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The evaluator writes that this let farming resume quickly and contributed to food security and economic recovery. In another section the evaluator credits satellite imagery, artificial intelligence and machine learning with the rapid reclamation of more than 21,000 km² of farmland. The evaluator does not name the tool, describe the model or cite a source for the area. The evaluator does not separate the AI's part from other data work. 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UNDP Ukraine commissioned a midterm evaluation, which an international consultant delivered on 30 December 2025. The evaluator used document review, interviews, focus groups and field visits. The evaluator found that AI-assisted and data-driven approaches enabled the cancellation of over 21,500 km² of agricultural land from the national database in 2023 alone. The evaluator writes that this let farming resume quickly and contributed to food security and economic recovery. In another section the evaluator credits satellite imagery, artificial intelligence and machine learning with the rapid reclamation of more than 21,000 km² of farmland. The evaluator does not name the tool, describe the model or cite a source for the area. The evaluator does not separate the AI's part from other data work. On field visits, the evaluator observed that farmers had resumed work on land that project-supported surveys had released."}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["summary","account"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].autonomy_permissions":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].component_role":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].deployment_configuration":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].inputs_outputs":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].model_name":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].model_version":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"systems[].product_name":{"state":"value_present","value":{"kind":"record_fields","fields":{"system":"AI-assisted, satellite-imagery and machine-learning approach to cancelling and prioritizing suspected hazardous areas in Ukraine's mine action database (unnamed tool)"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["system"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"systems[].provider":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"taxonomy_crosswalks[]":{"state":"unresolved","provenance":{"kind":"curatorial","basis":"Editorial assignment.","record_fields":[],"source_refs":[]},"reason":"This is an explicit unresolved assignment: the sources on record do not settle this question.","review_state":"not_assessed","coverage":"partial"},"title":{"state":"value_present","value":{"kind":"record_fields","fields":{"title":"An evaluation for UNDP credits AI-assisted approaches with cancelling over 21,500 km² of Ukrainian farmland from the hazard database in 2023","headline":"AI helps Ukraine remove 21,500 km² of farmland from its hazard records"}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["title","headline"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"},"version":{"state":"value_present","value":{"kind":"identifiers","identifiers":["80aa3cfdd27aa1abdd8256660654e476524d9063177ac1083a101316fd84b68f"],"role":"SHA-256 of the complete public record and its assessments"},"provenance":{"kind":"curatorial","basis":"SHA-256 of the public record, its assessments, and its displayed answers and notes, excluding its own identifier and the derived coverage summary.","record_fields":[],"source_refs":[]},"review_state":"record_mapped","coverage":"complete"},"workflow":{"state":"value_present","value":{"kind":"record_fields","fields":{"account":"UNDP runs the Mine Action Project in Ukraine with the national authorities for mine action and the State Emergency Service. UNDP Ukraine commissioned a midterm evaluation, which an international consultant delivered on 30 December 2025. The evaluator used document review, interviews, focus groups and field visits. The evaluator found that AI-assisted and data-driven approaches enabled the cancellation of over 21,500 km² of agricultural land from the national database in 2023 alone. The evaluator writes that this let farming resume quickly and contributed to food security and economic recovery. In another section the evaluator credits satellite imagery, artificial intelligence and machine learning with the rapid reclamation of more than 21,000 km² of farmland. The evaluator does not name the tool, describe the model or cite a source for the area. The evaluator does not separate the AI's part from other data work. On field visits, the evaluator observed that farmers had resumed work on land that project-supported surveys had released.","replication":{"produced_by":["UNDP's research and innovation work applied satellite imagery, artificial intelligence and machine learning.","The approach supported land cancellation and prioritization for the national authorities in charge of mine action.","Cancelled land was removed from the national database."],"must_hold":["Information systems must stay aligned with the national IMSMA database.","Mine action must stay embedded in government-led planning and prioritization."],"echoes":[]}}},"provenance":{"kind":"legacy_record","basis":"Editorial assignment.","record_fields":["account","replication"],"source_refs":[]},"review_state":"record_mapped","coverage":"partial"}},"summary":{"total":91,"addressed":91,"known":28,"reviewed":2,"reviewed_complete":2,"reviewed_partial":0,"record_mapped":26,"review_not_assessed":63,"not_assessed":0,"complete":false,"by_state":{"value_present":28,"not_reported":0,"unresolved":63,"not_assessed":0,"not_applicable":0,"withheld":0,"source_unavailable":0}}},"presentation_version":"848e623b41f18615039bbd40f59732b87bcee874a26d71acd17057c05eef026a"}