{"id":1195,"date":"2020-04-30T10:55:00","date_gmt":"2020-04-30T08:55:00","guid":{"rendered":"https:\/\/geopard.tech\/?p=1195"},"modified":"2024-12-01T23:12:12","modified_gmt":"2024-12-01T22:12:12","slug":"analityka-wielowarstwowa","status":"publish","type":"post","link":"https:\/\/geopard.tech\/pl\/blog\/multi-layer-analytics\/","title":{"rendered":"Wielowarstwowa (zintegrowana) analiza danych w rolnictwie precyzyjnym"},"content":{"rendered":"

Precyzyjne rolnictwo jest w stanie generowa\u0107\u00a0ogromne ilo\u015bci danych<\/span>\u00a0w postaci danych o plonach, zdj\u0119\u0107 satelitarnych i \u017cyzno\u015bci gleby, aby wymieni\u0107 tylko niekt\u00f3re.<\/p>\r\n

Brak \u0142atwych w u\u017cyciu zestaw\u00f3w narz\u0119dzi do precyzyjnego oprogramowania w chmurze, kt\u00f3re pomaga\u0142yby producentom upraw przekszta\u0142ca\u0107 warstwy danych terenowych w u\u017cyteczn\u0105 wiedz\u0119 i praktyczne zalecenia, ogranicza zastosowanie precyzyjnych technologii rolniczych.<\/p>\r\n

W rolnictwie precyzyjnym strefy zarz\u0105dzania to obszary na polu o podobnym potencjale plonowania, w zale\u017cno\u015bci od rodzaju gleby, po\u0142o\u017cenia nachylenia, sk\u0142adu chemicznego gleby, mikroklimatu i\/lub innych czynnik\u00f3w wp\u0142ywaj\u0105cych na produkcj\u0119 ro\u015blinn\u0105.<\/p>\r\n

Ten\u00a0wiedza producenta na dany temat<\/span>\u00a0jest bardzo wa\u017cnym elementem procesu. Strefy zarz\u0105dzania s\u0105 postrzegane jako mechanizm optymalizacji nak\u0142ad\u00f3w uprawowych i potencja\u0142u plonowania.<\/p>\r\n\t\t

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\"Mapa<\/figure><\/div>
\"Po\u0142\u0105czona<\/figure><\/div>
\"Po\u0142\u0105czona<\/figure><\/div>
\"Po\u0142\u0105czona<\/figure><\/div>
\"Skorygowana<\/figure><\/div>
\"mapa<\/figure><\/div>
\"po\u0142\u0105czona<\/figure><\/div>
\"mapy<\/figure><\/div>
\"Po\u0142\u0105czona<\/figure><\/div>
\"\u0142\u0105cznie<\/figure><\/div>\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t
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<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\r\n

\r\n\r\n<\/p>\r\n

Mapy wygenerowane przy u\u017cyciu jednej i kilku warstw danych.<\/em><\/p>\r\n

Najwi\u0119kszym wyzwaniem jest stworzenie stref zarz\u0105dzania, kt\u00f3re idealnie odzwierciedlaj\u0105 zmienno\u015b\u0107 pola. Po\u0142\u0105czenie r\u00f3\u017cnych warstw, takich jak zdj\u0119cia satelitarne, dane o \u017cyzno\u015bci gleby, dane topograficzne i dane z monitoringu plon\u00f3w, to kolejny logiczny krok w kierunku generowania\u2026 bardziej responsywne strefy zarz\u0105dzania<\/span>.<\/p>\r\n\r\n\r\n\r\n

Analityka wielowarstwowa (znana r\u00f3wnie\u017c jako zintegrowana analiza<\/span>) staje si\u0119 cz\u0119\u015bci\u0105 modu\u0142u geoprzestrzennej analityki GeoPard.<\/p>\r\n\r\n\r\n\r\n

