{"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":"grant-od-spolkovej-krajiny-severne-porynie-vestfalsko","status":"publish","type":"post","link":"https:\/\/geopard.tech\/sk\/blog\/grant-from-the-state-of-north-rhine-westphalia\/","title":{"rendered":"Hyperspektr\u00e1lne zobrazovanie pre po\u013enohospod\u00e1rstvo. Grant od spolkovej krajiny Severn\u00e9 Por\u00fdnie-Vestf\u00e1lsko."},"content":{"rendered":"

S pote\u0161en\u00edm oznamujeme, \u017ee projekt \u201cR\u00e1mec umelej inteligencie pre kvantitat\u00edvny odhad vlastnost\u00ed p\u00f4dy pomocou hyperspektr\u00e1lnych satelitn\u00fdch sn\u00edmok\u201d bol vybran\u00fd na \u010diasto\u010dn\u00e9 financovanie Ministerstvom \u017eivotn\u00e9ho prostredia Severn\u00e9ho Por\u00fdnia-Vestf\u00e1lska a Eur\u00f3pskou \u00faniou v r\u00e1mci REACT-EU InnovationUmweltwirtschaft.NRW<\/a> program. Grant je financovan\u00fd z Eur\u00f3pskeho fondu region\u00e1lneho rozvoja \/ Europ\u00e4ischen Fonds f\u00fcr regionale Entwicklung (EFRE).<\/p>\r\n

\"Eur\u00f3psky<\/p>\r\n

Pou\u017eitie umelej inteligencie a \u0161tatistiky v tomto projekte umo\u017enilo ur\u010di\u0165 korel\u00e1ciu medzi hyperspektr\u00e1lnymi a p\u00f4dnymi \u00fadajmi (napr. N, pH), \u010do u\u013eah\u010dilo presnej\u0161\u00ed a \u0161k\u00e1lovate\u013enej\u0161\u00ed pr\u00edstup k anal\u00fdze p\u00f4dy. Nadch\u00e1dzaj\u00face vypustenie hyperspektr\u00e1lnych satelitov s \u010dast\u00fdmi intervalmi op\u00e4tovn\u00fdch n\u00e1v\u0161tev a bezprobl\u00e9mov\u00fdm pr\u00edstupom k nov\u00fdm sn\u00edmkam bez oneskorenia predstavuje nieko\u013eko v\u00fdhod, najm\u00e4 v oblasti riadenia \u017eiv\u00edn pre udr\u017eate\u013en\u00e9 po\u013enohospod\u00e1rstvo. T\u00e1to technol\u00f3gia pom\u00e1ha pos\u00fadi\u0165 obsah a dostupnos\u0165 \u017eiv\u00edn v p\u00f4de, \u010do umo\u017e\u0148uje po\u013enohospod\u00e1rom prisp\u00f4sobi\u0165 strat\u00e9gie hnojenia. To vedie k lep\u0161iemu pr\u00edjmu \u017eiv\u00edn rastlinami, zn\u00ed\u017een\u00e9mu vplyvu na \u017eivotn\u00e9 prostredie a \u00faspor\u00e1m n\u00e1kladov.<\/p>\r\n\r\n\r\n

\u010co je hyperspektr\u00e1lne zobrazenie?<\/h2>\r\n

Hyperspektr\u00e1lne sn\u00edmkovanie je v\u00fdkonn\u00e1 technika dia\u013ekov\u00e9ho prieskumu Zeme, ktor\u00e1 zachyt\u00e1va elektromagnetick\u00e9 spektrum s vysok\u00fdm spektr\u00e1lnym rozl\u00ed\u0161en\u00edm.<\/p>\r\n

Na rozdiel od tradi\u010dn\u00fdch satelitn\u00fdch sn\u00edmok, ktor\u00e9 zvy\u010dajne pozost\u00e1vaj\u00fa z troch a\u017e \u0161tyroch p\u00e1siem (\u010derven\u00e9, zelen\u00e9, modr\u00e9 a niekedy bl\u00edzke infra\u010derven\u00e9), hyperspektr\u00e1lne sn\u00edmky zhroma\u017e\u010fuj\u00fa stovky a\u017e tis\u00edce \u00fazkych spektr\u00e1lnych p\u00e1siem vo vidite\u013enej, bl\u00edzkej infra\u010dervenej a kr\u00e1tkovlnnej infra\u010dervenej oblasti. Ka\u017ed\u00e9 p\u00e1smo poskytuje jedine\u010dn\u00e9 inform\u00e1cie o povrchov\u00fdch vlastnostiach sn\u00edmanej oblasti.<\/p>\r\n

Z\u00edskava sa pomocou senzorov namontovan\u00fdch na vzdu\u0161n\u00fdch alebo vesm\u00edrnych platform\u00e1ch. Tieto senzory pou\u017e\u00edvaj\u00fa spektrometre na meranie intenzity odrazen\u00e9ho alebo vy\u017earovan\u00e9ho \u017eiarenia vo viacer\u00fdch \u00fazkych p\u00e1smach.<\/p>\r\n

