Researchers Submit Patent Application, “Automated Optical-Based System Providing Dynamic Parametric Flood Impact Cover And Method Thereof”, for Approval (USPTO 20240077646): Swiss Reinsurance Company Ltd.

2024 MAR 25 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Washington, D.C., NewsRx journalists report that a patent application by the inventor SUNDERMANN, Lukas (Zurich, CH), filed on August 2, 2023, was made available online on March 7, 2024.

The patent’s assignee is Swiss Reinsurance Company Ltd. (Zurich, Switzerland).

News editors obtained the following quote from the background information supplied by the inventors: “Among the most impacting, damaging, and destructive natural or geophysical disaster of the world, floods are most frequent and uncertain type. Floods endangers rives, properties, infrastructures and damage a lot of livelihoods within a short period of time. FIG. 1 showing the physical impact of floods measured by monetary losses incurred in different countries. Controlling floods are difficult, but minimizing the impact by technical approaches is necessary. It is difficult to identify which measure is the better strategy and policy to deal with the floods. The combination of the human vulnerability and the physical exposures result in flood hazards. These losses and hazards can be minimized by making aware the public beforehand by providing them the reliable and suitable measuring data about flood risks, i.e. about the measurable probability value of having a certain impact strength to an object by an occurring flood event with a certain strength. Reliable prediction by technical forecast systems relying on measuring parameter values, preparedness, prevention, diminishing, and damage assessment are the stages of flood disaster management. Flood inundation maps are an important technical tool for providing the data in an accessible way. They reflect for different flood event types, the topographic forecasted pattern of a particular site, the sum of people and physical objects at risk, population anticipation and coping with the disaster and flood protection works. These are a crucial technical requirement for automated flood risk mitigation and risk-transfer rote pricing, municipal planning, ecological studies and set up of emergency action plans. Advancements in Remote Sensing (RS), technical modelling and forecasting and Geographic Information Systems (GIS) turned out to be important and particularly technically useful in flood inundation mopping. Floods can be predicted and flood risk areas can be identified via modelling with appropriately selected sensory input like hydrologic engineering centers-river analysis system (HEC-RAS) and hydrologic engineering centers-hydrologic modelling system (HEC-HMS) clubbing with GIS and Remote Sensing (RS). For example, for one-dimensional and unsteady-flow simulations of the designed floods. HEC-RAS and GIS can be used. Flood maps be generated for different return periods and these maps can be mapped to provide a comparison with other maps, e.g. using gradient or deviation measurements. This can be required for the technical prediction of floods.

“Not all flood events have the some impact, wherein the impact may vary in strength as well as in type. In urban contexts, for example, flooding can e.g. pose a significant hazard to moving vehicles and causes traffic disruption by placing water flow in the transportation network, resulting in vehicles being swept away, injuries, and the loss of life of passengers. The remote detection of urban flooding over a large area will allow cities to develop flood maps to reduce risk during weather events. Mapping urban flood events is c challenge for three main reasons: the urban environment is highly complex with waterways and drains at submeter resolutions, the flooding will be shallow and ephemeral, and ponding means that the flooding extent will be discontinuous. Hydrologic models that are the conventional approach in flood forecasting struggle with these factors, making the application of these techniques difficult. Attempts have been made in the prior art to map urban flooding and flood risk with traditional prior art methods. However, high resolution hydrologic modelling structures may be effective at small scales (e.g., a few urban blocks) but the computational resources and highly accurate inputs required to properly model urban flooding at the community scale are not widely available with the current technology. These limiting factors exemplify the need to find technically based methods of mapping or predicting flooding that are less computationally intensive. The advantage of remote sensing is flood detection for large scale flood mopping without the need for highly accurate inputs and computationally intense processes to advance flood risk management.

