A Study on Local-Scale Flood Risk Assessment in Bangladesh Based on Remote Sensing and Deep Learning

thesis_files_zenodo_SLIM.zipThis archive contains a slim, evidence-based reproducibility package for the thesis workflow. It includes selected small files such as CSV summaries, JSON metadata, cleaned notebooks, DEM-validation and MCDA ranking evidence, Sentinel-1 ROI/event-processing records, deep-learning model-comparison metrics, scene-inference metadata, and parcel/building/owner-level flood-impact summary tables. Large raw datasets, Sentinel-1 SAFE files, GeoTIFF rasters, model checkpoints, ArcGIS geodatabase internals, and temporary processing outputs are intentionally excluded to keep the package suitable for repository upload.

Appendix.zipThis archive contains the organized appendix evidence package used to support the thesis appendices. Files are grouped by appendix topic, including data/output inventory, DEM reference and vertical-datum evidence, MCDA ranking and sensitivity outputs, deep-learning model-comparison evidence, Sentinel-1 ROI and scene-inference evidence, and flood-depth/impact-translation tables. The package is intended as a traceable appendix support archive, not as a complete raw-data backup of the full project.