Machine Learning Solution for Predicting Flood Damage
Read how we used innovative data techniques to help a government agency reduce inspection costs and improve its structural damage/risk mitigation assessment processes to expedite recovery activities.
Prioritize inspection resources and leverage results from other inspection processes
Develop transparent methodology and decision criteria for determining flood estimates
Develop a less intrusive experience for communities recovering from a flooding disaster; protect sensitive information
Advance the use of technology-driven solutions to expedite damage assessment process
During the last few years, the United States (U.S.) has experienced unprecedented rainfall and flash flooding in a number of metropolitan areas, which has resulted in some of the costliest natural disasters in U.S. history. Government agencies have sought to apply data-driven solutions to aid in relief efforts to assess the damage resulting from storms and other natural hazards.
Special flood hazard areas are those areas that have been determined by federal agencies to have
- Limited appraisal or construction backgrounds
- Developing reasonable estimates of structure values and structure-specific damages in accordance with NFIP requirements in a timely manner
Understanding that efficiency, speed
- Lower cost for conducting flood damage inspections and estimates
- A less intrusive experience for communities recovering from
- Faster completion time to expedite contingent recovery activities
- Meet various stakeholder requirements
- Develop an accurate process which can be followed in different locations to support timely damage estimate determinations