基于无线传感网的森林环境监测系统研究
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摘要
森林是生态系统的主体,在全球碳循环中扮演这非常重要的角色。对森林生态非生物环境因子进行持续监测,进而阐明森林生态环境因子和森林生态系统的结构与功能之间的相互作用机制,可为森林的合理经营提供理论依据,为对森林生态效益进行科学计量和评价,为制定合理的环境政策具有十分重要的战略意义。
运用自组织网络的方式进行随机与格网相结合的方法,搭建了森林环境监测系统。描述了传感器节点的部署方法、数据路由协议及数据包内容,分析了在网络传输中数据缺失的原因和补偿的策略。通过多模态数据交叉测量与感知数据的综合认知技术,实现了对森林生态环境的连续时空多点协同监测。
论文以林内传感器节点的光照与温湿度数据为基础,运用IDW插值算法绘制了光照、温湿度的分布图,用线性回归法对相互之间的相关性进行分析,结果表明:无论林内、林缘和林外温湿度的变化相关度都很高;光照对温湿度的影响在林缘和林外的要略低于林内,表明在同样的光照条件下,森林具有良好的降温和增湿效果。
本研究还利用无线传感器节点与红外二氧化碳探头结合,在密闭容器内获得土壤表面的温湿度和二氧化碳浓度,通过对获得的数据进行重新标定和校正,计算出土壤表面二氧化碳通量,与Li-8100土壤测定仪对同一土壤样地进行的实验比较,其结果差别不到4%,这为土壤碳通量的测量的提供了一种新的低成本方法。
最后总结了无线传感网在森林环境监测中的应用中存在的问题,阐述了与森林生态学结合方面存在的挑战,并展望了未来的发展方向。
Forest is the main part of terrestrial ecosystem, which plays a very important role in global carbon cycle. Forest environment monitoring could illuminate the configuration and function of the forest. Studying the interaction between forest and environment will provide the principle for managing the forest reasonably. On the other hand,scientific computation and evaluation of ecological benefit of forest is important to constitute reasonable environment policy.
In this paper we proposed a way using stochastic and grid-based deployment to set up the system in the forest to sense light intensity,humidity and temperature. Using multi-hop forward, all sensor nodes send the packets to the sink. We analyze the data from multi-dimension after translating the data.
Based on the light, temperature and humidity data, we drew the distribution map of light, temperature and humidity in the forest. We used linear regression to study the relativity of them and the results depicted that the relativity between temperature and humidity was high wherever it is. Light affected more in the forest than at the edge or out of the forest. It revealed that forest could hold the humidity and lower the temperature.
This study measured the soil surface carbon dioxide concentration variation with infrared sensor and wireless sensor in the closed container. After comparing and calibrating the sensory data to the Li-8100 data, we calculated the carbon dioxide flux with sensory data. And then we contrasted to the experiment result of Li-8100. The result showed that the relative error was small. And it would provide a new method to measure the soil surface carbon dioxide flux .
At the end,this paper concluded the problems in the application of WSN in forest environment monitoring,expatiated the challenges of WSN in combination with forest ecology,and prospected the future development.
运用自组织网络的方式进行随机与格网相结合的方法,搭建了森林环境监测系统。描述了传感器节点的部署方法、数据路由协议及数据包内容,分析了在网络传输中数据缺失的原因和补偿的策略。通过多模态数据交叉测量与感知数据的综合认知技术,实现了对森林生态环境的连续时空多点协同监测。
论文以林内传感器节点的光照与温湿度数据为基础,运用IDW插值算法绘制了光照、温湿度的分布图,用线性回归法对相互之间的相关性进行分析,结果表明:无论林内、林缘和林外温湿度的变化相关度都很高;光照对温湿度的影响在林缘和林外的要略低于林内,表明在同样的光照条件下,森林具有良好的降温和增湿效果。
本研究还利用无线传感器节点与红外二氧化碳探头结合,在密闭容器内获得土壤表面的温湿度和二氧化碳浓度,通过对获得的数据进行重新标定和校正,计算出土壤表面二氧化碳通量,与Li-8100土壤测定仪对同一土壤样地进行的实验比较,其结果差别不到4%,这为土壤碳通量的测量的提供了一种新的低成本方法。
最后总结了无线传感网在森林环境监测中的应用中存在的问题,阐述了与森林生态学结合方面存在的挑战,并展望了未来的发展方向。
Forest is the main part of terrestrial ecosystem, which plays a very important role in global carbon cycle. Forest environment monitoring could illuminate the configuration and function of the forest. Studying the interaction between forest and environment will provide the principle for managing the forest reasonably. On the other hand,scientific computation and evaluation of ecological benefit of forest is important to constitute reasonable environment policy.
