{"id":4152,"date":"2022-03-22T07:05:58","date_gmt":"2022-03-22T06:05:58","guid":{"rendered":"https:\/\/geopard.tech\/?p=4152"},"modified":"2023-08-25T14:54:43","modified_gmt":"2023-08-25T12:54:43","slug":"zuschuss-des-landes-nordrhein-westfalen","status":"publish","type":"post","link":"https:\/\/geopard.tech\/de\/blog\/grant-from-the-state-of-north-rhine-westphalia\/","title":{"rendered":"Hyperspektrale Bildgebung f\u00fcr die Landwirtschaft. Gef\u00f6rdert vom Land Nordrhein-Westfalen."},"content":{"rendered":"

Wir freuen uns, bekanntgeben zu k\u00f6nnen, dass das Projekt \u201cRahmenwerk f\u00fcr k\u00fcnstliche Intelligenz zur quantitativen Sch\u00e4tzung von Bodeneigenschaften mithilfe hyperspektraler Satellitenbilder\u201d vom Ministerium f\u00fcr Umwelt und Umwelt des Landes Nordrhein-Westfalen und der Europ\u00e4ischen Union im Rahmen des Programms zur Teilf\u00f6rderung ausgew\u00e4hlt wurde. REACT-EU InnovationUmweltwirtschaft.NRW<\/a> Programm. Das Stipendium wird vom Europ\u00e4ischen Fonds f\u00fcr regionale Entwicklung (EFRE) finanziert.<\/p>\r\n

\"der<\/p>\r\n

Der Einsatz von k\u00fcnstlicher Intelligenz und Statistik in diesem Projekt erm\u00f6glichte die Bestimmung der Korrelation zwischen hyperspektralen Daten und Bodendaten (z. B. Stickstoff, pH-Wert) und damit einen pr\u00e4ziseren und skalierbaren Ansatz f\u00fcr die Bodenanalyse. Der bevorstehende Start hyperspektraler Satelliten mit kurzen \u00dcberflugintervallen und nahtlosem Zugriff auf neue Bilddaten bietet zahlreiche Vorteile, insbesondere f\u00fcr das N\u00e4hrstoffmanagement in der nachhaltigen Landwirtschaft. Die Technologie hilft, N\u00e4hrstoffgehalt und -verf\u00fcgbarkeit im Boden zu bestimmen und erm\u00f6glicht Landwirten so eine bedarfsgerechte D\u00fcngung. Dies f\u00fchrt zu einer besseren N\u00e4hrstoffaufnahme durch die Pflanzen, einer geringeren Umweltbelastung und Kosteneinsparungen.<\/p>\r\n\r\n\r\n

Was ist hyperspektrale Bildgebung?<\/h2>\r\n

Hyperspektrale Bildgebung ist eine leistungsstarke Fernerkundungstechnik, die das elektromagnetische Spektrum mit hoher spektraler Aufl\u00f6sung erfasst.<\/p>\r\n

Im Gegensatz zu herk\u00f6mmlichen Satellitenbildern, die typischerweise aus drei bis vier Spektralb\u00e4ndern (Rot, Gr\u00fcn, Blau und manchmal Nahinfrarot) bestehen, erfassen hyperspektrale Bilder Hunderte bis Tausende schmaler Spektralb\u00e4nder im sichtbaren, nahinfraroten und kurzwelligen Infrarotbereich. Jedes Band liefert einzigartige Informationen \u00fcber die Oberfl\u00e4cheneigenschaften des abgebildeten Gebiets.<\/p>\r\n

Die Daten werden mithilfe von Sensoren erfasst, die auf luft- oder weltraumgest\u00fctzten Plattformen montiert sind. Diese Sensoren verwenden Spektrometer, um die Intensit\u00e4t der reflektierten oder emittierten Strahlung in mehreren schmalen Spektralb\u00e4ndern zu messen.<\/p>\r\n

Durch die Erfassung einer breiten Palette spektraler Daten k\u00f6nnen hyperspektrale Sensoren subtile Unterschiede in den spektralen Signaturen verschiedener Materialien erkennen und so eine hochdetaillierte und pr\u00e4zise Analyse erm\u00f6glichen.<\/p>\r\n

