https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/Head https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo http://www.nanopub.org/nschema#hasAssertion https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/assertion https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo http://www.nanopub.org/nschema#hasProvenance https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/provenance https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/pubinfo https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/assertion https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study http://www.w3.org/1999/02/22-rdf-syntax-ns#type https://w3id.org/sciencelive/o/terms/FORRT-Replication-Study https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study http://www.w3.org/1999/02/22-rdf-syntax-ns#type https://w3id.org/sciencelive/o/terms/Replication-Study https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study http://www.w3.org/2000/01/rdf-schema#label Cross-discipline application of a BioImage.IO nucleus model to EO water segmentation via Galaxy https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study http://www.w3.org/2004/02/skos/core#related http://www.wikidata.org/entity/Q1367339 https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study http://www.w3.org/2004/02/skos/core#related http://www.wikidata.org/entity/Q197536 https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study http://www.w3.org/2004/02/skos/core#related http://www.wikidata.org/entity/Q56933 https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study https://w3id.org/sciencelive/o/terms/hasDeviationDescription Relative to the original Galaxy microscopy tutorial, only the input domain changed: DAPI fluorescence images of nuclei were replaced by inverted near-infrared Landsat composites of pond landscapes. The model weights, input axes and size, inference tool version, and the full post-processing chain (split → foreground−boundaries → threshold 0.6 → label map → overlay) are unchanged. No retraining, fine-tuning, or architecture change was performed. https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study https://w3id.org/sciencelive/o/terms/hasDiscipline http://www.wikidata.org/entity/Q199687 https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study https://w3id.org/sciencelive/o/terms/hasMethodologyDescription Annual peak-summer (July–August) Landsat Collection-2 Level-2 surface-reflectance composites were built over the Alaska Arctic Coastal Plain from the Microsoft Planetary Computer, fill-masked and median-composited, then resampled to a 256×256 single-channel image with the near-infrared band inverted so that water reads as bright objects on a dark background. Each image was run through the unchanged Galaxy "Process image using a BioImage.IO model" workflow (main_workflow.ga; NucleiSegmentationBoundaryModel; input axes bcyx, size 256,256,1,1) on usegalaxy.eu via BioBlend: model inference, split into foreground and boundary channels, compute foreground minus boundaries, threshold at 0.6, convert to a connected-component label map, and overlay. Total water area was taken as thresholded pixels times per-pixel ground area; body count as the number of labels. NDWI was computed from the green and near-infrared bands as the comparator. A byte-identical local TorchScript path (torch.load of the same model, identical post-processing) reproduces the Galaxy result for credential-free CI. https://w3id.org/sciencelive/np/RAzxasLjpd21-0cbBRwlKEbmprb2guev7X3pOhvrPE3yo/bmz-eo-water-study https://w3id.org/sciencelive/o/terms/hasScopeDescription Whether the segmentation behaviour of the BioImage.IO nucleus-boundary workflow — delineating discrete bright "blob" objects and yielding their total area and count — holds when the input is optical satellite imagery of open-water bodies rather than fluorescence microscopy of cell nuclei, benchmarked against the NDWI water index. In scope: open-water delineation (total area and body count) on cloud-screened peak-summer Landsat composites of an Arctic thermokarst-pond landscape. 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