{"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":"nepovratna-sredstva-dezele-severno-porenje-vestfalija","status":"publish","type":"post","link":"https:\/\/geopard.tech\/sl\/blog\/grant-from-the-state-of-north-rhine-westphalia\/","title":{"rendered":"Hiperspektralni posnetki za kmetijstvo. Nepovratna sredstva de\u017eele Severno Porenje-Vestfalija."},"content":{"rendered":"

Z veseljem sporo\u010damo, da je bil projekt \u201cOkvir umetne inteligence za kvantitativno oceno lastnosti tal z uporabo hiperspektralnih satelitskih posnetkov\u201d izbran za delno financiranje s strani Ministrstva za okolje Severnega Porenja-Vestfalije in Evropske unije v okviru programa REACT-EU InnovationUmweltwirtschaft.NRW<\/a> program. Donacijo financira Evropski sklad za regionalni razvoj \/ Europ\u00e4ischen Fonds f\u00fcr regionale Entwicklung (EFRE).<\/p>\r\n

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

Uporaba umetne inteligence in statistike v tem projektu je omogo\u010dila dolo\u010ditev korelacije med hiperspektralnimi in talnimi podatki (npr. N, pH), kar je omogo\u010dilo natan\u010dnej\u0161i in prilagodljivej\u0161i pristop k analizi tal. Prihajajo\u010da izstrelitev hiperspektralnih satelitov s pogostimi intervali ponovnih obiskov in nemotenim dostopom do novih posnetkov brez zamud predstavlja ve\u010d prednosti, zlasti pri upravljanju hranil za trajnostno kmetijstvo. Tehnologija pomaga oceniti vsebnost in razpolo\u017eljivost hranil v tleh, kar kmetom omogo\u010da prilagajanje strategij gnojenja. To vodi do bolj\u0161e absorpcije hranil s strani rastlin, manj\u0161ega vpliva na okolje in prihrankov stro\u0161kov.<\/p>\r\n\r\n\r\n

Kaj je hiperspektralno slikanje?<\/h2>\r\n

Hiperspektralno slikanje je zmogljiva tehnika daljinskega zaznavanja, ki zajema elektromagnetni spekter z visoko spektralno lo\u010dljivostjo.<\/p>\r\n

Za razliko od tradicionalnih satelitskih posnetkov, ki obi\u010dajno sestavljajo tri do \u0161tiri pasove (rde\u010di, zeleni, modri in v\u010dasih bli\u017enji infrarde\u010di), hiperspektralni posnetki zbirajo od sto do tiso\u010de ozkih spektralnih pasov v vidnem, bli\u017enjem infrarde\u010dem in kratkovalovnem infrarde\u010dem obmo\u010dju. Vsak pas zagotavlja edinstvene informacije o lastnostih povr\u0161ja posnetega obmo\u010dja.<\/p>\r\n

Pridobiva se z uporabo senzorjev, name\u0161\u010denih na zra\u010dnih ali vesoljskih platformah. Ti senzorji uporabljajo spektrometre za merjenje intenzivnosti odbitega ali oddanega sevanja v ve\u010d ozkih pasovih.<\/p>\r\n

Z zbiranjem \u0161irokega nabora spektralnih podatkov lahko hiperspektralni senzorji zaznajo subtilne razlike v spektralnih podpisih razli\u010dnih materialov, kar omogo\u010da zelo podrobno in natan\u010dno analizo.<\/p>\r\n

Uporaba hiperspektralnih slik<\/h2>\r\n
    \r\n
  • Spremljanje okolja:<\/strong> Igra klju\u010dno vlogo pri spremljanju in ocenjevanju zdravja ekosistemov. Pomaga prepoznati stres vegetacije, spremljati spremembe pokrovnosti tal, odkrivati invazivne vrste in meriti parametre kakovosti vode, kot sta koncentracija klorofila ali motnost v jezerih in rekah.<\/li>\r\n
  • Kmetijstvo:<\/strong> Pomaga pri preciznem kmetijstvu, saj zagotavlja podrobne informacije o zdravju pridelkov, vsebnosti hranil, ravni vlage in odkrivanju bolezni. Kmetje lahko na podlagi podatkov sprejemajo odlo\u010ditve glede namakanja, gnojenja in zatiranja \u0161kodljivcev, kar ima za posledico optimiziran pridelek in manj\u0161i vpliv na okolje.<\/li>\r\n
  • Geologija in raziskovanje mineralov<\/strong>Je klju\u010dnega pomena za kartiranje geolo\u0161kih formacij, prepoznavanje nahajali\u0161\u010d mineralov in karakterizacijo vrst kamnin. Geologom pomaga odkriti spremembe v mineralni sestavi in kartirati potencialna obmo\u010dja za raziskovanje, kar prispeva k u\u010dinkovitej\u0161im in ciljno usmerjenim rudarskim dejavnostim.<\/li>\r\n
  • Gozdarstvo<\/strong>Pomaga pri gospodarjenju z gozdovi in spremljanju. Omogo\u010da identifikacijo drevesnih vrst, kvantifikacijo gozdne biomase, odkrivanje stresa dreves in oceno \u0161kode zaradi po\u017earov v naravi. Te informacije pomagajo pri trajnostnem gospodarjenju z gozdovi, ohranjanju biotske raznovrstnosti in sistemih zgodnjega opozarjanja na gozdne po\u017eare.<\/li>\r\n<\/ul>\r\n

    Prednosti hiperspektralnih slik<\/h2>\r\n

    Njegova glavna prednost je v sposobnosti zagotavljanja podrobnih spektralnih informacij, kar omogo\u010da razlikovanje materialov z visoko natan\u010dnostjo.<\/p>\r\n

    To vodi do izbolj\u0161ane klasifikacije in kartiranja tipov pokrovnosti tal, izbolj\u0161ane identifikacije specifi\u010dnih snovi in bolj\u0161ega razumevanja okoljskih procesov.<\/p>\r\n

    Hiperspektralne podatke je mogo\u010de analizirati tudi z uporabo naprednih algoritmov in tehnik strojnega u\u010denja za pridobivanje dragocenih vpogledov in avtomatizacijo interpretacije slik.<\/p>","protected":false},"excerpt":{"rendered":"

    Z veseljem sporo\u010damo, da je bil projekt \u201cOkvir umetne inteligence za kvantitativno oceno lastnosti tal z uporabo hiperspektralnih satelitskih posnetkov\u201d izbran za delno\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_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"_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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