“While extreme flooding, especially that which falls in the 100-year event category, is quite understood, and mapped by a plurality of prior art systems, minor flooding is difficult to map and predict. This less severe flooding, known as nuisance flooding or NF, poses less of a hazard to lives and property, but can still be inconvenient or even dangerous, especially to drivers. Though drier regions such as Southern California may not experience the some extreme, spatially extensive flooding common in other more humid parts. NF remains a problem during the rainy season, especially for aging infrastructure or current systems that are not designed to handle changing climactic patterns. NF is expected to become more of a problem in the future as the climate changes and sea levels rise. Coastal areas such as Southern California are particularly vulnerable to NF. There is a need to develop new reliable techniques to detect catastrophic flooding, also covering urban flooding, which may be also used for nuisance flooding, reducing the risks associated with flooding during heavy rainfall in various context, covering urban and rural environments.

“In the technical field of remote sensing, systems have been developed in flood detection using optical methods such as aerial photographs or satellite imagery, such as SAR and LiDAR (Light Detection and Ranging) systems. SAR, or Synthetic Aperture Radar, is an especially promising technique. As an active sensor, the radar can detect the Earth’s surface no matter what time of day it is or what cloud conditions prevail. Some prior art systems for the detection of flooding with SAR try to combine SAR imagery measurements from COSMO-SkyMed (Agency Spaziale Italiana, Rome, Italy) and Landsat 8 OLI data (Boa Aerospace and technologies, Boulder, CO. USA) to measure map flooding along rivers. Others rely on measured RADARSAT-2 SAR images and flood stage data based on the return period for the 2011 Richelieu River flood in Canada, and even others rely on using TerroSAR-X in tandem with very high-resolution aerial imagery to measure map floodings. Until now. SAR data was considered insufficient for mapping flooding in more complex topographies and zones as urban zones due to the low resolution and shadow and layover in the complex urban environment.

“The technical need for reliable and fast measuring and/or forecasting systems is also reflected by the painfully lacking reliable automated flood impact and impact response or mitigation systems. For many countries, it is hardly possible to do a technically correct flood impact occurrence rating and/or determination based on predictive forward-looking impact measures. A glance at the loss history shows that physical damages and associated losses caused by flood events are equally high or higher than those of other natural catastrophic events as earthquakes, windstorms, or other perils. For many of those other perils various prediction and/or rating and/or early warning systems based on actual measuring parameter values already exist. Large physical part of industrial facilities, industrial power and time are lost by occurring flood events having a physical impact to such objects. Additionally, with the trend of increasing risk-transfer penetration for floods, the insurance and re-insurance industry is affected ever more by flood caused physical damages and losses. To extend the early warning and flood damage rating to detailed and even facultative business, however, the threat of immense data amounts has to be coped with. This is done by completely new simulation approaches simulating allowing to extrapolate actual physical measuring parameters to future, i.e. forward-looking time windows and geographic cells.

“Further, in many countries, a large number of industrial facilities and homes have a significant and measurably predictable probability (risk) for being impacted by flood events, and reasonably should be covered by flood mitigation and risk-transfer processes. However, many prior art systems do not capable to reliable hedge against the peril of flood events, inter alia, due to the prevalence of moral hazard and adverse selection phenomena, for example, in entering risk-transfers for objects most affected by the specific peril of flood. In such cases, traditional risk-transfer is not available. Whereas for other damage risks, risk-transfer systems can be based on the use of the low of large numbers to precisely determine a relatively small premium amount to large numbers of objects in order to cover the occurring damages of the small numbers of impacted objects who have suffered a loss due to the event-based impact to their objects. In flood event covers, typically the numbers of impacted objects is larger than the available number of individuals interested in protecting their property/objects from the peril using risk covers, which means that most prior art insurance systems do not provide risk-transfers to occurring flood events since the probability of operating the system in a sound profit range are regarded as being remote. Additionally, while there are risk-transfer systems that are enabled to provide primary flood risk covers for high value homes, the underwriting and provision of such mitigation processes does not account for many flood risks.”

There is additional background information. Please visit full patent to read further.”

