Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems

Area of Science:

• Environmental Science
• Forest Ecology
• Sensor Technology

Background:

• Climate change necessitates accurate forest microclimate monitoring.
• Wireless Sensor Networks (WSNs) offer potential for microclimate data collection.
• Limited research exists on WSN accuracy and error correction in forest environments.

Purpose of the Study:

• Evaluate the accuracy of wireless sensor temperature and humidity data in subtropical forests.
• Identify sources of observation error for wireless sensors.
• Develop and validate correction models to improve microclimate data accuracy.

Main Methods:

• Field experiments in two subtropical forests in Zhejiang Province, China.
• Comparison of wireless sensor data with standard meteorological data.
• Analysis of error sources and development of correction models using humidity as a factor.

Main Results:

• Wireless sensor data showed good overall accuracy but with systematic errors.
• Temperature errors varied diurnally (overestimated daytime, underestimated nighttime).
• Humidity data were generally overestimated; correction models improved accuracy.

Conclusions:

• WSNs are valuable for forest microclimate monitoring, but error analysis is crucial.
• Correction models effectively enhance data reliability.
• Sensor shell material may influence errors, indicating a need for shading measures.