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

Abstract Timely and accurate detection of microclimates is extremely valuable for monitoring and stimulating exchanges of mass and energy in forest ecosystems under climate change. Recently, the rapid growth of wireless sensor networks (WSNs) has provided a new approach for detecting microclimates i...

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Autores principales:	Jiaxin Jin, Ying Wang, Hong Jiang, Xiaofeng Chen
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Wireless Sensor Subtropical Forest Types Temperature-based Sensors Shading Measures Observation Error Medicine R Science Q
Acceso en línea:	https://doaj.org/article/240b0d8c69c54d1da9bc0def83dd5316
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spelling	oai:doaj.org-article:240b0d8c69c54d1da9bc0def83dd53162021-12-02T15:08:37ZEvaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems10.1038/s41598-018-34832-72045-2322https://doaj.org/article/240b0d8c69c54d1da9bc0def83dd53162018-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-34832-7https://doaj.org/toc/2045-2322Abstract Timely and accurate detection of microclimates is extremely valuable for monitoring and stimulating exchanges of mass and energy in forest ecosystems under climate change. Recently, the rapid growth of wireless sensor networks (WSNs) has provided a new approach for detecting microclimates in a complex environment at multiple temporal and spatial scales. However, applications of wireless sensors in forest microclimate monitoring have rarely been studied, and the corresponding observation accuracy, error sources and correction methods are not well understood. In this study, through field experiments in two typical subtropical forest ecosystems in Zhejiang Province, China, the accuracy of the temperature and humidity observed by the wireless sensors was evaluated against standard meteorological data. Furthermore, the observation error sources were analyzed and corresponding correction models were established. The results showed that the wireless sensor-based temperature and humidity values performed well within the total observation accuracy. However, the observation errors varied with season, daily periodicity and weather conditions. For temperature, the wireless sensor observations were overestimated during the daytime while they were underestimated during the nighttime. For humidity, the data observed by the wireless sensors generally appeared as overestimates. Adopting humidity as the corrected factor, correction models were established and effectively improved the accuracy of the microclimatic data observed by the wireless sensors. Notably, our error analysis demonstrated that the observation errors may be associated with the shell material of the wireless sensor, suggesting that shading measures for the wireless sensors should be considered for outdoor work.Jiaxin JinYing WangHong JiangXiaofeng ChenNature PortfolioarticleWireless SensorSubtropical Forest TypesTemperature-based SensorsShading MeasuresObservation ErrorMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-9 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Wireless Sensor Subtropical Forest Types Temperature-based Sensors Shading Measures Observation Error Medicine R Science Q
spellingShingle	Wireless Sensor Subtropical Forest Types Temperature-based Sensors Shading Measures Observation Error Medicine R Science Q Jiaxin Jin Ying Wang Hong Jiang Xiaofeng Chen Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems
description	Abstract Timely and accurate detection of microclimates is extremely valuable for monitoring and stimulating exchanges of mass and energy in forest ecosystems under climate change. Recently, the rapid growth of wireless sensor networks (WSNs) has provided a new approach for detecting microclimates in a complex environment at multiple temporal and spatial scales. However, applications of wireless sensors in forest microclimate monitoring have rarely been studied, and the corresponding observation accuracy, error sources and correction methods are not well understood. In this study, through field experiments in two typical subtropical forest ecosystems in Zhejiang Province, China, the accuracy of the temperature and humidity observed by the wireless sensors was evaluated against standard meteorological data. Furthermore, the observation error sources were analyzed and corresponding correction models were established. The results showed that the wireless sensor-based temperature and humidity values performed well within the total observation accuracy. However, the observation errors varied with season, daily periodicity and weather conditions. For temperature, the wireless sensor observations were overestimated during the daytime while they were underestimated during the nighttime. For humidity, the data observed by the wireless sensors generally appeared as overestimates. Adopting humidity as the corrected factor, correction models were established and effectively improved the accuracy of the microclimatic data observed by the wireless sensors. Notably, our error analysis demonstrated that the observation errors may be associated with the shell material of the wireless sensor, suggesting that shading measures for the wireless sensors should be considered for outdoor work.
format	article
author	Jiaxin Jin Ying Wang Hong Jiang Xiaofeng Chen
author_facet	Jiaxin Jin Ying Wang Hong Jiang Xiaofeng Chen
author_sort	Jiaxin Jin
title	Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems
title_short	Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems
title_full	Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems
title_fullStr	Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems
title_full_unstemmed	Evaluation of Microclimatic Detection by a Wireless Sensor Network in Forest Ecosystems
title_sort	evaluation of microclimatic detection by a wireless sensor network in forest ecosystems
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/240b0d8c69c54d1da9bc0def83dd5316
work_keys_str_mv	AT jiaxinjin evaluationofmicroclimaticdetectionbyawirelesssensornetworkinforestecosystems AT yingwang evaluationofmicroclimaticdetectionbyawirelesssensornetworkinforestecosystems AT hongjiang evaluationofmicroclimaticdetectionbyawirelesssensornetworkinforestecosystems AT xiaofengchen evaluationofmicroclimaticdetectionbyawirelesssensornetworkinforestecosystems
_version_	1718388049241440256

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

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