{"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":"dotacja-z-kraju-zwiazkowego-nadrenia-polnocna-westfalia","status":"publish","type":"post","link":"https:\/\/geopard.tech\/pl\/blog\/grant-from-the-state-of-north-rhine-westphalia\/","title":{"rendered":"Obrazowanie hiperspektralne dla rolnictwa. Grant z kraju zwi\u0105zkowego Nadrenia P\u00f3\u0142nocna-Westfalia."},"content":{"rendered":"

Z przyjemno\u015bci\u0105 informujemy, \u017ce projekt \u201cRamowa analiza sztucznej inteligencji do ilo\u015bciowej oceny w\u0142a\u015bciwo\u015bci gleby z wykorzystaniem hiperspektralnych obraz\u00f3w satelitarnych\u201d zosta\u0142 wybrany do cz\u0119\u015bciowego dofinansowania przez Ministerstwo \u015arodowiska Nadrenii P\u00f3\u0142nocnej-Westfalii i Uni\u0119 Europejsk\u0105 w ramach REACT-EU InnovationUmweltwirtschaft.NRW<\/a> program. Dotacja finansowana jest ze \u015brodk\u00f3w Europejskiego Funduszu Rozwoju Regionalnego \/ Europ\u00e4ischen Fonds f\u00fcr regionale Entwicklung (EFRE).<\/p>\r\n

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

Wykorzystanie sztucznej inteligencji i statystyki w tym projekcie umo\u017cliwi\u0142o okre\u015blenie korelacji mi\u0119dzy danymi hiperspektralnymi a danymi glebowymi (np. azotem, pH), co umo\u017cliwi\u0142o bardziej precyzyjne i skalowalne podej\u015bcie do analizy gleby. Zbli\u017caj\u0105ce si\u0119 wystrzelenie satelit\u00f3w hiperspektralnych z cz\u0119stymi rewizytami i bezproblemowym dost\u0119pem do nowych obraz\u00f3w bez op\u00f3\u017anie\u0144 niesie ze sob\u0105 szereg korzy\u015bci, szczeg\u00f3lnie w zakresie zarz\u0105dzania sk\u0142adnikami od\u017cywczymi w zr\u00f3wnowa\u017conym rolnictwie. Technologia ta pomaga oceni\u0107 zawarto\u015b\u0107 i dost\u0119pno\u015b\u0107 sk\u0142adnik\u00f3w od\u017cywczych w glebie, umo\u017cliwiaj\u0105c rolnikom dostosowanie strategii nawo\u017cenia. Prowadzi to do lepszego pobierania sk\u0142adnik\u00f3w od\u017cywczych przez ro\u015bliny, zmniejszenia wp\u0142ywu na \u015brodowisko i oszcz\u0119dno\u015bci koszt\u00f3w.<\/p>\r\n\r\n\r\n

Czym jest obrazowanie hiperspektralne?<\/h2>\r\n

Obrazowanie hiperspektralne to pot\u0119\u017cna technika teledetekcji, kt\u00f3ra pozwala na rejestrowanie widma elektromagnetycznego z wysok\u0105 rozdzielczo\u015bci\u0105 spektraln\u0105.<\/p>\r\n

W przeciwie\u0144stwie do tradycyjnych zdj\u0119\u0107 satelitarnych, kt\u00f3re zazwyczaj sk\u0142adaj\u0105 si\u0119 z trzech do czterech pasm (czerwonego, zielonego, niebieskiego i czasami bliskiej podczerwieni), zdj\u0119cia hiperspektralne gromadz\u0105 setki, a nawet tysi\u0105ce w\u0105skich pasm widmowych obejmuj\u0105cych zakresy widzialne, bliskiej podczerwieni i podczerwieni kr\u00f3tkofalowej. Ka\u017cde pasmo dostarcza unikalnych informacji o w\u0142a\u015bciwo\u015bciach powierzchni obrazowanego obszaru.<\/p>\r\n

Pomiary przeprowadza si\u0119 za pomoc\u0105 czujnik\u00f3w zamontowanych na platformach powietrznych lub kosmicznych. Czujniki te wykorzystuj\u0105 spektrometry do pomiaru intensywno\u015bci promieniowania odbitego lub emitowanego w wielu w\u0105skich pasmach.<\/p>\r\n

Gromadz\u0105c szerok\u0105 gam\u0119 danych spektralnych, czujniki hiperspektralne mog\u0105 wykrywa\u0107 drobne r\u00f3\u017cnice w sygnaturach spektralnych r\u00f3\u017cnych materia\u0142\u00f3w, co pozwala na niezwykle szczeg\u00f3\u0142ow\u0105 i precyzyjn\u0105 analiz\u0119.<\/p>\r\n

