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2026
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| Online Access: | https://doi.org/10.5281/zenodo.20378184 |
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| author | Hasan, Md Rakib Arafat Rahman Shoumik Zubyer Mst Anika Khatun Rupa Fazla Zawadul Arabi Yeasmin Nahar Jolly |
| author_facet | Hasan, Md Rakib Arafat Rahman Shoumik Zubyer Mst Anika Khatun Rupa Fazla Zawadul Arabi Yeasmin Nahar Jolly |
| contents | <p>This archive is the data companion to the analysis code at https://github.com/rakibhhridoy/five-rivers-heavy-metals, supporting the manuscript "Geochemistry Source Attribution and Satellite-Prediction Boundaries for Heavy Metals in Dhaka's Five Rivers" (Hasan, Rahman, Zubyer, Rupa, Arabi, and Jolly).</p> <blockquote> <p> </p> <p><span class="Apple-converted-space"> </span>Contents:</p> <p><span class="Apple-converted-space"> </span><em>- data/ — the curated tabular dataset used by the analysis pipeline: primary</em></p> <p><em><span class="Apple-converted-space"> </span>17-station sediment and water chemistry, real Google AlphaEarth V1 satellite</em></p> <p><em><span class="Apple-converted-space"> </span>embeddings, hydrological-proximity features, ERA5/CHIRPS climate covariates, and</em></p> <p><em><span class="Apple-converted-space"> </span>the harmonized 111-row secondary literature dataset with its audit trail.</em></p> <p> </p> <p><em><span class="Apple-converted-space"> </span>- gis/ — the full geospatial tree (~3.4 GB uncompressed): computed spectral-index</em></p> <p><em><span class="Apple-converted-space"> </span>rasters (NDVI, EVI, SAVI, NDWI, MNDWI, AWEI, NDBI, UI, BUI, NDSI, LST), per-year</em></p> <p><em><span class="Apple-converted-space"> </span>land-use/land-cover rasters (2017-2025) for change detection, the SRTM digital</em></p> <p><em><span class="Apple-converted-space"> </span>elevation model used for D8 flow routing, brick-kiln/industrial/sampling point</em></p> <p><em><span class="Apple-converted-space"> </span>shapefiles, inverse-distance-weighting interpolation rasters, and the</em></p> <p><em><span class="Apple-converted-space"> </span>deep-learning model-search notebooks and trained model weights.</em></p> </blockquote> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20378184 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Geochemistry Source Attribution and Satellite-Prediction Boundaries for Heavy Metals in Dhaka's Five Rivers Hasan, Md Rakib Arafat Rahman Shoumik Zubyer Mst Anika Khatun Rupa Fazla Zawadul Arabi Yeasmin Nahar Jolly <p>This archive is the data companion to the analysis code at https://github.com/rakibhhridoy/five-rivers-heavy-metals, supporting the manuscript "Geochemistry Source Attribution and Satellite-Prediction Boundaries for Heavy Metals in Dhaka's Five Rivers" (Hasan, Rahman, Zubyer, Rupa, Arabi, and Jolly).</p> <blockquote> <p> </p> <p><span class="Apple-converted-space"> </span>Contents:</p> <p><span class="Apple-converted-space"> </span><em>- data/ — the curated tabular dataset used by the analysis pipeline: primary</em></p> <p><em><span class="Apple-converted-space"> </span>17-station sediment and water chemistry, real Google AlphaEarth V1 satellite</em></p> <p><em><span class="Apple-converted-space"> </span>embeddings, hydrological-proximity features, ERA5/CHIRPS climate covariates, and</em></p> <p><em><span class="Apple-converted-space"> </span>the harmonized 111-row secondary literature dataset with its audit trail.</em></p> <p> </p> <p><em><span class="Apple-converted-space"> </span>- gis/ — the full geospatial tree (~3.4 GB uncompressed): computed spectral-index</em></p> <p><em><span class="Apple-converted-space"> </span>rasters (NDVI, EVI, SAVI, NDWI, MNDWI, AWEI, NDBI, UI, BUI, NDSI, LST), per-year</em></p> <p><em><span class="Apple-converted-space"> </span>land-use/land-cover rasters (2017-2025) for change detection, the SRTM digital</em></p> <p><em><span class="Apple-converted-space"> </span>elevation model used for D8 flow routing, brick-kiln/industrial/sampling point</em></p> <p><em><span class="Apple-converted-space"> </span>shapefiles, inverse-distance-weighting interpolation rasters, and the</em></p> <p><em><span class="Apple-converted-space"> </span>deep-learning model-search notebooks and trained model weights.</em></p> </blockquote> |
| title | Geochemistry Source Attribution and Satellite-Prediction Boundaries for Heavy Metals in Dhaka's Five Rivers |
| url | https://doi.org/10.5281/zenodo.20378184 |