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Mathematical Problems in Engineering
Volume 2014, Article ID 840278, 8 pages
http://dx.doi.org/10.1155/2014/840278
Research Article

Sensor Nodes Deployment Strategy for Monitoring Roadside Biomass Carbon Stocks of Tourism Destination: A Case of Wulong World Natural Heritage, China

1Tourism School, Sichuan University, Chengdu 610064, China
2College of Tourism and Geography, Chongqing Normal University, No. 12, Tianchen Road, Shapingba District, Chongqing 400047, China
3Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, A11 Datun Road, Chaoyang District, Beijing 100101, China
4State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China

Received 27 December 2013; Accepted 4 March 2014; Published 7 April 2014

Academic Editor: Fuzhong Nian

Copyright © 2014 Jun Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Since the late 1978s, China has experienced one of the highest tourism growth rates in the world, which in turn has driven extensive land-use and land-cover change. The aim of this research is to develop a sensor nodes positioning strategy for detecting land use related dynamics of vegetation carbon stocks of Wulong world natural heritage. Based on the assessment of road networks’ influences on biomass carbon stocks, roadside biomass carbon stocks risk index was proposed as a sensor deployment strategy to identify the optimal positions of the sensors to detect the changes in vegetation carbon stocks. Forest and cropland around the lower levels of roads should be the most important region of sensor nodes deployment strategy. The results generated from this study have the ability to achieve optimal solution of spatial positioning problem with minimum number of sensors in biomass carbon monitoring sensor networks. This analysis appears to have great potential for a wide range of practical applications in tourism industry in China.