Zastosowania obrazowania hiperspektralnego<\/h2>\r\n
    \r\n
  • Monitoring \u015brodowiska:<\/strong> Odgrywa kluczow\u0105 rol\u0119 w monitorowaniu i ocenie stanu ekosystem\u00f3w. Pomaga identyfikowa\u0107 stres ro\u015blinno\u015bci, monitorowa\u0107 zmiany pokrycia terenu, wykrywa\u0107 gatunki inwazyjne oraz mierzy\u0107 parametry jako\u015bci wody, takie jak st\u0119\u017cenie chlorofilu czy m\u0119tno\u015b\u0107 w jeziorach i rzekach.<\/li>\r\n
  • Rolnictwo:<\/strong> Wspomaga rolnictwo precyzyjne, dostarczaj\u0105c szczeg\u00f3\u0142owych informacji o kondycji upraw, zawarto\u015bci sk\u0142adnik\u00f3w od\u017cywczych, poziomie wilgotno\u015bci i wykrywaniu chor\u00f3b. Rolnicy mog\u0105 podejmowa\u0107 decyzje dotycz\u0105ce nawadniania, nawo\u017cenia i zwalczania szkodnik\u00f3w w oparciu o dane, co przek\u0142ada si\u0119 na optymalizacj\u0119 plon\u00f3w i ograniczenie wp\u0142ywu na \u015brodowisko.<\/li>\r\n
  • Geologia i poszukiwanie z\u0142\u00f3\u017c mineralnych<\/strong>:Jest niezb\u0119dny do mapowania formacji geologicznych, identyfikacji z\u0142\u00f3\u017c mineralnych i charakteryzowania rodzaj\u00f3w ska\u0142. Pomaga geologom wykrywa\u0107 zmiany w sk\u0142adzie mineralnym i mapowa\u0107 potencjalne obszary poszukiwa\u0144, przyczyniaj\u0105c si\u0119 do bardziej efektywnej i ukierunkowanej dzia\u0142alno\u015bci g\u00f3rniczej.<\/li>\r\n
  • Le\u015bnictwo<\/strong>Wspomaga zarz\u0105dzanie lasami i ich monitorowanie. Umo\u017cliwia identyfikacj\u0119 gatunk\u00f3w drzew, kwantyfikacj\u0119 biomasy le\u015bnej, wykrywanie stresu drzewnego i ocen\u0119 szk\u00f3d spowodowanych po\u017carami. Informacje te wspomagaj\u0105 zr\u00f3wnowa\u017con\u0105 gospodark\u0119 le\u015bn\u0105, ochron\u0119 bior\u00f3\u017cnorodno\u015bci oraz systemy wczesnego ostrzegania przed po\u017carami las\u00f3w.<\/li>\r\n<\/ul>\r\n

    Korzy\u015bci z obrazowania hiperspektralnego<\/h2>\r\n

    Jego g\u0142\u00f3wn\u0105 zalet\u0105 jest mo\u017cliwo\u015b\u0107 uzyskania szczeg\u00f3\u0142owych informacji spektralnych, co pozwala na rozr\u00f3\u017cnianie materia\u0142\u00f3w z du\u017c\u0105 dok\u0142adno\u015bci\u0105.<\/p>\r\n

    Dzi\u0119ki temu mo\u017cliwa jest lepsza klasyfikacja i mapowanie rodzaj\u00f3w pokrycia terenu, lepsza identyfikacja okre\u015blonych substancji i lepsze zrozumienie proces\u00f3w zachodz\u0105cych w \u015brodowisku.<\/p>\r\n

    Dane hiperspektralne mo\u017cna r\u00f3wnie\u017c analizowa\u0107, stosuj\u0105c zaawansowane algorytmy i techniki uczenia maszynowego, co pozwala na wyci\u0105ganie cennych wniosk\u00f3w i automatyzacj\u0119 interpretacji obraz\u00f3w.<\/p>","protected":false},"excerpt":{"rendered":"

    Z przyjemno\u015bci\u0105 informujemy, \u017ce projekt \u201cRamowa analiza sztucznej inteligencji do ilo\u015bciowej oceny w\u0142a\u015bciwo\u015bci gleby z wykorzystaniem hiperspektralnych obraz\u00f3w satelitarnych\u201d zosta\u0142 wybrany do cz\u0119\u015bciowego\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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