As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventor’s summary information for this patent application: “It is one object of the present invention to provide an automated system and method for reliable forward-looking measurements and ratings of physical impacts of occurring location-dependent catastrophic events, as flood events, to a specific object, and in automated conduct and provision/generation of appropriate covers and/or hedging against the impacted damage to the specific object, it is further an object of this invention to provide a new and better automated system and method for providing a dynamic parametric cover, which does not have the above-mentioned disadvantages of the prior art. In particular, it is an object of the present invention to provide a risk-transfer cover based on an extend of a flooded area. Further it is an object, to generate a pricing measure for a cover based on the chosen limit value (payout cover) and a measured and/or forecasted exposure value (e.g. related to the amount severity and/or extend of flooding to an area). The extent of flooded area is generated by assessing an Area of Interest (AOI) using automated systems such as Synthetic Aperture Radar or Drones and by dividing the area into grid cells. The AOI can e.g. be defined client- or user-specific. Ideally the grid cells cover the entire AOI. Later, with using technology such as SAR, it can e.g. be determined how much of the AOI is flooded (in percent area or number of grid cells).

“The spacing between the messed network points, and thus the size of the grid cells can e.g. be predefined and can be different for different risk-transfer structures and user to be covered. The grid size can, thus, be predefined or automatically negotiated between a user and the inventive system, or it can by automatically and/or dynamically adjusted by the system based on a desired resolution within a selected area. The resolution can also be varied by the system e.g. in dependence to the severity of the impact in a certain area. e.g. the severity of flooding. The resolution can also be increased automatically and/or dynamically at the border of the affected area to achieve a more precise quantitative measure for the actual affected or impacted area.

“In particular, these aims are achieved by the invention in which by means of an optical-based measuring and/or forecasting system and method for measuring a quantitative flooding extent measure value and/or a flooding impact extent measure value for physical objects located within a topographic and/or geographic area impacted by an occurrence of a flood event, comprising (i) measuring by means of satellite-based and/or airplane-based aerial remote sensing devices of the optical-based measuring and/or forecasting system, optical imaging sensory data and transmitting said optical imaging sensory data via a data transmission link to a central ground station. (ii) capturing a geographic and/or topographic area to be covered by a predefined data structure of a flood map generator, the data structure at least comprising definable area parameters capturing geographic location and/or geographic extent of said geographic and/or topographic area, and generating a flood map by the flood map generator based on the transmitted optical imaging sensory data using the predefined data structure, (iii) generating equally spaced network points over said geographic and/or topographic area providing a meshed network of network points having a definable mesh size and covering the whole geographic and/or topographic area. (iv) aggregating, after an occurrence of a flood event, for an affected area of said geographic and/or topographic area the total number of network points within the affected area, (v) measuring, after the occurrence of the flood event, the affected area of said geographic and/or topographic area based on measuring a flooding at each network point of the meshed network within the affected area based on the flood mop, wherein network points measured as flooded are contributing to the measured affected area while network points measured as not flooded are not contributing to the measured affected area, and (vii) measuring the flooding extent measure value and/or flooding impact extent measure value of the affected area based on the network points measured as flooded to the total number of network points of the affected area.

“In an embodiment variant, the method further comprises (i) providing a dynamic parametric flood impact cover for an object physically impacted by the occurrence of the flood event by using an adoptive risk-transfer structure based on the flooding extent measure value and/or the flooding impact extent measure value, (ii) generating the parametric coverage covering a possible loss associated with the occurrence of the flood event and impacting the geographic area measured by the affected area, as per the adjustable risk-transfer structure a threshold measure and is triggered by a threshold-trigger, wherein the threshold-trigger is selected from a percentage of the affected area given by the measured affected area to the geographic area; and (iii) transferring, by an electronic payment transfer module, based on the generated parametric coverage monetary pay-out parameter values by electronic payment transfer to the individual.

“The network points can e.g. be measured as flooded when each network point of a specified area is flooded. The network points can e.g. be regularly spaced within the mesh network with a pre-definable spacing. The network points can further e.g. be essentially 0.005 x 0.005 deg mesh network points. Flood determination per grid cell can e.g. be binary at the centroid. However, it can also be determined dependent on the flood depth, i.e. more refined.

“In another embodiment of the invention, the mesh network points are measured as flooded when each network point of the measured affected area is flooded. The network points can be defined as corner points of two dimensional m x n blocks. The m x n blocks are of approx. 8.7210-5 radian. The network points measured as flooded can e.g. be determined using at least a neural network approach, and the affected area is measured using on-air imaging devices.

