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Showing 1 to 7 of 7 for “"flood mapping"”.

  1. Real-time flood mapping for disaster management decision support in Chennai

    … is prone to unpredictable rainfall and heavy flooding events during northeast monsoon season between October and December. The floods during December 2015 were one of the costliest natural disasters the city (T. E. Narasimhan, 2015) had witnessed and it exposed the critical need for providing …

    mit Repository record for Real-time flood mapping for disaster management decision support in Chennai (opens in a new tab)

  2. Riverine flooding using GIS and remote sensing

    Floods are caused by extreme meteorological and hydrological changes that are influenced directly or indirectly by human activities within the environment. The flood trends show that floods will reoccur and shall continue to affect the livelihoods, property, agriculture and the surrounding …

    cape-town Repository record for Riverine flooding using GIS and remote sensing (opens in a new tab)

  3. Validating the Quality of Crowdsourced Data for Flood Modeling of Hurricane Harvey in Houston, Texas

    Flood is one of the most widespread natural hazards in the world. Hurricane Harvey, a 1000-year flood event, hit Texas in 2017 and resulted in significant property damage, bodily injury, and casualty. As one of the most impacted areas, Houston is chosen to be the study area of this study. For …

    texas-state Repository record for Validating the Quality of Crowdsourced Data for Flood Modeling of Hurricane Harvey in Houston, Texas (opens in a new tab)

  4. Investigating Compound Flood Using Remote Sensing And Hydrodynamic Modeling

    <p>Flooding is a frequent and destructive natural disaster that poses serious risks to infrastructure and socio-environmental systems. It involves multiple processes (e.g., coastal, pluvial, and fluvial) that can combine to cause more devastation than any process alone, called compound flooding …

    usm Repository record for Investigating Compound Flood Using Remote Sensing And Hydrodynamic Modeling (opens in a new tab)

  5. Big Remote Sensing Data and Machine Learning for Assessing 21st Century Flooding and Socioeconomic Exposures

    … events and climate extremes such as flooding, rising sea levels due to climate change, solid earth changes, and other anthropogenic activities. With the increasing population in the era of changing climate, the number of people suffering from exposure to extreme events and sea level …

    vt Repository record for Big Remote Sensing Data and Machine Learning for Assessing 21st Century Flooding and Socioeconomic Exposures (opens in a new tab)

  6. Hexagonal Discrete Global Grid Systems in Topographical and Hydrological Modeling

    … into the DGGS and used to predict future flood risks under multiple climate change scenarios. This dissertation promotes the adoption of DGGS in real-world decision-making, particularly in topographical and hydrological modeling. The proposed methodology for heterogenous data integration …

    calgary Repository record for Hexagonal Discrete Global Grid Systems in Topographical and Hydrological Modeling (opens in a new tab)

  7. Mapping under uncertainity : spatial politics, urban development, and the future of coastal flood risk

    Flooding is the most common and single largest source of disaster-caused property damage in the United States. The past year, 2017, was the costliest for weather and climate disasters in US history. To mitigate these losses, the Federal Emergency Management Agency and National Flood Insurance …

    mit Repository record for Mapping under uncertainity : spatial politics, urban development, and the future of coastal flood risk (opens in a new tab)