statements)

References 44 publications

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“…However, the existing information systems still have certain risks [8][9][10] in information security, such as data leakage and network attacks. Therefore, in the future, we should pay more attention to improving the security of information systems and adopt more advanced security technologies, such as data encryption and authentication, to ensure the security and stability of information [11][12].…”

Section: Introductionmentioning

confidence: 99%

Research on Efficient Retrieval Method of Key Information of Discipline Inspection and Supervision Based on Digital Technology

Chen,

Cai

2024

Proceedings of the 3rd International Conference on Innovation Design and Digital Technology, ICIDDT 2023, November 3–5, 2023, Z

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Influenced by the characteristics of discipline inspection and supervision information itself, it is difficult to guarantee the correlation between the corresponding retrieval results and the retrieval objectives. Therefore, this paper puts forward the research on the efficient retrieval method of key information of discipline inspection and supervision based on digital technology. After comprehensively analyzing its specific attributes from four aspects: discipline inspection and supervision workflow information, discipline inspection and supervision object type information, discipline inspection and supervision content information and discipline inspection and supervision result information, the LightLDA technology in digital technology is introduced in the specific retrieval method design process, and the information in the retrieval likelihood model of discipline inspection and supervision information is fused with LDA by Wei and Croft in the LightLDA technology, and the information with the greatest likelihood to the retrieval information is taken as the retrieval output result. In the test results, the nDCG value is always stable above 40.0%,recall rates are consistently above 90%, which has obvious advantages compared with the control group.

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Section: Introductionmentioning

confidence: 99%

Research on Efficient Retrieval Method of Key Information of Discipline Inspection and Supervision Based on Digital Technology

Chen,

Cai

2024

Proceedings of the 3rd International Conference on Innovation Design and Digital Technology, ICIDDT 2023, November 3–5, 2023, Z

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“…Some models, such as the salt transport model, the Hydrus-2D model [5], and the SWAP model [6], can simulate the SSC for a long time and across a wide range by inputting meteorological and soil parameters and other data, but due to the uncertainty of the model parameters, its errors continue to accumulate, which affects the accuracy of the simulation. In general, the remote sensing inversion method selects the relevant variables sensitive to SSC through spectral transformation and exponential screening, and performs model verification analysis [7,8]. Based on Sentinel-2A image technology, Wang [9] analyzed the spectral characteristics and parameters of SSC with different salinization soil degrees by using UAV cameras, and established an inversion model.…”

Section: Introductionmentioning

confidence: 99%

ECWS: Soil Salinity Measurement Method Based on Electrical Conductivity and Moisture Content

Mu,

Han,

et al. 2024

Agronomy

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A novel method, ECWS, is proposed for measuring soil initial salinity content (b), based on the soil electrical conductivity EC and soil moisture content WS. This pioneering model rigorously establishes and incorporates the inherent potential correlation among soil bulk conductivity (ECa), soil solution conductivity (ECw), volume water content (θc), and soil salinity content (SSC). First of all, in order to delve the deeper relationship between ECa, ECw, θc and SSC, the soil salinity conductivity conversion coefficient ρa and soil leaching solution salinity conductivity conversion coefficient ρw were employed based on the formula of parallel conducting channels of the soil–water system, and a new measurement model of salinity content was constructed. After that, a mathematical analysis method was used to transform the coefficients of multiple sets of regression equations into matrices to solve ρa, ρw and b. Finally, to validate the accuracy of the proposed ECWS method, verification tests were conducted by utilizing TDR and PWMER sensors. The results with different salinity contents showed that the b size obtained by ECWS model were K2SO4 (1.84 g/kg), NaCl (1.91 g/kg), and KCl (1.92 g/kg). The maximum deviation was less than 0.08 g/kg (relative error less than 5%). The results showed that the influence of different anions and cations on the measurement of salinity content Cl− is greater than that of SO42−, and K+ is greater than that of Na+. This study revealed the relationship between soil electrical conductivity and soil salinity content to a certain extent, and realized the transformation between them, which provided a new method for the measurement of soil salinity content, and also provided a reference for related research on the measurement of soil salinization.

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Comprehensive Survey On Remote Sensing Image Processing Techniques for Image Classification

Tran,

Huynh

2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Retrieval of soil salinity based on multi-source remote sensing data and differential transformation technology

Cited by 6 publications

References 44 publications

Research on Efficient Retrieval Method of Key Information of Discipline Inspection and Supervision Based on Digital Technology

Research on Efficient Retrieval Method of Key Information of Discipline Inspection and Supervision Based on Digital Technology

ECWS: Soil Salinity Measurement Method Based on Electrical Conductivity and Moisture Content

Comprehensive Survey On Remote Sensing Image Processing Techniques for Image Classification

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