International Journal of Applied Earth Observation and Geoinformation
ReviewEnvironmental sensor networks for vegetation, animal and soil sciences
Introduction
Recent advances in information and communication technologies (ICT) and the development of Environmental sensor networks (ESNs) provide new opportunities for using sensors to monitor environmental change. ESNs can be used to help improve our understanding of environmental phenomena and guide natural resource management (NRM) (e.g. evaluating the effect of climate change and grazing impacts on tree regeneration through a number of seasons; tracking weed incursions; monitoring grazing impacts on native groundcover; and tracking cattle). Environmental sensor networks typically refer to sensing that occurs in close proximity to the target, as opposed to remote sensors that sense at large distances from the target. Sensors in the environmental sciences include, for example, digital cameras, visible to near-infrared spectrometers, soil water sensors, GPS-enabled movement tracking devices and bioacoustic sensors. Sensors can be advantageous in environmental applications because they can be: (i) used to acquire time-series data (Hart and Martinez, 2006), (ii) deployed in locations that are difficult to access and therefore they can overcome practical limitations of traditional monitoring, and (iii) are more time- and cost-effective than traditional field methods. For instance, soil moisture probes provide levels of precision, accuracy and repeatability not traditionally achievable using manual techniques.
Research into ESNs has traditionally focused on the software and hardware engineering components of sensor networks. This has included hardware design (Klingbeil and Wark, 2008, Rahimi et al., 2005), algorithms for distributed computation in sensor networks (Ferentinos and Tsiligiridis, 2007, Worboys and Duckham, 2006), methods for monitoring and positioning nodes (Kohno et al., 1999, Shih et al., 2008), energy efficiency in sensor and network design (Ci et al., 2007) and more recently integrating and hosting sensor data via the internet (Liang et al., 2005). Where there is intent to discuss environmental applications, there remains a focus on engineering challenges (Hart and Martinez, 2006, Pon et al., 2005, Szewczyk et al., 2004). The focus on engineering is not surprising given that sensors and sensor networks are enabling technologies that must be developed before applied NRM-focused sensor studies can commence. Recent technical advancements including hardware miniaturisation, improvements in the efficiency of solar technology, the widespread availability of wireless communication networks such as 3G networks, and improvements and decreases in the cost of sensors, means that novel deployments of ESNs are now possible. Thus, it is imperative that the focus shifts towards understanding the specific environmental domains where research and management will most benefit from using ESNs.
This review moves away from the traditional focus on ICT elements and focuses on applications for proximal monitoring of terrestrial environmental change. We specifically limit our treatment of sensor engineering, wireless network design, algorithms for sensor management and supporting technologies such as database tools for the real-time delivery of sensor data through the Internet. Owing to the breadth of possible applications, we have restricted this review to the following terrestrial applications in which we believe new technologies will be most useful: (a) vegetation monitoring (including crops and pastures), (b) animal movement and diversity assessment, and (c) soil sensing. Climate, aquatic and hydrologic applications are so extensive that they are considered beyond the scope of this review. As this review focuses on proximal sensors, remote sensing technologies such as multispectral or hyperspectral images from satellite- and airborne-sensors are not included. However, where proximal sensors are used to calibrate and validate remote sensors, such as through the use of ground-based hand-held spectrometers, these are discussed, within the context of terrestrial vegetation monitoring applications.
Within each of these application domains, we review the technologies that have been or could be used, and comment on how and why environmental sensing in particular could help address particular research questions or management issues. We also briefly examine technological limitations. We conclude with a synthesis which explores future directions and research needs for applying sensors in environmental monitoring.
Section snippets
Monitoring natural terrestrial vegetation using sensors
The use of ESNs in vegetation studies is dominated by: (i) array-based measurements from digital photography covering small areas of <5 m, and typically focused on assessing characteristics of vegetation in rangelands and grasslands at medium scales (e.g. trees, groundcover using digital photography) (Bennett et al., 2000, Booth et al., 2004, Booth and Cox, 2008), and (ii) point-based measurements using spectral or other sensors for assessing vegetation characteristics such as yield or biomass.
Animal movement for environmental monitoring
Natural biotic resources are mostly managed within multi-use landscapes (i.e. natural areas interspersed with more intensive human uses, including agricultural and urban areas). Both wild and domesticated animals inhabit these landscapes, and landscape structure and variability influence how animals behave and use the resources. Problems can arise when native animals cannot maintain their natural foraging and dispersal movements, leading to population declines, or when native or domesticated
Soil sensing
Concerns over food security, hydrologic processes and global climate change are transforming agriculture and the way in which we use and manage our soils. Consequently, there is a greater need for detailed information about soils including its measurement, modelling and mapping. Conventional soil surveys cannot provide the soil information at appropriate resolutions which are required to support these resource management challenges. The primary reason is well known; when spatial, functional
Future directions and conclusion
This review highlights that the applied operational use of ESNs remains in its infancy and we can expect a rapid advancement in their potential as technical advancements continue. For example, the miniaturisation, improvement in quality and reduction in cost of charge coupled devices (CCDs) can provide a suite of new opportunities for proximal image acquisition for vegetation monitoring applications. In terms of future directions the following are seen as important:
- (i)
A greater focus on validating
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