Zberom \u0161irokej \u0161k\u00e1ly spektr\u00e1lnych \u00fadajov dok\u00e1\u017eu hyperspektr\u00e1lne senzory detekova\u0165 jemn\u00e9 rozdiely v spektr\u00e1lnych podpisoch r\u00f4znych materi\u00e1lov, \u010do umo\u017e\u0148uje vysoko detailn\u00fa a presn\u00fa anal\u00fdzu.<\/p>\r\n

Aplik\u00e1cie hyperspektr\u00e1lneho zobrazovania<\/h2>\r\n
    \r\n
  • Monitorovanie \u017eivotn\u00e9ho prostredia:<\/strong> Zohr\u00e1va d\u00f4le\u017eit\u00fa \u00falohu pri monitorovan\u00ed a hodnoten\u00ed zdravia ekosyst\u00e9mov. Pom\u00e1ha identifikova\u0165 stres veget\u00e1cie, monitorova\u0165 zmeny krajinnej pokr\u00fdvky, odha\u013eova\u0165 inv\u00e1zne druhy a mera\u0165 parametre kvality vody, ako je koncentr\u00e1cia chlorofylu alebo z\u00e1kal v jazer\u00e1ch a riekach.<\/li>\r\n
  • Po\u013enohospod\u00e1rstvo:<\/strong> Pom\u00e1ha v presnom po\u013enohospod\u00e1rstve t\u00fdm, \u017ee poskytuje podrobn\u00e9 inform\u00e1cie o zdrav\u00ed plod\u00edn, obsahu \u017eiv\u00edn, \u00farovni vlhkosti a detekcii chor\u00f4b. Po\u013enohospod\u00e1ri m\u00f4\u017eu na z\u00e1klade \u00fadajov robi\u0165 rozhodnutia t\u00fdkaj\u00face sa zavla\u017eovania, hnojenia a ochrany proti \u0161kodcom, \u010do vedie k optimalizovan\u00fdm v\u00fdnosom plod\u00edn a zn\u00ed\u017een\u00e9mu vplyvu na \u017eivotn\u00e9 prostredie.<\/li>\r\n
  • Geol\u00f3gia a prieskum nerastn\u00fdch surov\u00edn<\/strong>Je u\u017eito\u010dn\u00fd pri mapovan\u00ed geologick\u00fdch form\u00e1ci\u00ed, identifik\u00e1cii lo\u017e\u00edsk nerastov a charakteriz\u00e1cii typov horn\u00edn. Pom\u00e1ha geol\u00f3gom odhali\u0165 zmeny v zlo\u017een\u00ed miner\u00e1lov a mapova\u0165 potenci\u00e1lne oblasti na prieskum, \u010d\u00edm prispieva k efekt\u00edvnej\u0161\u00edm a cielenej\u0161\u00edm \u0165a\u017eobn\u00fdm \u010dinnostiam.<\/li>\r\n
  • Lesn\u00edctvo<\/strong>Pom\u00e1ha pri obhospodarovan\u00ed lesov a monitorovan\u00ed. Umo\u017e\u0148uje identifik\u00e1ciu druhov stromov, kvantifik\u00e1ciu lesnej biomasy, detekciu stresu stromov a hodnotenie \u0161k\u00f4d sp\u00f4soben\u00fdch lesn\u00fdmi po\u017eiarmi. Tieto inform\u00e1cie pom\u00e1haj\u00fa pri udr\u017eate\u013enom obhospodarovan\u00ed lesov, ochrane biodiverzity a syst\u00e9moch v\u010dasn\u00e9ho varovania pred lesn\u00fdmi po\u017eiarmi.<\/li>\r\n<\/ul>\r\n

    V\u00fdhody hyperspektr\u00e1lneho zobrazovania<\/h2>\r\n

    Jeho hlavnou v\u00fdhodou je schopnos\u0165 poskytova\u0165 podrobn\u00e9 spektr\u00e1lne inform\u00e1cie, \u010do umo\u017e\u0148uje rozli\u0161ovanie materi\u00e1lov s vysokou presnos\u0165ou.<\/p>\r\n

    To vedie k lep\u0161ej klasifik\u00e1cii a mapovaniu typov krajinnej pokr\u00fdvky, lep\u0161ej identifik\u00e1cii \u0161pecifick\u00fdch l\u00e1tok a lep\u0161iemu pochopeniu environment\u00e1lnych procesov.<\/p>\r\n

    Hyperspektr\u00e1lne d\u00e1ta je mo\u017en\u00e9 analyzova\u0165 aj pomocou pokro\u010dil\u00fdch algoritmov a techn\u00edk strojov\u00e9ho u\u010denia na z\u00edskanie cenn\u00fdch poznatkov a automatiz\u00e1ciu interpret\u00e1cie obrazu.<\/p>","protected":false},"excerpt":{"rendered":"

    S pote\u0161en\u00edm oznamujeme, \u017ee projekt \u201cR\u00e1mec umelej inteligencie pre kvantitat\u00edvne odhadovanie vlastnost\u00ed p\u00f4dy pomocou hyperspektr\u00e1lnych satelitn\u00fdch sn\u00edmok\u201d bol vybran\u00fd na \u010diasto\u010dn\u00fd\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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