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

机译:基于大数据的盐碱地水盐动态变化规律分析

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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.
机译:随着“互联网+”的迅猛发展,盐碱地的监测服务发生了深刻的变化,大数据,云计算和数据挖掘等智能技术逐渐被应用来分析盐碱地的变化趋势。 。为了研究盐碱地的动态变化规律,利用物联网同步监测系统对土壤水分,盐分等相关数据进行连续监测。然后以垦利县永安镇土壤为研究对象,研究了土壤温度,盐分,水分和pH等关键因素的变化趋势及其相关性。结果表明,土壤水分和盐分含量具有较明显的季节变化。土壤为碱性土壤,pH值随季节变化不明显。相关分析表明,在大多数月份中,水分和盐分含量之间存在显着的正相关,并且这两个因素与其他土壤因素之间的相关性不同。通过对土壤水分和盐分等关键因素的变化趋势及其相关性的研究,揭示了影响该地区水分和盐分变化的因素,为下一步土壤盐碱化的改善提供参考。

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