Abstract: A system and method designed to assess the future socio-economic impacts of weather events relative to variable climatic conditions is described. The techniques described include a complex data aggregation process pulling data from a heterogeneous set of sources and formats. The aggregation is followed by translating, pruning and pre-processing image data. A neural network is then trained on the pre-processed image data. The trained neural network is then designed to provide an output relative to a prompt, including estimations of economic impacts of peril severity and frequency; estimations on impact of future settlement, and probabilistic layers of future climate events.

Abstract: In at least one aspect, a computer system is provided that includes at least one computer having software stored thereon that when executed causes the at least one computer to perform a method that includes the step or steps of: receiving at least one image that depicts a structure on real property, the structure having a first floor and at least one structural element depicted in the at least one image; dividing the image into a plurality of regions; predicting at least one bounding box for the at least one structural element in the at least one image; predicting that the bounding box contains a structural element of interest; estimating a first floor elevation or height of the structure on the real property based on the structural element of interest; and storing the estimated first floor elevation or height in at least one database.