Klasyczne kombinacje parametr\u00f3w zintegrowanej analizy obejmuj\u0105 jedne lub wi\u0119cej danych dotycz\u0105cych plon\u00f3w, map\u0119 NDVI, wysoko\u015b\u0107 oraz fizykochemiczne charakterystyki czujnika glebowego.\u00a0<\/p>\r\n

GeoPard obs\u0142uguje te parametry i dodatkowo umo\u017cliwia uwzgl\u0119dnienie innych warstw danych terenowych, kt\u00f3re s\u0105 ju\u017c dost\u0119pne w systemie lub zosta\u0142y przes\u0142ane bezpo\u015brednio przez u\u017cytkownika (pr\u00f3bkowanie gleby, zbiory danych o plonach itp.).<\/p>\r\n

Dzi\u0119ki temu mo\u017cesz swobodnie korzysta\u0107 z\u00a0kompletny zestaw parametr\u00f3w<\/span>\u00a0przeprowadzanie zintegrowanej analityki:<\/p>\r\n\r\n\r\n\r\n

Wielowarstwowa analiza danych o wydajno\u015bci<\/strong><\/p>\r\n

Dane teledetekcyjne:<\/p>\r\n

    \r\n
  • Mapa potencjalnej produktywno\u015bci (jednoroczna i wieloletnia)<\/li>\r\n
  • Mapa stabilno\u015bci\/zmienno\u015bci<\/li>\r\n
  • Wska\u017aniki ro\u015blinno\u015bci NDVI, EVI2, WDRVI, LAI, SAVI, OSAVI, GCI, GNDVI<\/li>\r\n<\/ul>\r\n

    Topografia:<\/p>\r\n

      \r\n
    • Cyfrowy poziom terenu<\/li>\r\n
    • Nachylenie<\/li>\r\n
    • Krzywizna<\/li>\r\n
    • Wska\u017anik wilgotno\u015bci<\/li>\r\n
    • Odcienie wzg\u00f3rz<\/li>\r\n<\/ul>\r\n

      Dane glebowe:<\/p>\r\n

        \r\n
      • pH<\/li>\r\n
      • CEC (zdolno\u015b\u0107 wymiany kation\u00f3w)<\/li>\r\n
      • SOM (materia organiczna gleby)<\/li>\r\n
      • K (potas)<\/li>\r\n
      • Niska grubo\u015b\u0107 wierzchniej warstwy gleby, mniejsza dost\u0119pna pojemno\u015b\u0107 wodna (gleba podatna na susz\u0119)<\/li>\r\n
      • EC (przewodno\u015b\u0107 elektryczna)<\/li>\r\n
      • i inne atrybuty chemiczne dost\u0119pne w przes\u0142anym zestawie danych<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n

        Wa\u017cne jest podkre\u015blenie, \u017ce czynniki niestandardowe s\u0105 konfigurowane na ka\u017cdej warstwie danych w celu przypisania \u017c\u0105danych\u00a0waga warstwy<\/span>.Zach\u0119camy do dzielenia si\u0119 przypadkami u\u017cycia zintegrowanej analityki i tworzenia map stref zarz\u0105dzania w oparciu o wiedz\u0119 terenow\u0105, przy jednoczesnym doborze \u017ar\u00f3de\u0142 danych i ich wag w GeoPard.<\/p>\r\n\r\n\r\n\r\n

        Zdj\u0119cia w tym blogu przedstawiaj\u0105 przyk\u0142adowe pole z warstwami danych (takimi jak mapa produktywno\u015bci obejmuj\u0105ca 18 lat, numeryczny model terenu, nachylenie, cieniowanie, dane dotycz\u0105ce plon\u00f3w z 2019 r.) oraz r\u00f3\u017cne kombinacje map analityki integracyjnej.\u00a0<\/p>\r\n

        Mo\u017cna \u015bledzi\u0107 kroki ewolucji stref zarz\u0105dzania, rozszerzaj\u0105c jednocze\u015bnie analiz\u0119 integracyjn\u0105 o dodatkow\u0105 warstw\u0119 danych.<\/p>\r\n

