Monitoring Forest Environment Factor Based On Wireless Sensor Networks

Under the background of global warming, forest environment system plays an important role in the whole climate change. At first, scholars put more energy on the photosynthesis of vegetation on the ground, ignoring the important role of the underground soil in the whole ecosystem. With the further development of science, scholars have found that as a whole ecosystem, the ground is very important. So we use the wireless sensor network to monitor the environmental factors of forest, including the environmental factors of the ground.The experimental design of this paper is based on the study of the two parts of the ground. For the first part of the study, the corresponding research methods and monitoring instruments have been developed, improved, and applied. At first the gas phase chromatograph method for study of soil carbon content has a big change. The micrometeorological method, static chamber method, and dynamic chamber method have been widely applied in the carbon content in the soil tests. But these techniques have more or less drawbacks. For example, micro meteorology measurement method is a method through a flux tower observations, although the monitoring range is very wide and it can monitor for a long time, the flux tower building cost is high and the maintenance is expensive, which causes an economic barrier for a wide range of applications. In this paper, the information fusion method based on Kalman filter is designed to improve the accuracy of soil respiration monitoring system. In addition, for the monitoring of the forest land, the cost of the construction of the tower is more expensive, although the flux tower is used to monitor the ecological environment changes in a certain range of large area. After the completion of the construction, the flux tower can only be fixed at some points of the monitoring environment because of be lack of mobility. So this paper designs a set of monitoring system based on wireless sensor network to monitor and detect the large number of sensors.The experimental results show that:1. Soil carbon flux monitoring system is feasible based on Fick law, and can achieve real-time monitoring of soil respiration, but the accuracy is not high enough,and the error is about 8%. The two information fusion algorithm based on Kalman filtering algorithm is to improve significantly the accuracy of the soil carbon flux monitoring. The results show that for the upper part of the ground, three climate factors exist great temporal and spatial variation in the camophor canopy. Especially, the top layers (layer 6th and 7th) are suffering the most powerful solar radiation, followed by bottom two layers(lay 1th and 2th). Comparatively, the solar radiation intensity is minimum in middle layers (layer 3th,4th and 5th). As the canopy height changes, the variation trend of temperature is almost as same as the solar radiation intensity. However, the diversity between the top layers and the middle layers is smaller, compared with the variety of solar radiation. The variation trend of relative humidity is completely the opposite as temperature is. With the timely dynamic changes, the fluctuation range of temperature and relative humidity is greater than the solar radiation in the top layers during the light day, due to the influence of the transpiration of canopy leaves. And as time changes, the fluctuation range of solar radiation intensity is greater in middle layers. The reason is that the spatial distribution of leaves is different in canopy, so the solar radiation intensity is different when the solar zenith angle is changed. From the above experiments, we know that the wireless sensor network system designed in this paper can take the burden of monitoring forest environmental factors, and the whole system can complete the field monitoring of large scale and long time.