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Analysis of Dynamic Change Regulation of Water and Salt in Saline-Alkali Land Based on Big Data

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Cloud Computing and Security (ICCCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11063))

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Abstract

With the rapid development of the “Internet plus”, the monitoring service of saline-alkali land has undergone profound changes, intelligent technologies such as big data, cloud computing and data mining are gradually being applied to analyze the changing trend of saline-alkaline lands. In order to study the dynamic changes rule of saline-alkali land, using the synchronous monitoring system of the Internet of things to monitor soil moisture, salt content and other relevant data continuously. Then taking the soil of Yong’an town in Kenli County as the research object, the change trend and correlation of the key factors such as soil temperature, salt and water and pH are studied. The results show that the soil water content and salt content had a relatively obvious seasonal change. The soil was alkaline soil, and the change of pH value was not obvious with the season. Correlation analysis shows that there is a significant positive correlation between water content and salt content in most months, and correlations between the two factors and the other soil factors are different. Through the research on the trend and correlation of key factors such as soil water and salt, revealed the factors that affect the change of water content and salt content in the area which provided reference for the improvement of soil salinization in the next step.

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Acknowledgements

This work was financially supported by the following project:

(1) The Independent Innovation and Achievement Transformation of Shandong Province under Grant No. 2014ZZCX07106.

(2) Science and Technology development Program of Shandong Province under Grant No. 2014GNC110012.

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Correspondence to Pingzeng Liu .

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Zhao, R., Liu, P., Li, H., Yu, X., Wang, X. (2018). Analysis of Dynamic Change Regulation of Water and Salt in Saline-Alkali Land Based on Big Data. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11063. Springer, Cham. https://doi.org/10.1007/978-3-030-00006-6_28

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  • DOI: https://doi.org/10.1007/978-3-030-00006-6_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00005-9

  • Online ISBN: 978-3-030-00006-6

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