{"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":"flerskiktsanalys","status":"publish","type":"post","link":"https:\/\/geopard.tech\/swe\/blog\/multi-layer-analytics\/","title":{"rendered":"Flerlagers (integrerad) dataanalys inom precisionsjordbruk"},"content":{"rendered":"

Precisionsjordbruk kan generera\u00a0enorma m\u00e4ngder data<\/span>\u00a0i form av avkastningsdata, satellitbilder och jordb\u00f6rdighet, bland annat.<\/p>\r\n

Bristen p\u00e5 l\u00e4ttanv\u00e4nda molnbaserade precisionsprogramvaruverktyg som hj\u00e4lper gr\u00f6doproducenter att omvandla f\u00e4ltdatalager till anv\u00e4ndbar kunskap och handlingsbara rekommendationer begr\u00e4nsar till\u00e4mpningen av precisionsjordbrukstekniker.<\/p>\r\n

Inom precisionsjordbruk \u00e4r sk\u00f6tselzoner omr\u00e5den inom ett f\u00e4lt som har liknande avkastningspotential baserat p\u00e5 jordtyp, lutningsl\u00e4ge, jordkemi, mikroklimat och\/eller andra faktorer som p\u00e5verkar gr\u00f6doproduktionen.<\/p>\r\n

Den\u00a0producentens kunskap inom ett omr\u00e5de<\/span>\u00a0\u00e4r en mycket viktig del av processen. F\u00f6rvaltningszoner ses som en mekanism f\u00f6r att optimera gr\u00f6dor och avkastningspotential.<\/p>\r\n\t\t

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\"18<\/figure><\/div>
\"Kombinerad<\/figure><\/div>
\"Kombinerad<\/figure><\/div>
\"Kombinerad<\/figure><\/div>
\"Korrigerad<\/figure><\/div>
\"zoner<\/figure><\/div>
\"kombinerad<\/figure><\/div>
\"kartor<\/figure><\/div>
\"Kombinerad<\/figure><\/div>
\"kombinerad<\/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

Kartor genererade med ett enda datalager och flera datalager.<\/em><\/p>\r\n

Den stora utmaningen \u00e4r att bygga sk\u00f6tselzoner som perfekt \u00e5terspeglar f\u00e4ltvariationer. En kombination av olika lager som satellitbilder, markb\u00f6rdighet, topografiska derivat och avkastnings\u00f6vervakningsdata \u00e4r n\u00e4sta logiska steg f\u00f6r att generera mer responsiva hanteringszoner<\/span>.<\/p>\r\n\r\n\r\n\r\n

Flerskiktsanalys (\u00e4ven k\u00e4nd som integrerad analys<\/span>) blir en del av GeoPards geospatiala analysmotor.<\/p>\r\n\r\n\r\n\r\n

Klassiska kombinationer av integrerade analysparametrar inkluderar en eller flera avkastningsdata, NDVI-karta, h\u00f6jd och fysikalisk-kemiska egenskaper fr\u00e5n jordsensorer.\u00a0<\/p>\r\n

GeoPard st\u00f6der dessa parametrar och till\u00e5ter dessutom inkludering av andra f\u00e4ltdatalager som antingen redan finns tillg\u00e4ngliga i systemet eller laddas upp direkt av anv\u00e4ndaren (jordprovtagning, avkastningsdataset etc.).<\/p>\r\n

Som ett resultat \u00e4r du fri att arbeta med\u00a0komplett upps\u00e4ttning parametrar<\/span>\u00a0utf\u00f6ra integrerad analys:<\/p>\r\n\r\n\r\n\r\n

Analys av avkastningsdata i flera lager<\/strong><\/p>\r\n

Fj\u00e4rranalysdata:<\/p>\r\n

    \r\n
  • Karta \u00f6ver potentiell produktivitet (enkelt\u00e5r och fler\u00e5r)<\/li>\r\n
  • Stabilitets-\/variationskarta<\/li>\r\n
  • Vegetationsindex NDVI, EVI2, WDRVI, LAI, SAVI, OSAVI, GCI, GNDVI<\/li>\r\n<\/ul>\r\n

    Topografi:<\/p>\r\n

      \r\n
    • Digital h\u00f6jd<\/li>\r\n
    • Sluttning<\/li>\r\n
    • Kr\u00f6kning<\/li>\r\n
    • Fuktindex<\/li>\r\n
    • Kullar<\/li>\r\n<\/ul>\r\n

