Abstract: An example method for processing wind field data includes generating wind field base data using the preliminary data and one or more empirical equations based on climatology. The wind field base data includes multiple data sets each associated with a different time-point in a first set of time-points. The method also includes performing spatial interpolation and temporal interpolation over the wind field base data to generate a sequence of two-dimensional wind field representations each associated with a different time-point in a second set of time-points, and visualizing the sequence of two-dimensional wind field representations.

Abstract: Systems and methods for determining elevation based on structural modeling and light detection and ranging (LIDAR) data are disclosure. LIDAR bare earth data corresponding to an area within a parcel boundary is obtained as preliminary elevation data. A basis of structure boundary is determined for a structure within the parcel boundary based on an absence of the LIDAR bare earth data within a region in the area. Three-dimensional models are generated based on photographic data, to represent portions of the structure that affect LIDAR signals. A structure boundary for the structure is determined based on the basis of structure boundary in combination with supplemental elevation data generated using the three-dimensional models. Adjacent grade values are determined based on a portion of the preliminary elevation data and supplemental elevation data corresponding to an area between the structure boundary and a buffer boundary.

Abstract: An example method for processing wind field data includes generating wind field base data using the preliminary data and one or more empirical equations based on climatology. The wind field base data includes multiple data sets each associated with a different time-point in a first set of time-points. The method also includes performing spatial interpolation and temporal interpolation over the wind field base data to generate a sequence of two-dimensional wind field representations each associated with a different time-point in a second set of time-points, and visualizing the sequence of two-dimensional wind field representations.

Abstract: Systems and methods for determining elevation based on structural modeling and light detection and ranging (LIDAR) data are disclosure. LIDAR bare earth data corresponding to an area within a parcel boundary is obtained as preliminary elevation data. A basis of structure boundary is determined for a structure within the parcel boundary based on an absence of the LIDAR bare earth data within a region in the area. Three-dimensional models are generated based on photographic data, to represent portions of the structure that affect LIDAR signals. A structure boundary for the structure is determined based on the basis of structure boundary in combination with supplemental elevation data generated using the three-dimensional models. Adjacent grade values are determined based on a portion of the preliminary elevation data and supplemental elevation data corresponding to an area between the structure boundary and a buffer boundary.

Abstract: Methods, systems, and apparatuses that may be utilized for the production of automation assisted elevation certificates are provided. One such method includes receiving, by an elevation certificate application, a plurality of elevation data points. Each of the elevation data points indicates an elevation at a particular location within an area defined between a structure boundary of a structure on a parcel of real property and a buffer boundary that surrounds the structure boundary. A first set of the elevation data points are determined that correspond to a first determined number of the plurality of elevation data points indicating highest elevations. A second set of the elevation data points are determined that correspond to a second determined number of the plurality of elevation data points indicating lowest elevations. A map of a region including the structure is displayed on a user computer device, and the first set and the second set of elevation data points are displayed on the map.

Abstract: Estimating storm damage on a large scale includes collecting geospatial data from a plurality of sensors disparately situated in a defined geographic area; collecting the geospatial data occurs before and during a determined or simulated significant weather event. Geospatial property attribute information for each of a plurality of real property structures within the defined geographic area is also provided. A supercomputer estimates a magnitude and duration of significant weather event forces at points associated with each of the plurality of real property structures according to a significant weather event model in order to produce at least one model output data set. The model output data set is applied to the geospatial property attribute information and, based on the application of model output data, damage to the plurality of real property structures is automatically estimated.