Spatio-temporal variation analysis of soil temperature based on wireless sensor network

Abstract: Soil temperature is a key factor for best planting dates decision-making in the large scale farming areas of northeast China because of high latitudes and frigid environment. Continuous data were collected from a wireless sensor network (WSN)-based monitoring system to exactly analyze and understand soil temperature of the whole farmland. Using the classical statistics and geo-statistics methods, real-time monitoring data were analyzed with three aspects, i.e. temporal variation, spatial variation and spatio-temporal variation. Temporal variation analysis of each sensor node showed a sinusoidal curve of daily soil temperature and gave the long-term trend of daily average soil temperature in a certain period. Spatial variation analysis provided the spatial distribution map of daily average soil temperature within a study region for a certain day. Spatio-temporal variation analysis quantified the variation process of the spatial distribution over time by the monitored classes distribution indicator (MCDI) proposed. Experimental results showed that the above variations analysis of the real-time data provide an effective approach to determine whole-farmland soil temperature.