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[1]Ji Jingjing,Bai Liying,She Dongli,et al.Comparative Study on Retrieval Model of Dissolved N2O Concentration in Drainage Ditch Based on GF-1 Satellite Remote Sensing[J].Research of Soil and Water Conservation,2024,31(05):257-264.[doi:10.13869/j.cnki.rswc.2024.05.035]

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Comparative Study on Retrieval Model of Dissolved N₂O Concentration in Drainage Ditch Based on GF-1 Satellite Remote Sensing

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 31 Number of periods: 2024 05 Page number: 257-264 Column: Public date: 2024-08-10

Title:: Comparative Study on Retrieval Model of Dissolved N₂O Concentration in Drainage Ditch Based on GF-1 Satellite Remote Sensing

Author(s):: Ji Jingjing¹, Bai Liying², She Dongli¹, Guan Wei³, Ali mu·Abu laiti¹, Pan Yongchun¹; (1.College of Agricultural Science and Engineering, Hohai University, Nanjing 211100, China; 2.Zhenjiang Branch of Jiangsu Provincial Hydrology and Water Resources Survey Bureau, Zhenjiang, Jiangsu 21208, China; 3.Jiangsu Linhai Farm Co., Ltd., Sheyang, Jiangsu 224353, China)

Keywords:: N₂O concentration; GF-1 satellite; inversion; machine learning

CLC:: X87

DOI:: 10.13869/j.cnki.rswc.2024.05.035

Abstract:: [Objective]The aims of this study are to explore the feasibility of using GF-1 satellite data to retrieve the concentration of dissolved nitrous oxide(N₂O)in water, so as to provide an effective way to realize low-cost and high-efficiency real-time monitoring of water quality. [Methods]The 1st and 5th drainage ditches in Qingtongxia Irrigation District of Ningxia were selected as the research objects, and the reflectance and water quality parameters of GF-1 satellite image band, which were highly correlated with the concentration of dissolved N₂O in the drainage ditches, were selected as independent variables, and the optimal combination of independent variables was determined by optimal subset screening method. Multiple linear regression, BP neural network and support vector machine models were respectively constructed to predict and compare the concentration of dissolved N₂O in water. [Results]The water temperature(T)and dissolved organic carbon(DOC)were the main factors affecting the concentration of dissolved N₂O in water, and satellite bands such as near infrared(NIR)were significantly correlated with the variation trend of dissolved N₂O concentration in water. When the independent variable including 7 factors such as T and NIR, the model had the best prediction effect. Among the three models, the R² of BP neural network model was 0.64, which had the highest prediction accuracy. [Conclusion]There is a complex correlation between GF-1 satellite data and water quality parameters and dissolved N₂O concentration in water bodies, and BP neural network can use GF-1 satellite data to retrieve dissolved N₂O concentration in water bodies with high accuracy.

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Last Update: 2024-08-10