In this paper we proposed a way using stochastic and grid-based deployment to set up the system in the forest to sense light intensity,humidity and temperature. Using multi-hop forward, all sensor nodes send the packets to the sink. We analyze the data from multi-dimension after translating the data.
Based on the light, temperature and humidity data, we drew the distribution map of light, temperature and humidity in the forest. We used linear regression to study the relativity of them and the results depicted that the relativity between temperature and humidity was high wherever it is. Light affected more in the forest than at the edge or out of the forest. It revealed that forest could hold the humidity and lower the temperature.
This study measured the soil surface carbon dioxide concentration variation with infrared sensor and wireless sensor in the closed container. After comparing and calibrating the sensory data to the Li-8100 data, we calculated the carbon dioxide flux with sensory data. And then we contrasted to the experiment result of Li-8100. The result showed that the relative error was small. And it would provide a new method to measure the soil surface carbon dioxide flux .
At the end,this paper concluded the problems in the application of WSN in forest environment monitoring,expatiated the challenges of WSN in combination with forest ecology,and prospected the future development.
引文
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[2]贺庆棠.森林环境学[M].北京:高等教育出版社,2005.
[3]中国林业与生态建设状况公报http://www.gov.cn/gzdt/2008-01/21/content_864441.htm
[4]王奉安.森林碳汇的作用[J].辽宁:环境保护与循环经济.201030(5):26-17.
[5] http://www.ccchina.gov.cn/en/NewsInfo.asp?NewsId=21190
[6]全国第七次森林资源清查结果, http://www.forestry.gov.cn/portal/main/s/65/content-326341.html
[7]李俊清.森林生态学[M].北京:高等教育出版社,2006.
[8]张会儒,唐守正,王彦辉.德国森林资源和环境监测技术体系及其借鉴[J].世界林业研究.200215(2):63-70.
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[13] Ituen,I.;Sohn,G.The Environmental applications of wireless Sensor networks[J]. Inter. J.Content 2007,3,1-7.
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[33]李光辉,赵军,王智.基于无线传感器网络的森林火灾检测预警系统[J].传感技术学报,2006,19(6):2760-2764.
[34]陆志平,秦会斌,王春芳.无线传感器巫昂罗在森林火灾检测中的应用[J].杭州电子科技大学学报,2006,26(5):48-51.
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[37] R?zvan Mus?loiu-e , Andreas Terzis , Katalin Szlavecz , Alex Szalay , Joshua Cogan , Jim Gray. Life Under your feet: a wireless soil ecology sensor network.
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[2]贺庆棠.森林环境学[M].北京:高等教育出版社,2005.
[3]中国林业与生态建设状况公报http://www.gov.cn/gzdt/2008-01/21/content_864441.htm
[4]王奉安.森林碳汇的作用[J].辽宁:环境保护与循环经济.201030(5):26-17.
[5] http://www.ccchina.gov.cn/en/NewsInfo.asp?NewsId=21190
[6]全国第七次森林资源清查结果, http://www.forestry.gov.cn/portal/main/s/65/content-326341.html
[7]李俊清.森林生态学[M].北京:高等教育出版社,2006.
[8]张会儒,唐守正,王彦辉.德国森林资源和环境监测技术体系及其借鉴[J].世界林业研究.200215(2):63-70.
[9]国家林业局.国家林业局陆地生态系统定位研究网络中长期发展规划(2008-2020),2008.
[10]李汉玲. WSN24-Link系列无线传感网络及应用[J].机械工程与自动化,200802:163-165.
