Browse State-of-the-Art › Flood extent forecasting
Flood extent forecasting
5 papers with code · 1 benchmark · 1 dataset archive 2025-07-28
Flood extent forecasting is the task of predicting a binary 2D flood extent map (water vs no water), given input drivers and forcings. The focus is specifically on the impact and extent modeling, such that e.g. atmosphere state (such as precipitation) may be assumed as inputs, to disentangle the impact modeling from upstream challenges such as weather forecasting. This is complementary to time series forecasting of river streamflow and runoff, as well as post-hoc mapping of floods. For related work, data & benchmarks, see https://arxiv.org/abs/2409.18591.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| Global Flood forecasting (5 rows) | U-TAE | Panoptic Segmentation of Satellite Image Time Series with... | code | Syntology ran 10 of 11 samples · 1 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
5 shown of 5 papers with code (5 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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15 May 2023 2 repositories listedRecently, Transformers have gained popularity in the computer vision community and also in medical image segmentation due to their ability to process global features effectively.
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27 Sep 2024 1 repository listed Syntology ran 8 of 12 samples · 4 unverifiedAltogether, our dataset and benchmark provide a comprehensive platform for evaluating flood forecasts, enabling future solutions for this critical challenge.
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4 Dec 2021 1 repository listed Syntology ran 0 of 15 samples · 15 unverifiedTo demonstrate the usefulness of this data set, we implement a neural network that takes advantage of the spatial information of this data to predict wildfire spread.
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16 Jul 2021 1 repository listed Syntology ran 10 of 11 samples · 1 unverifiedWe also introduce PASTIS, the first open-access SITS dataset with panoptic annotations.
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1 Jun 2019 1 repository listedTo address this gap in the literature, we provide the first crop type semantic segmentation dataset of small holder farms, specifically in Ghana and South Sudan.
Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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