Study on Temporal and Spatial Variation of Soil Moisture Based on Sensing Data of Internet of Things

Soil moisture plays an important role in the agricultural production. The temporal and spatial variation of soil moisture is an important index to evaluate soil water content. In this paper, the variation of soil moisture in space and time is analyzed by time series analysis and geostatistical methods using Internet of things (IOT) data in order to provide a theoretical basis for the rational arrangement and precise management in farm. The results show that the change of soil moisture is mainly affected by the distribution of rainfall and there is obvious seasonal variation: the soil moisture was poor from April to July and gradually improved after August. From a viewpoint of vertical and lateral distribution, the soil moisture at 4 soil depths 20, 40, 60, 80cm significantly differentiated. Due to the greater impact of the outside climate, the closer to the surface, the greater the coefficient of variation is. Meanwhile the coefficient of variation decreases with the deepening of the soil layer as well. In addition, the soil water content in the field of each depth has a moderate degree of spatial correlation. With the increase of soil depth, the spatial correlation of soil moisture reduced. The spatial correlation before irrigation was slightly smaller than the spatial correlation after irrigation.