[11]司海飞,杨忠,王珺.无线传感网络研究现状与应用[J].机电工程,201128(1):16-21.
[12]顾振宇.无线传感网国内外现状. http://www.istis.sh.cn/list/list.aspx?id=6751
[13] Ituen,I.;Sohn,G.The Environmental applications of wireless Sensor networks[J]. Inter. J.Content 2007,3,1-7.
[14] J. Porter et al, Wireless sensor networks for Ecology, BioScience, Vol. 55 No.7, pp.561-567, 570, Jul. 2005.
[15] MTS/MDA Sensor Board Users Manual, Crossbow technology Inc., San Jose, CA, 2006.
[16]闫丛丛.用于图像采集的ZigBee无线传感器网络节点设计[J/OL].http://www.paper.edu.cn/index.php/default/releasepaper/downPaper/200912-1231
[17]王如松.资源、环境与产业转型的复合生态管理[J].系统工程理论与实践.2003(2):125-132
[18]王绍刚,何国金,刘定生,汪小钦.森林碳循环模型方法研究与进展[J].科技导报,200826(9):72-77
[19] J. de Rosnay. The macroscope: a new world scientific system. Harper & Row, 1979.
[20] A. Mainwaring, J. Polastre, R. Szewczyk, D. Culler, and J. Anderson. Wireless sensornetworks for habitat monitoring. In Proceedings of the First ACM International Workshop on Wireless Sensor Networks and Applications,2002.
[21] K. Martinez, J. K. Hart, and R. Ong. Environmental sensor networks. IEEE Computer, 38(8):50–56, August 2004.
[22] E. Osterweil and D. Estrin. ESS: The extensible sensing system. http://www.cens.ucla.edu/ eoster/ess/, Apr. 2004.
[23]毛晓峰,杨珉,毛迪林.无线传感器网络应用综述[J].计算机应用与软件,2008,(3):179-181.
[24]李海光.基于IEEE+802.15.4_Zigbee的无线传感网络研究[D].硕士论文.20080408
[25] Gilman Tolle, Joseph Polastre, Robert Szewczyk, et al. A macroscope in the redwoods[R]. Proceedings of the 3rd international conference on Embedded networked sensor systems, 2005: 51-63.
[26] Ankur Suri, S.S. Iyengar*, Eungchun Cho.Ecoinformatics using wireless sensor networks: An overview[J].ECOLOGICALINFORMATICS ( 2 0 0 6 ):287– 293
[27] Biagioni, Edoardo S., Bridges, K.W. The application of remote sensor technology to assist the recovery of rare and endangered species.
[28] http://www.intel.com/technology/techresearch/research/rs01031.htm.
[29] http://www.sim.cas.cn/kxcb/kpcg/200909/t20090915_2483910.html
[30] Mo LI,Yunhao Liu. Underground coal mine monitoring with wireless sensor networks[C]. ACM Transcations on sensor neworks,2009
[31] Mo Lufeng,He Yuan,Liu Yunhao,Zhao Jizhong,Tang Shaojie,Li Xiangyang,Dai Guojun. Canopy closure with GreenOrbs:sustainable sensing in the forest[C]. Sensys 2009
[32]郭忠文,罗汉江,洪锋等.水下无线传感网络的研究进展[J].计算机研究与发展,201047(3):377-389.
[33]李光辉,赵军,王智.基于无线传感器网络的森林火灾检测预警系统[J].传感技术学报,2006,19(6):2760-2764.
[34]陆志平,秦会斌,王春芳.无线传感器巫昂罗在森林火灾检测中的应用[J].杭州电子科技大学学报,2006,26(5):48-51.
[35]张军国,李文彬,韩宁等.基于ZigBee无线传感器网络的森林火灾检测系统的研究[J].北京林业大学学报,2007,29(4):41-45.
[36]唐勇,周明天,张欣.无线传感器网络路由协议研究进展. Journal of Software, Vol.17, No.3, March 2006, pp.410?421
[37] R?zvan Mus?loiu-e , Andreas Terzis , Katalin Szlavecz , Alex Szalay , Joshua Cogan , Jim Gray. Life Under your feet: a wireless soil ecology sensor network.
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