SensorScope is a turnkey solution for environmental monitoring systems, based on a wireless sensor network and resulting from a collaboration between environmental and network researchers. Given the interest in climate change, environmental monitoring is a domain where sensor networks will have great impact by providing high resolution spatio-temporal data for long periods of time. SensorScope is such a system, which has already been successfully deployed multiple times in various environments (e.g., mountainous, urban). Here, we describe the overall hardware and software architectures and especially focus on the sensor network itself. We also describe one of our most prominent deployments, on top of a rock glacier in Switzerland, which resulted in the description of a micro-climate phenomenon leading to cold air release from a rock-covered glacier in a region of high alpine risks. Another focus of this paper is the description of what happened behind the scenes to turn SensorScope from a laboratory experiment into successful outdoor deployments in harsh environments. Illustrated by various examples, we point out many lessons learned while working on the project. We indicate the importance of simple code, well suited to the application, as well as the value of close interaction with end-users in planning and running the network and finally exploiting the data.

A sensor network data gathering and visualization infrastructure is demonstrated, comprising of global sensor networks (GSN) middleware and Microsoft SensorMap. Users are invited to actively participate in the process of monitoring real-world deployments and can inspect measured data in the form of contour plots overlayed onto a high resolution map and a digital topographic model. Users can go back in time virtually to search for interesting events or simply to visualize the temporal dependencies of the data. The system presented is not only interesting and visually enticing for non-expert users but brings substantial benefits to environmental scientists. The easily installed data acquisition component as well as the powerful data sharing and visualization platform opens up new ground in collaborative data gathering and interpretation in the spirit of Web 2.0 applications.

Environmental monitoring constitutes an important field of application for wireless sensor networks. Given the severity of potential climate changes, environmental impact on cities, and pollution, it is a domain where sensor networks can have great impact and as such, is getting more and more attention. Current data collection techniques are indeed rather limited and make use of very expensive sensing stations, leading to a lack of appropriate observations. In this paper, we present SensorScope, a collaborative project between environmental and network researchers, that aims at providing an efficient and inexpensive out-of-the-box environmental monitoring system, based on a wireless sensor network. We especially focus on data gathering and present the hardware and network architecture of SensorScope. We also describe a real-world deployment, which took place on a rock glacier in Switzerland, as well as the results we obtained.

Experiments were conducted using truck-based microwave radiometers operating at 1.41- (L-band) and 2.65-GHz (S-band) horizontal polarization to observe small plots during and following sprinkler irrigation. These experiments were conducted on a sandy loam soil in 1993 and a silt loam in 1995. Sandy loam soils typically have higher infiltration capabilities than clays, and in the authors' studies, they were not able to exceed this with the irrigation system. The observed brightness temperature (T/sub B/) quickly reached a nominally constant value during irrigation. When the irrigation was stopped, the T/sub B/ began to increase as drainage took place. Contributing depth-related differences were observed for L- and S-band as expected. The irrigation rates in 1995 with the silt loam soil exceeded the saturated conductivity of the soil. During irrigation, the T/sub B/ values exhibited a phenomenon that had not been previously observed and identified and is associated with coherent interference. The Land S-band exhibited similar patterns but were not identical due to contributing depth. These results suggested the existence of a sharp dielectric boundary (wet over dry soil) that was increasing in depth with time. The temporal description of the wetting front boundary was used with a coherent radiative transfer model to predict T/sub B/ for L- and S-band.

A scanning water Raman-lidar, designed and constructed to study surface-atmosphere processes with high spatial and temporal resolution is described. It is shown that the lidar is able to measure the absolute water content and then calculate evaporative fluxes and other atmospheric parameters quickly over relatively large areas. This capability provides new opportunities for the study of microscale atmospheric processes. Examples of data and analyses are presented. An analysis is presented which determines the spatial and temporal resolution which is required of a remote sensor in the boundary layer.>