Processed Spatio-Temporal Flood Prediction Dataset for Jakarta

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1. Verfasser: Ramadhani, Putri Adistia
Format: Recurso digital
Sprache:Englisch
Veröffentlicht: Zenodo 2025
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author Ramadhani, Putri Adistia
author_facet Ramadhani, Putri Adistia
contents <p>This dataset contains processed temporal, spatial, and graph-based features used to train a hybrid CNN–LSTM–GNN framework for flood risk prediction in Jakarta. The data includes 30-day rainfall sequences, 64-dimensional spatial embeddings derived from DEM, slope, land-use, and drainage-density rasters, as well as concatenated graph embeddings representing hydrological connectivity. Only derived features are provided; raw rainfall, DEM, land-use, and OSM drainage shapefiles are excluded due to redistribution restrictions.</p> <p>The dataset is intended for reproducible research in spatio-temporal deep learning and graph-based environmental modeling. All files are provided in NPZ, NPY, or CSV formats and are compatible with standard Python libraries such as NumPy and pandas. The dataset is released under the CC BY 4.0 license.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17781599
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Processed Spatio-Temporal Flood Prediction Dataset for Jakarta
Ramadhani, Putri Adistia
Flood Risk Prediction
Spatio-Temporal Modeling
Deep Learning
CNN–LSTM–GNN
Hydrological Connectivity
Urban Flooding
Jakarta
<p>This dataset contains processed temporal, spatial, and graph-based features used to train a hybrid CNN–LSTM–GNN framework for flood risk prediction in Jakarta. The data includes 30-day rainfall sequences, 64-dimensional spatial embeddings derived from DEM, slope, land-use, and drainage-density rasters, as well as concatenated graph embeddings representing hydrological connectivity. Only derived features are provided; raw rainfall, DEM, land-use, and OSM drainage shapefiles are excluded due to redistribution restrictions.</p> <p>The dataset is intended for reproducible research in spatio-temporal deep learning and graph-based environmental modeling. All files are provided in NPZ, NPY, or CSV formats and are compatible with standard Python libraries such as NumPy and pandas. The dataset is released under the CC BY 4.0 license.</p>
title Processed Spatio-Temporal Flood Prediction Dataset for Jakarta
topic Flood Risk Prediction
Spatio-Temporal Modeling
Deep Learning
CNN–LSTM–GNN
Hydrological Connectivity
Urban Flooding
Jakarta
url https://doi.org/10.5281/zenodo.17781599