{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:BY2PD2CWAT7VWILJDVVTMVN4XT","short_pith_number":"pith:BY2PD2CW","schema_version":"1.0","canonical_sha256":"0e34f1e85604ff5b21691d6b3655bcbcde06a4cf203e3e85d99ca2aaf350c0ae","source":{"kind":"arxiv","id":"2506.20388","version":1},"attestation_state":"computed","paper":{"title":"A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Han Wang, Huaguo Huang, Liangxiu Han, Shen Tan, Xin Zhang","submitted_at":"2025-06-25T12:51:49Z","abstract_excerpt":"Accurate, cost-effective monitoring of plantation aboveground biomass (AGB) is crucial for supporting local livelihoods and carbon sequestration initiatives like the China Certified Emission Reduction (CCER) program. High-resolution canopy height maps (CHMs) are essential for this, but standard lidar-based methods are expensive. While deep learning with RGB imagery offers an alternative, accurately extracting canopy height features remains challenging. To address this, we developed a novel model for high-resolution CHM generation using a Large Vision Foundation Model (LVFM). Our model integrat"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.20388","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-25T12:51:49Z","cross_cats_sorted":[],"title_canon_sha256":"e9150470572de0af01013c0efd2dfaf170abbaac7fc0cc2b9d0e799515a7bca6","abstract_canon_sha256":"984295f84e06261e352e1a9d4f5c03a5dbac7fcf85fa5662256387687391a624"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:27:04.728263Z","signature_b64":"BBOVKnI+h95D2NWwDIDGokaFRHgfD/J+WnEaYsChjm+W5GK6L5wiNKKfcxvbbh5NrFLoQNK+MUSvjxHPdcukBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e34f1e85604ff5b21691d6b3655bcbcde06a4cf203e3e85d99ca2aaf350c0ae","last_reissued_at":"2026-07-05T11:27:04.727783Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:27:04.727783Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Han Wang, Huaguo Huang, Liangxiu Han, Shen Tan, Xin Zhang","submitted_at":"2025-06-25T12:51:49Z","abstract_excerpt":"Accurate, cost-effective monitoring of plantation aboveground biomass (AGB) is crucial for supporting local livelihoods and carbon sequestration initiatives like the China Certified Emission Reduction (CCER) program. High-resolution canopy height maps (CHMs) are essential for this, but standard lidar-based methods are expensive. While deep learning with RGB imagery offers an alternative, accurately extracting canopy height features remains challenging. To address this, we developed a novel model for high-resolution CHM generation using a Large Vision Foundation Model (LVFM). Our model integrat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.20388","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.20388/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.20388","created_at":"2026-07-05T11:27:04.727836+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.20388v1","created_at":"2026-07-05T11:27:04.727836+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.20388","created_at":"2026-07-05T11:27:04.727836+00:00"},{"alias_kind":"pith_short_12","alias_value":"BY2PD2CWAT7V","created_at":"2026-07-05T11:27:04.727836+00:00"},{"alias_kind":"pith_short_16","alias_value":"BY2PD2CWAT7VWILJ","created_at":"2026-07-05T11:27:04.727836+00:00"},{"alias_kind":"pith_short_8","alias_value":"BY2PD2CW","created_at":"2026-07-05T11:27:04.727836+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT","json":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT.json","graph_json":"https://pith.science/api/pith-number/BY2PD2CWAT7VWILJDVVTMVN4XT/graph.json","events_json":"https://pith.science/api/pith-number/BY2PD2CWAT7VWILJDVVTMVN4XT/events.json","paper":"https://pith.science/paper/BY2PD2CW"},"agent_actions":{"view_html":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT","download_json":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT.json","view_paper":"https://pith.science/paper/BY2PD2CW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.20388&json=true","fetch_graph":"https://pith.science/api/pith-number/BY2PD2CWAT7VWILJDVVTMVN4XT/graph.json","fetch_events":"https://pith.science/api/pith-number/BY2PD2CWAT7VWILJDVVTMVN4XT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT/action/storage_attestation","attest_author":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT/action/author_attestation","sign_citation":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT/action/citation_signature","submit_replication":"https://pith.science/pith/BY2PD2CWAT7VWILJDVVTMVN4XT/action/replication_record"}},"created_at":"2026-07-05T11:27:04.727836+00:00","updated_at":"2026-07-05T11:27:04.727836+00:00"}