公开(公告)号：US20240411016A1

公开(公告)日：2024-12-12

申请号：US18715646

申请日：2022-12-01

Applicant: Luxembourg Institute of Science and Technology

Inventor： Jie ZHAO ,  Yu LI ,  Marco CHINI

IPC: G01S13/95 ,  G01S13/90

Abstract: This method comprises: pre-processing (312) SAR data of the geographical region to determine a plurality of SAR images (2), said region being subdivided into a plurality of adjacent cells; defining (314) an urban mask (4) of said region, said urban mask providing, for each cell, a likelihood that said cell is an urban area; applying (316), on the plurality of SAR images, a deep learning classification algorithm, to compute, for each cell of said region, a class (6) indicative that the corresponding cell is either a flooded urban area, a flooded rural area, or a non-flooded area, the deep learning classification algorithm being structured as a fully convolutional neural network (16) and comprising dynamic parameters and static parameters, the values of the dynamic parameters being computed from the urban mask and the value of the static parameter being computed during a training stage.