Seasonal wireless sensor network link performance in boreal forest phenology monitoring

Rankine, Cassidy; Sánchez‐Azofeifa, Arturo; MacGregor, M.H.

doi:10.1109/sahcn.2014.6990366

Cited by 5 publications

(13 citation statements)

References 15 publications

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“…; Rankine et al . ). Precision microclimate data can be coupled with phenocam‐derived datasets and low‐cost full‐genome sequencing of thousands of individuals to allow better modeling of climate–phenology relationships and identification of traits for species adaptability to climate change (Whitham et al .…”

Section: Next‐generation Monitoringmentioning

confidence: 97%

“…Wireless-mesh sensor networks that are used to measure soil properties, micro-meteorological parameters (temperature/relative humidity), and photosynthetically active radiation can quantify environmental drivers of phenology at considerably better spatial resolutions than traditional weather stations (Burgess et al 2010 ;Rankine et al 2014 ). Precision microclimate data can be coupled with phenocam-derived datasets and low-cost full-genome sequencing of thousands of individuals to allow better modeling of climate-phenology relationships and identifi cation of traits for species adaptability to climate change (Whitham et al 2006 ).…”

Section: Mesh Sensor Networkmentioning

confidence: 99%

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Using phenocams to monitor our changing Earth: toward a global phenocam network

Brown

Hultine

Steltzer

et al. 2016

Frontiers in Ecol & Environ

230

184

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Rapid changes to the biosphere are altering ecological processes worldwide. Developing informed policies for mitigating the impacts of environmental change requires an exponential increase in the quantity, diversity, and resolution of field‐collected data, which, in turn, necessitates greater reliance on innovative technologies to monitor ecological processes across local to global scales. Automated digital time‐lapse cameras – “phenocams” – can monitor vegetation status and environmental changes over long periods of time. Phenocams are ideal for documenting changes in phenology, snow cover, fire frequency, and other disturbance events. However, effective monitoring of global environmental change with phenocams requires adoption of data standards. New continental‐scale ecological research networks, such as the US National Ecological Observatory Network (NEON) and the European Union's Integrated Carbon Observation System (ICOS), can serve as templates for developing rigorous data standards and extending the utility of phenocam data through standardized ground‐truthing. Open‐source tools for analysis, visualization, and collaboration will make phenocam data more widely usable.

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Section: Next‐generation Monitoringmentioning

confidence: 97%

Section: Mesh Sensor Networkmentioning

confidence: 99%

Using phenocams to monitor our changing Earth: toward a global phenocam network

Brown

Hultine

Steltzer

et al. 2016

Frontiers in Ecol & Environ

230

184

View full text Add to dashboard Cite

show abstract

“…The spatial extent of the WSN footprint accounted for approximately 55% of measured flux measurements. Additional details on the WSN deployment and technical capabilities can be found in Rankine et al [ 53 ]. Individual nodes were outfitted with an upward and downward facing quantum sensors (SQ-110, Apogee Instruments Inc.), providing transmitted PPFD and soil reflected PPFD measurements, respectively.…”

Section: Methodsmentioning

confidence: 99%

Testing of Automated Photochemical Reflectance Index Sensors as Proxy Measurements of Light Use Efficiency in an Aspen Forest

Castro

Sánchez‐Azofeifa

2018

Sensors

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Commercially available autonomous photochemical reflectance index (PRI) sensors are a new development in the remote sensing field that offer novel opportunities for a deeper exploration of vegetation physiology dynamics. In this study, we evaluated the reliability of autonomous PRI sensors (SRS-PRI) developed by METER Group Inc. as proxies of light use efficiency (LUE) in an aspen (Populus tremuloides) forest stand. Before comparisons between PRI and LUE measurements were made, the optical SRS-PRI sensor pairs required calibrations to resolve diurnal and seasonal patterns properly. An offline diurnal calibration procedure was shown to account for variable sky conditions and diurnal illumination changes affecting sensor response. Eddy covariance measurements provided seasonal gross primary productivity (GPP) measures as well as apparent canopy quantum yield dynamics (α). LUE was derived from the ratio of GPP to absorbed photosynthetically active radiation (APAR). Corrected PRI values were derived after diurnal and midday cross-calibration of the sensor’s 532 nm and 570 nm fore-optics, and closely related to both LUE (R2 = 0.62, p < 0.05) and α (R2 = 0.72, p < 0.05). A LUE model derived from corrected PRI values showed good correlation to measured GPP (R2 = 0.77, p < 0.05), with an accuracy comparable to results obtained from an α driven LUE model (R2 = 0.79, p < 0.05). The automated PRI sensors proved to be suitable proxies of light use efficiency. The onset of continuous PRI sensors signifies new opportunities for explicitly examining the cause of changing PRI, LUE, and productivity over time and space. As such, this technology represents great value for the flux, remote sensing and modeling community.

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“…These two papers offer a guide for our future work investigating the low-power link performance in forest environment. To monitor a Canadian boreal forest ecosystem, Rankine et al [ 41 ] operate a wireless sensor network; they report that the forest environment is so complex that it is very hard to accurately model the link performance; they mainly focus on investigating the variation of link RSSI, and they believe that the canopy structure, the wind speed and the off leaves possibly impact the link performance.…”

Section: Related Workmentioning

confidence: 99%

Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests

Ding

Sun

Yang

et al. 2016

Sensors

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Wireless sensor networks are expected to automatically monitor the ecological evolution and wildlife habits in forests. Low-power links (transceivers) are often adopted in wireless sensor network applications, in order to save the precious sensor energy and then achieve long-term, unattended monitoring. Recent research has presented some performance characteristics of such low-power wireless links under laboratory or outdoor scenarios with less obstacles, and they have found that low-power wireless links are unreliable and prone to be affected by the target environment. However, there is still less understanding about how well the low-power wireless link performs in real-world forests and to what extent the complex in-forest surrounding environments affect the link performances. In this paper, we empirically evaluate the low-power links of wireless sensors in three typical different forest environments. Our experiment investigates the performance of the link layer compatible with the IEEE 802.15.4 standard and analyzes the variation patterns of the packet reception ratio (PRR), the received signal strength indicator (RSSI) and the link quality indicator (LQI) under diverse experimental settings. Some observations of this study are inconsistent with or even contradict prior results that are achieved in open fields or relatively clean environments and thus, provide new insights both into effectively evaluating the low-power wireless links and into efficiently deploying wireless sensor network systems in forest environments.

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Seasonal wireless sensor network link performance in boreal forest phenology monitoring

Cited by 5 publications

References 15 publications

Using phenocams to monitor our changing Earth: toward a global phenocam network

Using phenocams to monitor our changing Earth: toward a global phenocam network

Testing of Automated Photochemical Reflectance Index Sensors as Proxy Measurements of Light Use Efficiency in an Aspen Forest

Link Investigation of IEEE 802.15.4 Wireless Sensor Networks in Forests

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