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Part 1: Document Description
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Citation |
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Title: |
Co-exposure patterns of heat, wildfire, and wildfire smoke in Western US |
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Identification Number: |
doi:10.7910/DVN/9VDUAP |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-05-08 |
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Version: |
2 |
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Bibliographic Citation: |
Hu, Kate; Trisovic, Ana; Ankita Bakshi, 2024, "Co-exposure patterns of heat, wildfire, and wildfire smoke in Western US", https://doi.org/10.7910/DVN/9VDUAP, Harvard Dataverse, V2 |
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Citation |
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Title: |
Co-exposure patterns of heat, wildfire, and wildfire smoke in Western US |
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Identification Number: |
doi:10.7910/DVN/9VDUAP |
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Authoring Entity: |
Hu, Kate (Harvard University) |
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Trisovic, Ana (Harvard University) |
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Ankita Bakshi (ESRI) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Trisovic, Ana |
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Depositor: |
Trisovic, Ana |
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Date of Deposit: |
2023-08-16 |
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Holdings Information: |
https://doi.org/10.7910/DVN/9VDUAP |
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Study Scope |
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Keywords: |
Earth and Environmental Sciences |
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Abstract: |
We provide data on three heat-related natural hazards: extreme heat, wildfire burn zones, and wildfire smoke from 2006-2020 in eleven Western US states. |
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Country: |
United States |
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Geographic Unit(s): |
Administrative, census tract |
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Geographic Bounding Box: |
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Methodology and Processing |
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Sources Statement |
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Data Sources: |
Weather Data. For daily temperature data from 2005-2021, we use the REACCH METDATA Maximum Air Temperature dataset, derived from the GRIDMET climate dataset referring to the highest daily temperature at a census tract location. Wildfire Data. We use archived Moderate Resolution Imaging Spectroradiometer (MODIS) C6.1 MCD41A1 active fire/hot spot data to capture wildfire occurrence. Wildfire Smoke Data. We use a previously developed wildfire smoke dataset from Childs et al. based on a machine-learning model, using gradient-boosted trees for the architecture. |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a> |
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Other Study Description Materials |
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200_merge_data.ipynb |
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application/x-ipynb+json |
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250_get_metrics.ipynb |
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application/x-ipynb+json |
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301_hotspots.ipynb |
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application/x-ipynb+json |
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301_stats_hotspots.ipynb |
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application/x-ipynb+json |
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301_stats_hotspot_risk.ipynb |
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application/x-ipynb+json |
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302_hotspots_agg_plt_svi.ipynb |
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application/x-ipynb+json |
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303_trends.ipynb |
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application/x-ipynb+json |
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304_state_plots.ipynb |
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Notes: |
application/x-ipynb+json |
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304_top_states_plot.ipynb |
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Notes: |
application/x-ipynb+json |
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305_get_grid_plots.ipynb |
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application/x-ipynb+json |
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305_hotspot_profiling.ipynb |
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application/x-ipynb+json |
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306_ct_profiling.ipynb |
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Notes: |
application/x-ipynb+json |
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307_coastline_profiling-rolling_heat.ipynb |
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application/x-ipynb+json |
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308_text_stats.ipynb |
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Notes: |
application/x-ipynb+json |
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309_pymannkendall.ipynb |
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Notes: |
application/x-ipynb+json |
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310_bivariate_plot.ipynb |
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application/x-ipynb+json |
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320_get_grid_plots.ipynb |
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application/x-ipynb+json |
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401_demographic_pies.ipynb |
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application/x-ipynb+json |
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402_age-hotspot.ipynb |
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application/x-ipynb+json |
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405_tribal_land.ipynb |
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application/x-ipynb+json |
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helper_400.py |
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text/x-python-script |
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plotting.py |
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Notes: |
text/x-python-script |
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README-1.md |
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Notes: |
text/markdown |
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README.md |
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Notes: |
text/markdown |
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requirements.txt |
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Notes: |
text/plain |
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Label: |
wildfireday-temperature-smoke_pm-per_day_per_ct |
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Notes: |
application/octet-stream |