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Advances in Environmental Sensor Networks
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Advances in Environmental Sensor Networks

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).

Deadline for manuscript submissions: closed (31 December 2010) | Viewed by 10234

Special Issue Editor

Dr. Tim Wark

E-Mail Website
Guest Editor
CSIRO ICT Centre, 1 Technology Ct, QCAT, Pullenvale, QLD 4069, Australia
Interests: wireless sensor networks; image/audio processing; in-network processing; pattern recognition; adaptive energy management; environmental sensing

Special Issue Information

Dear Colleagues,

Environmental sensing has been a highly compelling application driver for wireless sensor networks since the formation of the field. The lack of continuous energy supplies, dynamic radio environments and significant scientific interest for measurements derived from large-scale, high temporal and spatial resolution deployments, has made this a rich area of research. Despite the progress in the field over the past decade however, many research challenges still remain unsolved ranging from reliable network protocols, adaptive energy management and energy harvesting, through to improved methods for sensor calibration, anomaly detection and multimedia networks. This special issue will present recent research in a range of these areas, and help bring to light some of the key research issues which remain to be solved in order to make wide-spread environmental sensing a reality.

Dr. Tim Wark
Guest Editor

Keywords

  • energy harvesting
  • low-power
  • long-term
  • dynamic
  • adaptive
  • multimedia

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Published Papers (1 paper)

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Research

18 pages, 826 KiB  
Article
Comparison of Laboratory and Field Remote Sensing Methods to Measure Forage Quality
by Xulin Guo, John F. Wilmshurst and Zhaoqin Li
Int. J. Environ. Res. Public Health 2010, 7(9), 3513-3530; https://doi.org/10.3390/ijerph7093513 - 27 Sep 2010
Cited by 23 | Viewed by 9590
Abstract
Recent research in range ecology has emphasized the importance of forage quality as a key indicator of rangeland condition. However, we lack tools to evaluate forage quality at scales appropriate for management. Using canopy reflectance data to measure forage quality has been conducted [...] Read more.
Recent research in range ecology has emphasized the importance of forage quality as a key indicator of rangeland condition. However, we lack tools to evaluate forage quality at scales appropriate for management. Using canopy reflectance data to measure forage quality has been conducted at both laboratory and field levels separately, but little work has been conducted to evaluate these methods simultaneously. The objective of this study is to find a reliable way of assessing grassland quality through measuring forage chemistry with reflectance. We studied a mixed grass ecosystem in Grasslands National Park of Canada and surrounding pastures, located in southern Saskatchewan. Spectral reflectance was collected at both in-situ field level and in the laboratory. Vegetation samples were collected at each site, sorted into the green grass portion, and then sent to a chemical company for measuring forage quality variables, including protein, lignin, ash, moisture at 135 ºC, Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF), Total Digestible, Digestible Energy, Net Energy for Lactation, Net Energy for Maintenance, and Net Energy for Gain. Reflectance data were processed with the first derivative transformation and continuum removal method. Correlation analysis was conducted on spectral and forage quality variables. A regression model was further built to investigate the possibility of using canopy spectral measurements to predict the grassland quality. Results indicated that field level prediction of protein of mixed grass species was possible (r2 = 0.63). However, the relationship between canopy reflectance and the other forage quality variables was not strong. Full article
(This article belongs to the Special Issue Advances in Environmental Sensor Networks)
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