{"id":448999,"date":"2026-01-07T22:19:51","date_gmt":"2026-01-07T21:19:51","guid":{"rendered":"https:\/\/forschung.fh-kaernten.at\/siena\/projects\/vine\/"},"modified":"2026-05-07T22:43:38","modified_gmt":"2026-05-07T20:43:38","slug":"vine","status":"publish","type":"page","link":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/projects\/vine\/","title":{"rendered":"VINE"},"content":{"rendered":"\t\t
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VINE<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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The ongoing PhD project, conducted in close cooperation with the University of Salzburg, aims to establish a high-resolution research and development (R&D) framework for the detection, monitoring and characterization of individual grapevines within vineyard systems. The framework integrates uncrewed aerial systems (UAS), 3D point-cloud analysis, multispectral time series and multiscale remote sensing approaches for phenological trajectory modelling and scalable vineyard monitoring. <\/span><\/p>

The methodological framework includes single-vine detection and crown segmentation from 3D point clouds, derivation of vine-specific physiological and structural indicators such as vegetation indices, canopy metrics and geometric descriptors; spatial and temporal analysis of vine health and stress patterns using spatial statistics and phenological trajectory analysis across multiple growth stages. In addition, the project investigates conjunctive UAS\u2013satellite approaches using Sentinel-2 and PlanetScope data for scaling vine-level information to coarser satellite resolutions. <\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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The research objectives are to characterize individual plants and derive geometric and physiological parameters capable of identifying health and stress dynamics within vineyards. Further goals include distinguishing temporal phenological variability from true physiological anomalies through dense multitemporal UAS observations combined with seasonal satellite image time series. <\/span><\/p>

Current research focuses on the development of multitemporal spectral-library-assisted machine learning frameworks for subpixel vine fraction estimation from multispectral satellite imagery. This includes the generation of phenology-aware UAS-derived spectral libraries, aggregation of object-based vine fractions to satellite pixel scales, and the integration of spectral similarity metrics with Random Forest regression models to improve scalable vineyard fraction mapping across different phenological stages. <\/span><\/p>

We gratefully acknowledge the support and provision of vineyard test sites by Weinhof Lagger in Millstatt and \u201cAuf der Leiten\u201d by Sem Kegley and Georg Lexer in Stegendorf, Carinthia.<\/span><\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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VINE The ongoing PhD project, conducted in close cooperation with the University of Salzburg, aims to establish a high-resolution research and development (R&D) framework for the detection, monitoring and characterization of individual grapevines within vineyard systems. The framework integrates uncrewed aerial systems (UAS), 3D point-cloud analysis, multispectral time series and Read more<\/a><\/p>\n","protected":false},"author":172,"featured_media":0,"parent":448124,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/template-pagebuilder-full-width.php","meta":{"_crdt_document":"","inline_featured_image":false,"ngg_post_thumbnail":0,"footnotes":""},"class_list":["post-448999","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/pages\/448999","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/users\/172"}],"replies":[{"embeddable":true,"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/comments?post=448999"}],"version-history":[{"count":1,"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/pages\/448999\/revisions"}],"predecessor-version":[{"id":449000,"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/pages\/448999\/revisions\/449000"}],"up":[{"embeddable":true,"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/pages\/448124"}],"wp:attachment":[{"href":"https:\/\/forschung.fh-kaernten.at\/siena\/en\/wp-json\/wp\/v2\/media?parent=448999"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}