Anwendungen von Hyperspektralbildern<\/h2>\r\n
    \r\n
  • Umwelt\u00fcberwachung:<\/strong> Es spielt eine entscheidende Rolle bei der \u00dcberwachung und Bewertung des Zustands von \u00d6kosystemen. Es hilft, Vegetationsstress zu erkennen, Landnutzungs\u00e4nderungen zu \u00fcberwachen, invasive Arten aufzusp\u00fcren und Wasserqualit\u00e4tsparameter wie Chlorophyllkonzentration oder Tr\u00fcbung in Seen und Fl\u00fcssen zu messen.<\/li>\r\n
  • Landwirtschaft:<\/strong> Es unterst\u00fctzt die Pr\u00e4zisionslandwirtschaft durch detaillierte Informationen \u00fcber Pflanzengesundheit, N\u00e4hrstoffgehalt, Feuchtigkeitsgehalt und Krankheitserkennung. Landwirte k\u00f6nnen datengest\u00fctzte Entscheidungen hinsichtlich Bew\u00e4sserung, D\u00fcngung und Sch\u00e4dlingsbek\u00e4mpfung treffen, was zu optimierten Ernteertr\u00e4gen und einer geringeren Umweltbelastung f\u00fchrt.<\/li>\r\n
  • Geologie und Mineralexploration<\/strong>Es ist von entscheidender Bedeutung f\u00fcr die Kartierung geologischer Formationen, die Identifizierung von Mineralvorkommen und die Charakterisierung von Gesteinsarten. Es hilft Geologen, Ver\u00e4nderungen in der Mineralzusammensetzung zu erkennen und potenzielle Explorationsgebiete zu kartieren, was zu effizienteren und gezielteren Bergbauaktivit\u00e4ten beitr\u00e4gt.<\/li>\r\n
  • Forstwirtschaft<\/strong>Es unterst\u00fctzt die Forstwirtschaft und -\u00fcberwachung. Es erm\u00f6glicht die Bestimmung von Baumarten, die Quantifizierung der Waldbiomasse, die Erkennung von Baumstress und die Beurteilung von Waldbrandsch\u00e4den. Diese Informationen tragen zu einer nachhaltigen Forstwirtschaft, dem Erhalt der Biodiversit\u00e4t und Fr\u00fchwarnsystemen f\u00fcr Waldbr\u00e4nde bei.<\/li>\r\n<\/ul>\r\n

    Vorteile hyperspektraler Bildgebung<\/h2>\r\n

    Sein Hauptvorteil liegt in seiner F\u00e4higkeit, detaillierte Spektralinformationen zu liefern, die eine hochpr\u00e4zise Unterscheidung von Materialien erm\u00f6glichen.<\/p>\r\n

    Dies f\u00fchrt zu einer verbesserten Klassifizierung und Kartierung der Landbedeckungstypen, einer besseren Identifizierung spezifischer Substanzen und einem besseren Verst\u00e4ndnis der Umweltprozesse.<\/p>\r\n

    Hyperspektrale Daten k\u00f6nnen auch mithilfe fortschrittlicher Algorithmen und maschineller Lernverfahren analysiert werden, um wertvolle Erkenntnisse zu gewinnen und die Bildinterpretation zu automatisieren.<\/p>","protected":false},"excerpt":{"rendered":"

    Wir freuen uns, bekannt zu geben, dass das Projekt \u201cRahmenwerk f\u00fcr k\u00fcnstliche Intelligenz zur quantitativen Sch\u00e4tzung von Bodeneigenschaften mithilfe hyperspektraler Satellitenbilder\u201d f\u00fcr eine Teilf\u00f6rderung ausgew\u00e4hlt wurde\u2026<\/p>","protected":false},"author":210249426,"featured_media":4161,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_eb_attr":"","content-type":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_wpcom_ai_launchpad_first_post":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"{title}\n\n{excerpt}\n\n{url}","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"_wpas_customize_per_network":false,"jetpack_post_was_ever_published":false},"categories":[1661,1365],"tags":[1599],"class_list":["post-4152","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-satellite-imagery","category-news","tag-remote-sensing"],"acf":[],"yoast_head":"\nHyperspectral imagery for Agriculture. 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