“The grid cells measured as flooded can e.g. be determined using an artificial intelligence-based or machine-learning based engine, such as a neural network data processing structure, and the affected area can e.g. be measured using on-air imaging devices. The variant with the proposed grid-cell-based floodplain mapping is an inventive remote sensing intensive process that can e.g. be implemented all over the defined area. It can e.g. comprise a Digital Elevation Modelling (DEM) structure, with the predefined or adaptive measuring accuracy based on the selected grid size. The DEM structures allow the inventive system to derive the slope and terrain characteristics of the selected area. Is there a river, and if so is there a flat expanse of plain around that river? What might be below sea level that is near the mouth of a delta? To get the highest accuracy possible for these DEMs, the inventive system can e.g. use remote sensing. In particular measuring devices for aerial or space-based photography and/or LIDAR devices and Synthetic Aperture Radar (SAR) devices to produce the required high-accuracy DEMs. Aerial imagery can be used with multiple images to generate a DEM being captured using e.g. a plane or UAS. However, the quality of aerial imagery can e.g. be affected by lighting conditions and clouds. LiDAR, which shoots pulses of light and records their response, is an active system. That means it is less affected by lighting conditions, but can measure through fight haze and clouds. Also SAR is able to measure through clouds at any time day or night, but is one of the most complicated remote sensing systems to be integrated. With the inventive DEMs, which can also be improved by other imagery sources such as satellite, or UAS imagery, features of importance can be monitored and/or detected in relation to how they relate to possible floodplains. Using remote sensing, the present system allows to classify land cover into many different areas of interest, such as low-lying plains, forests, sandy deltas, and urban areas, and then use those classifications to feed into the floodplain modeling structure. With LiDAR, the system can e.g. also automatically identify buildings and detect where they lie within the possible floodplains. i.e. assign floodplain-related measuring parameter values. These multiple inputs create a map thot shows areas where flooding is measured with a higher probability value. The automated mapping can also be used for predictive modelling, cover or flood impact mitigation, and flood preparation or automated alarm signaling for activation of automated alarm systems.

“As an embodiment variant, the system is automated to electronically disperse payments or transfer monetary porometer values to achieve the desired automatic cover covering the physical damage or impact caused by the natural event, e.g. the flooding event. The payments are dispersed via an electronic payment transfer module based on the generated parametric coverage monetary pay-out parameter. In particular, it is an object of the present invention to provide an automated method and system for providing dynamic parametric cover to an individual in case of an occurrence of a flood event by using an adaptive risk-transfer structure based on physical flood event measurements.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“1. An optical-based measuring and/or forecasting method, implemented by optical-based measuring and forecasting system, for measuring a quantitative flooding extent and/or a flooding impact measure for physical objects located within a topographic and/or geographic area impacted by an occurrence of a flood event, comprising: measuring by satellite-based and/or airplane-based aerial remote sensing devices of the optical-based measuring and forecasting system, optical imaging sensory data and transmitting said optical imaging sensory data via a data transmission link to a central ground station, capturing a geographic and/or topographic area to be covered by a predefined data structure of a flood map generator, the data structure at least comprising definable area parameters capturing geographic location and/or geographic extent of said geographic and/or topographic area, and generating a flood map by the flood map generator based on the transmitted optical imaging sensory data using the predefined data structure, generating equally spaced network points over said geographic and/or topographic area providing a meshed network of network points having a definable mesh size and covering the whole geographic and/or topographic area, wherein a gird of grid cells over geographic and/or topographic area is defined by the meshed network each grid cell having a network point as a centroid and wherein the geographic and/or topographic area is completely covered by the grid cells of the grid aggregating, after a measured occurrence of a flood event, for an affected area of said geographic and/or topographic area the total number of network points within the affected area. measuring, otter the occurrence of the flood event, the affected area of said geographic and/or topographic area based on measuring a flooding at each network point of the meshed network within the affected area based on the flood map, wherein network points measured as flooded are contributing to the measured affected area while network points measured as not flooded are contributing to the area measured as not affected, and measuring the flooding extent value and/or flooding impact measure value of the affected area based on the network points measured as flooded to the total number of network points of the geographic and/or topographic area.

