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Result-based payments (RBPs) reward land users for conservation outcomes and are a promising alternative to standard payments, which are targeted at specific land use measures. A major barrier to the implementation of RBPs, particularly for the conservation of mobile species, is the substantial monitoring cost. Passive acoustic monitoring may offer promising opportunities for low-cost monitoring as an alternative to human observation. We develop a costing framework for comparing human observation and passive acoustic monitoring and apply it to a hypothetical RBP scheme for farmland bird conservation. We consider three different monitoring scenarios: daytime monitoring for the whinchat and the ortolan bunting, nighttime monitoring for the gray partridge and the common quail, and day-and-night monitoring for all four species. We also examine the effect of changes in relevant parameters (such as participating area, travel distance and required monitoring time) on the cost comparison. Our results show that passive acoustic monitoring is still more expensive than human observation for daytime monitoring. In contrast, passive acoustic monitoring has a cost advantage for nighttime as well as day-and-nighttime monitoring in all considered scenarios.
Mobile cyber-physical systems (MCPSs) such as motor vehicles, railed vehicles, aircraft, or spacecraft are commonly used in our life today. These systems are location-independent and embedded in a physical environment which is usually harsh and uncertain. MCPSs are equipped with a wide range of sensors that continuously produce sensor data streams. It is mandatory to process these data streams in an appropriate manner in order to satisfy different monitoring objectives, and it is anticipated that the complexity of MCPSs will continue to increase in the future. For instance, this includes the system description and the amount of data that must be processed. Accordingly, it is necessary to monitor these systems in order to provide reliability and to avoid critical damage. Monitoring is usually a semi-automatic process while human experts are responsible for consequent decisions. Thus, appropriate monitoring approaches are required to both provide a reasonably precise monitoring process and to reduce the complexity of the monitoring process itself.
The contribution of the present thesis is threefold. First, a knowledge discovery cycle (KDC) has been developed, which aims to combine the research areas of knowledge discovery in databases and knowledge discovery from data streams to monitor MCPSs. The KDC is a cyclic process chain comprising an online subcycle and an offline subcycle. Second, a new data stream anomaly detection algorithm has been developed. Since it is necessary to identify a large number of system states automatically during operation, data stream anomaly detection becomes a key task for monitoring MCPSs. Third, the KDC and the anomaly detection algorithm have been prototypically implemented and a case study has been performed in a real world scenario relating to the ISS Colombus module.
This volume summarizes the monitoring activities and results at the ‘Chicken Creek’ catchment for the period 2005 to 2010. The development in all ecosystem compartments is assessed, classified, and compared to more mature systems with regard to functional relevance and succession stage. In a final synopsis, the whole catchment is evaluated with regard to ecosystem development and an outlook is given on the expected trends both in the short and the medium term.
This report introduces the monitoring installations of the artificial catchment 'Chicken Creek' and summarizes results of the measurement in the period 2005-2008, covering various aspects and compartments from meteorology and hydrology, soil and soil solution chemistry, vegetation and soil fauna to limnology and surface patternsfor the period 2005 to 2008. This volume is the beginning of a series with results of the ongoing Chicken Creek monitoring program.