A rapid high-resolution multi-sensory urban flood mapping framework via DEM upscaling

Author:

Tan WeikaiORCID,Qin NannanORCID,Zhang Ying,McGrath HeatherORCID,Fortin MaximORCID,Li JonathanORCID

Funder

Natural Resources Canada

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference78 articles.

1. Generating a highly detailed DSM from a single high-resolution satellite image and an SRTM elevation model;Amirkolaee;Remote Sens. Lett.,2021

2. Terrain super-resolution through aerial imagery and fully convolutional networks;Argudo;Comput. Graph. Forum,2018

3. Sen1Floods11: A georeferenced dataset to train and test deep learning flood algorithms for Sentinel-1;Bonafilia,2020

4. Gridded flood depth estimates from satellite-derived inundations;Bryant;Nat. Hazards Earth Syst. Sci.,2022

5. Flooding in calgary - Flood of 2013;City of Calgary,2021

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1. MHFNet: An Improved HGR Multimodal Network for Informative Correlation Fusion in Remote Sensing Image Classification;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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