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Zerger  Andre  Wealands  Stephen 《Natural Hazards》2004,33(2):191-208
Spatially explicit hydrodynamic flood models can play animportant role in natural hazard risk reduction. A key element of these models that make them suitable for riskreduction is the ability to provide time-series inundation information about the onset, duration and passingof a hazard event. Such information can be critical for landuse planning, for mapping evacuation egress routes,and for locating suitable emergency shelters to name only a few risk treatments. This research contends that abarrier to effective risk reduction is providing disaster managers with access to model results in a structured andflexible framework that allows consequences of different hazard scenarios to be assessed and mapped. Toaddress these limitations, a framework has been developed that links a commercial relational databasemanagement system with a GIS-based decision support system. The framework utilises industry standard dataexchange protocols and results in efficient time-series hazard data management. A case study based in Cairns,in far-north coastal Australia is presented to illustrate how the system has been developed. Results show that theframework reduces data volumes significantly, while making pre-run modelled inundation results rapidly accessibleto disaster managers. Of note is the ability of the framework to present results in terms of risk to buildings,roads and other spatial features in urban regions, and to provide answers to relatively complex risk questions.  相似文献   
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Environmental sensor networks (ESNs) provide new opportunities for improving our understanding of the environment. In contrast to remote sensing technologies where measurements are made from large distances (e.g. satellite imagery, aerial photography, airborne radiometric surveys), ESNs focus on measurements that are made in close proximity to the target environmental phenomenon. Sensors can be used to collect a much larger number of measurements, which are quantitative and repeatable. They can also be deployed in locations that may otherwise be difficult to visit regularly. Sensors that are commonly used in the environmental sciences include ground-based multispectral vegetation sensors, soil moisture sensors, GPS tracking and bioacoustics for tracking movement in wild and domesticated animals. Sensors may also be coupled with wireless networks to more effectively capture, synthesise and transmit data to decision-makers. The climate and weather monitoring domains provide useful examples of how ESNs can provide real-time monitoring of environmental change (e.g. temperature, rainfall, sea-surface temperature) to many users. The objective of this review is to examine state-of-the-art use of ESNs for three environmental monitoring domains: (a) terrestrial vegetation, (b) animal movement and diversity, and (c) soil. Climate and aquatic monitoring sensor applications are so extensive that they are beyond the scope of this review. In each of the three application domains (vegetation, animals and soils) we review the technologies, the attributes that they sense and briefly examine the technical limitations. We conclude with a discussion of future directions.  相似文献   
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