GI for Disaster Management
Each year, disasters such as storms, floods, fires, volcanoes, earthquakes, and epidemics cause thousands of casualties and tremendous damage to property around the world, displacing tens of thousands of people from their homes and destroying their livelihoods. The majority of these casualties and p...
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| Year of Publication: | 2020 |
| Language: | English |
| Physical Description: | 1 electronic resource (160 p.) |
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| 245 | 1 | 0 | |a GI for Disaster Management |
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| 520 | |a Each year, disasters such as storms, floods, fires, volcanoes, earthquakes, and epidemics cause thousands of casualties and tremendous damage to property around the world, displacing tens of thousands of people from their homes and destroying their livelihoods. The majority of these casualties and property loss could be prevented if better information were available regarding the onset and course of such disasters. Several remote sensing technologies, such as meteorological and Earth observation satellites, communication satellites, and satellite-based positioning, supported by geoinformation technologies, offer the potential to contribute to improved prediction and monitoring of potential hazards, risk mitigation, and disaster management which, in turn, would lead to sharp reductions in losses to life and property. This book explores most of the scientific issues related to spatially supported disaster management and its integration with geographical information system technologies in different disaster examples and scales. Dealing with disasters over space and time represents a long-lasting theme, now approached by means of innovative techniques and modelling approaches. Several priorities for actions are outlined toward preventing new and reduce existing disaster risks, including understanding disaster risk, strengthening disaster risk governance for management of disaster risk, investing in disaster reduction for resilience, and enhancing disaster preparedness for effective response. This book presents ideas to address the challenges facing different components of spatial patterns related to ecological processes, and the published articles extended versions of selected presentations from the Gi4DM Conference in 2019 in Prague. | ||
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| 653 | |a first responder | ||
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| 653 | |a landslide | ||
| 653 | |a flood | ||
| 653 | |a logistic regression | ||
| 653 | |a Mamdani fuzzy algorithm | ||
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| 653 | |a tide gauge | ||
| 653 | |a satellite altimetry | ||
| 653 | |a GNSS | ||
| 653 | |a post-fire management | ||
| 653 | |a forest regeneration | ||
| 653 | |a fire severity mapping | ||
| 653 | |a multispectral imagery | ||
| 653 | |a Sentinel-2A | ||
| 653 | |a unmanned aerial vehicles | ||
| 653 | |a Parrot SEQUOIA | ||
| 653 | |a climate change | ||
| 653 | |a fuzzy logic | ||
| 653 | |a GIS, household | ||
| 653 | |a Index method | ||
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