DocumentCode :
1772801
Title :
Seasonal wireless sensor network link performance in boreal forest phenology monitoring
Author :
Rankine, C.J. ; Sanchez-Azofeifa, G.A. ; MacGregor, M.H.
Author_Institution :
Dept. Earth & Atmos. Sci., Univ. of Alberta, Edmonton, AB, Canada
fYear :
2014
fDate :
June 30 2014-July 3 2014
Firstpage :
302
Lastpage :
310
Abstract :
While indoor wireless sensor network (WSN) research has recently flourished for monitoring civil and industrial infrastructure, considerably less attention has been given to the development of reliable outdoor WSNs capable of long-term operation in challenging remote locations. We present wireless sensor network link performance results from the first year of monitoring micro-meteorological conditions alongside the 802.15.4 link received signal strength indicator (RSSI) within an old growth stand of deciduous boreal Aspen forest (Populus tremuloides) in Northern Alberta, Canada. Thirty-six weather proof nodes were equipped with meteorological sensors and distributed across one hectare in the forest understory to assess the application of WSNs for observing high resolution changes in seasonal ecosystem productivity and forest phenology. We describe here the density distribution of node RSSI using Gaussian kernel density estimates in relation to node antenna-receiver orientation and vegetation seasonality. RSSI across the network displays a lognormal distribution with an increasing bimodal tendency with path length through the forest stand. Spatial variability in RSSI is discussed with respect to forest structure. A strong temporal relationship between RSSI variability and plant canopy development is observed with a 20dBm or 100 fold difference in mean network radio signal power from spring leaf presence to fall leaf absence. The meteorological and biophysical factors associated with this trend are explored using multiple regression and relative factor importance analysis. Our results indicate that in addition to meteorological data, spectral vegetation density metrics are useful in assisting deployment planning and network performance diagnostics when using wireless sensor networks for remote forestry applications. The longevity and performance of this outdoor WSN can be seen as a new standard for harsh network-climate tolerance in northern boreal environments.
Keywords :
environmental monitoring (geophysics); remote sensing; vegetation; wireless sensor networks; Canada; Gaussian kernel density estimates; Northern Alberta; Populus tremuloides; boreal forest phenology monitoring; civil infrastructure; deciduous boreal Aspen forest; fall leaf absence; indoor wireless sensor network; industrial infrastructure; long term operation; micrometeorological conditions; outdoor WSN; received signal strength indicator; seasonal ecosystem productivity; seasonal wireless sensor network link performance; spatial variability; spectral vegetation density metrics; spring leaf presence; Meteorology; Monitoring; Receivers; Temperature sensors; Vegetation mapping; Wireless sensor networks; Forests; Micrometeorology; Phenology; RSSI; Wireless Sensor Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensing, Communication, and Networking (SECON), 2014 Eleventh Annual IEEE International Conference on
Conference_Location :
Singapore
Type :
conf
DOI :
10.1109/SAHCN.2014.6990366
Filename :
6990366
Link To Document :
بازگشت