        \r\n

        Cz\u0119sto zadawane pytania<\/h2>\r\n
        \r\n

        1. Czym s\u0105 warstwy danych?<\/strong><\/p>\r\n

        Warstwy danych odnosz\u0105 si\u0119 do pojedynczych komponent\u00f3w lub element\u00f3w danych, kt\u00f3re s\u0105 zorganizowane i u\u0142o\u017cone razem w celu utworzenia kompleksowej reprezentacji okre\u015blonego obszaru lub tematu.<\/p>\r\n

        Ka\u017cda warstwa reprezentuje okre\u015blony aspekt danych, taki jak cechy geograficzne, u\u017cytkowanie grunt\u00f3w, g\u0119sto\u015b\u0107 zaludnienia czy czynniki \u015brodowiskowe. Warstwy te mo\u017cna \u0142\u0105czy\u0107 i analizowa\u0107 zbiorczo, aby uzyska\u0107 wgl\u0105d, wizualizowa\u0107 wzorce i podejmowa\u0107 \u015bwiadome decyzje.<\/p>\r\n

        Warstwy danych s\u0105 powszechnie stosowane w systemach informacji geograficznej (GIS) i analizie przestrzennej w celu lepszego zrozumienia i przedstawienia z\u0142o\u017conych danych w spos\u00f3b wizualny i interpretowalny.<\/p>\r\n

        2. Czym jest analiza zintegrowana?<\/strong><\/p>\r\n

        Analiza zintegrowana odnosi si\u0119 do procesu \u0142\u0105czenia i analizowania danych z wielu \u017ar\u00f3de\u0142 lub dyscyplin w celu uzyskania bardziej wszechstronnego i holistycznego zrozumienia konkretnego problemu lub zjawiska.<\/p>\r\n

        Polega ona na scalaniu zestaw\u00f3w danych, stosowaniu technik statystycznych i badaniu zale\u017cno\u015bci pomi\u0119dzy r\u00f3\u017cnymi zmiennymi lub domenami.<\/p>\r\n

        Zintegrowana analiza pozwala na uzyskanie bardziej niuansowego i powi\u0105zanego obrazu z\u0142o\u017conych system\u00f3w, u\u0142atwiaj\u0105c identyfikacj\u0119 wzorc\u00f3w, trend\u00f3w i zwi\u0105zk\u00f3w przyczynowo-skutkowych, kt\u00f3re mog\u0142yby nie by\u0107 oczywiste w przypadku analizy danych w izolacji.<\/p>\r\n

        Dzi\u0119ki takiemu podej\u015bciu badacze i decydenci mog\u0105 podejmowa\u0107 bardziej \u015bwiadome i skuteczne decyzje w oparciu o szerszy zakres informacji.<\/p>","protected":false},"excerpt":{"rendered":"

        Rolnictwo precyzyjne jest w stanie generowa\u0107 ogromne ilo\u015bci danych, mi\u0119dzy innymi w postaci danych o plonach, zdj\u0119\u0107 satelitarnych i \u017cyzno\u015bci gleby. Brak \u0142atwych w u\u017cyciu rozwi\u0105za\u0144 chmurowych\u2026<\/p>","protected":false},"author":210157960,"featured_media":1331,"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":[1657,1366,1368],"tags":[1598],"class_list":["post-1195","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-precision-farming","category-topography","category-yield","tag-precision-agriculture"],"acf":[],"yoast_head":"\nIntegrated analysis for agribusiness<\/title>\n<meta name=\"description\" content=\"Multi layer yield data analytics (also known as integrated analysis) is becoming a part of the GeoPard geospatial analytics engine.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/geopard.tech\/pl\/blog\/analityka-wielowarstwowa\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Integrated analysis for agribusiness\" \/>\n<meta property=\"og:description\" content=\"Multi layer yield data analytics (also known as integrated analysis) is becoming a part of the GeoPard geospatial analytics engine.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/geopard.tech\/pl\/blog\/analityka-wielowarstwowa\/\" \/>\n<meta property=\"og:site_name\" content=\"GeoPard - 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