“2. An automated method according to the optical-based measuring and forecasting method of claim 1, further comprising: providing a dynamic parametric flood impact cover for a physical object physically impacted by the occurrence of the flood event by using an adaptive damage-cover structure based on the measured flooding extent value and/or the flooding impact measure value, generating the parametric coverage covering a possible loss associated with the occurrence of the flood event impacting the geographic area measured by the affected area, as per the adjustable damage-cover structure a flood threshold measure is triggered by on electronic threshold-trigger, wherein the threshold-trigger is selected from a measured percentage value given by the measured affected area to the geographic area or the measured affected network points to the total number of network points; and transferring, by an electronic payment transfer module, based on the generated parametric coverage monetary pay-out parameter values by electronic payment transfer to an impacted physical object and/or a risk-exposed individual associated with an impacted physical object.

“3. The method according to claim 1, wherein network points are measured as flooded when each network point of a defined area is flooded.

“4. The method according to claim 1, wherein the network points are regularly spaced within the mesh network with a pre-definable spacing.

“5. The method according to claim 4, wherein the network points are essentially 0.005 x 0.005 deg mesh network points.

“6. The method according to claim 4, wherein the network points represent the corner points of two dimensional m x n blocks.

“7. The method according to claim 6, wherein the dimensional m x n blocks are of approx. 8.72*10-5 radian.

“8. The method according to claim 1, wherein the geographic and/or topographic area comprising unvarying landscape representative of area covered by dry land and wetland.

“9. The method according to claim 1, wherein the occurrence of the flood event is detected using loopback signaling.

“10. The method according to claim 1, wherein the mesh network points measured as flooded are determined using at least a machine-learning approach.

“11. The method according to claim 1, wherein the affected area is measured using on-air imaging devices.

“12. The method according to claim 1, wherein a step of generating a premium value based on the payout coverage associated with a measurement.

“13. An optical-based measuring and forecasting system for providing a dynamic parametric cover in case of a measured occurrence of a flood event by using an adoptive damage cover structure based on physical flood event measurements, comprising a predefined data structure to capture a geographic and/or topographic area to be covered, the data structure at least comprising definable area parameters capturing geographic location and/or geographic extent of said geographic area, comprising: satellite-based and/or airplane-based aerial remote sensing devices for measuring optical imaging sensory data and transmitting said optical imaging sensory data via a data transmission link and network to a central ground station, wherein the central ground station comprises a flood map generator for capturing a geographic and/or topographic area by means of a measured flood map and for generating the flood map by the flood map generator based on the transmitted optical imaging sensory data using the predefined data structure, a meshed network structure of network points generated with equally spaced network points over said geographic and/or topographic area having a definable mesh size and covering the whole geographic and/or topographic area, and measuring engine for aggregating, after an occurrence of a flood event, within an affected area of said geographic and/or topographic area the total number of network points, and for measuring, after the occurrence of the flood event, the affected area of said geographic and/or topographic area based on measuring a flooding of each network point of the meshed network within the affected area based on the flood map, wherein network points measured as flooded are contributing to the measured affected area while network points measured as not flooded are contributing to the area measured as not affected, and for measuring the flooding extent value and/or flooding impact measure value of the affected area based on the network points measured as flooded to the total number of network points of the affected area.

“14. An optical-based measuring and forecasting system according to claim 13, wherein a parametric coverage is generated covering a loss associated with the occurrence of the flood event and impacting the geographic area measured by the affected area, as per the adjustable damage-cover structure a threshold measure is triggered by a threshold-trigger, wherein the threshold-trigger is selected from a percentage of the affected area to the geographic area, and wherein by an electronic payment transfer module, based on the generated parametric coverage, monetary pay-out parameter values are transferred by electronic payment transfer to the flood-exposed physical object and/or an individual associated with the flood-exposed physical object.”

For additional information on this patent application, see: SUNDERMANN, Lukas. Automated Optical-Based System Providing Dynamic Parametric Flood Impact Cover And Method Thereof. U.S. Patent Application Number 20240077646, filed August 2, 2023 and posted March 7, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20240077646)&db=US-PGPUB&type=ids

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