{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3WZO3W6PXQ4KAV43RLAHU4WMWH","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e2e13de783c94228422feae083706b523bc30764e0b13feca180fc2a9eac4192","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T16:19:59Z","title_canon_sha256":"f7d822c3f76fb041d5b3dff68366d95f4d2ba73cb12c7ed8108724c9f601ca55"},"schema_version":"1.0","source":{"id":"2606.30511","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.30511","created_at":"2026-06-30T02:18:18Z"},{"alias_kind":"arxiv_version","alias_value":"2606.30511v1","created_at":"2026-06-30T02:18:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.30511","created_at":"2026-06-30T02:18:18Z"},{"alias_kind":"pith_short_12","alias_value":"3WZO3W6PXQ4K","created_at":"2026-06-30T02:18:18Z"},{"alias_kind":"pith_short_16","alias_value":"3WZO3W6PXQ4KAV43","created_at":"2026-06-30T02:18:18Z"},{"alias_kind":"pith_short_8","alias_value":"3WZO3W6P","created_at":"2026-06-30T02:18:18Z"}],"graph_snapshots":[{"event_id":"sha256:2490a7c66953df836a3d6fba63847c91511b49d24a4b4fb7c06d9d5866411a17","target":"graph","created_at":"2026-06-30T02:18:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.30511/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reliable high-resolution flood extent mapping from satellite imagery remains constrained by limited data fidelity and sensor-specific artifacts. Multispectral optical imagery is degraded by clouds, shadows, and urban confounders, while synthetic aperture radar (SAR) imagery is affected by speckle noise and sensor co-registration uncertainty. This work presents an integrated flood mapping framework that jointly addresses these limitations through curated datasets and novel learning strategies. We introduce a new Sentinel-2 (S2) and Sentinel-1 (S1) dataset covering the contiguous United States, ","authors_text":"Arkaprabha Ganguli, David Ma, Eugene Yan, Jeremy Feinstein, Shreya Pandit","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T16:19:59Z","title":"High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.30511","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8d2dedec9086407a0a21c3e807c926da7617b347beb1dbfa279881048d1f3fec","target":"record","created_at":"2026-06-30T02:18:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e2e13de783c94228422feae083706b523bc30764e0b13feca180fc2a9eac4192","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T16:19:59Z","title_canon_sha256":"f7d822c3f76fb041d5b3dff68366d95f4d2ba73cb12c7ed8108724c9f601ca55"},"schema_version":"1.0","source":{"id":"2606.30511","kind":"arxiv","version":1}},"canonical_sha256":"ddb2eddbcfbc38a0579b8ac07a72ccb1df36bfa5803b1a91b9895dc2945d4c90","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ddb2eddbcfbc38a0579b8ac07a72ccb1df36bfa5803b1a91b9895dc2945d4c90","first_computed_at":"2026-06-30T02:18:18.213387Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T02:18:18.213387Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vaTfoXAu0ZdFeC/qxsA5tRXAEfavSui5ewZJtnxc6KZenTyqwpIrd7GbTOmDBTZfVlp6Qo0lAQKz6HRNnf8DCA==","signature_status":"signed_v1","signed_at":"2026-06-30T02:18:18.213814Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.30511","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d2dedec9086407a0a21c3e807c926da7617b347beb1dbfa279881048d1f3fec","sha256:2490a7c66953df836a3d6fba63847c91511b49d24a4b4fb7c06d9d5866411a17"],"state_sha256":"12d5fecf1b4aedd332b05f013c5d5d3d3e6679d8c699b398867c587f1e29ec50"}