      Jorddata:<\/p>\r\n

        \r\n
      • pH-v\u00e4rde<\/li>\r\n
      • CEC (katjonbyteskapacitet)<\/li>\r\n
      • SOM (jordorganiskt material)<\/li>\r\n
      • K (kalium)<\/li>\r\n
      • Tunn matjord, l\u00e4gre tillg\u00e4nglig vattenh\u00e5llningskapacitet (torkben\u00e4gen jord)<\/li>\r\n
      • EC (elektrisk ledningsf\u00f6rm\u00e5ga)<\/li>\r\n
      • och andra kemiska attribut som finns tillg\u00e4ngliga i den uppladdade datam\u00e4ngden<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n

        Det \u00e4r viktigt att betona att anpassade faktorer konfigureras ovanp\u00e5 varje datalager f\u00f6r att tilldela \u00f6nskad\u00a0lagervikt<\/span>.Du \u00e4r varmt v\u00e4lkommen att dela med dig av dina anv\u00e4ndningsfall f\u00f6r integrerad analys och bygga kartor \u00f6ver hanteringszoner baserat p\u00e5 din kunskap inom omr\u00e5det n\u00e4r du v\u00e4ljer datak\u00e4llor och deras vikter i GeoPard.<\/p>\r\n\r\n\r\n\r\n

        Bilderna i den h\u00e4r bloggen inneh\u00e5ller ett exempelf\u00e4lt med datalager (som en produktivitetskarta som t\u00e4cker 18 \u00e5r, digital h\u00f6jdmodell, lutning, skugga \u00f6ver kullar, avkastningsdata f\u00f6r 2019) och olika kombinationer av integrationsanalyskartor.\u00a0<\/p>\r\n

        Du kan f\u00f6lja stegen i utvecklingen av hanteringszoner samtidigt som du ut\u00f6kar integrationsanalysen med ett ytterligare datalager.<\/p>\r\n

        \r\n

        Vanliga fr\u00e5gor och svar<\/h2>\r\n
        \r\n

        1. Vad \u00e4r datalager?<\/strong><\/p>\r\n

        Datalager h\u00e4nvisar till de enskilda komponenter eller element i data som \u00e4r organiserade och staplade tillsammans f\u00f6r att skapa en helt\u00e4ckande representation av ett specifikt omr\u00e5de eller \u00e4mne.<\/p>\r\n

        Varje lager representerar en specifik aspekt av informationen, s\u00e5som geografiska s\u00e4rdrag, markanv\u00e4ndning, befolkningst\u00e4thet eller milj\u00f6faktorer. Dessa lager kan kombineras och analyseras gemensamt f\u00f6r att f\u00e5 insikter, visualisera m\u00f6nster och fatta v\u00e4lgrundade beslut.<\/p>\r\n

        Datalager anv\u00e4nds ofta i geografiska informationssystem (GIS) och spatial analys f\u00f6r att b\u00e4ttre f\u00f6rst\u00e5 och representera komplex data p\u00e5 ett visuellt och tolkningsbart s\u00e4tt.<\/p>\r\n

        2. Vad \u00e4r integrerad analys?<\/strong><\/p>\r\n

        Integrerad analys avser processen att kombinera och analysera data fr\u00e5n flera k\u00e4llor eller discipliner f\u00f6r att f\u00e5 en mer omfattande och holistisk f\u00f6rst\u00e5else av ett visst problem eller fenomen.<\/p>\r\n

        Det inneb\u00e4r att sammanfoga datam\u00e4ngder, till\u00e4mpa statistiska tekniker och utforska samband mellan olika variabler eller dom\u00e4ner.<\/p>\r\n

        Integrerad analys m\u00f6jligg\u00f6r en mer nyanserad och sammankopplad syn p\u00e5 komplexa system, vilket underl\u00e4ttar identifieringen av m\u00f6nster, trender och orsakssamband som kanske inte \u00e4r uppenbara n\u00e4r man analyserar data isolerat.<\/p>\r\n

        Denna metod g\u00f6r det m\u00f6jligt f\u00f6r forskare och beslutsfattare att fatta mer v\u00e4lgrundade och effektiva beslut baserat p\u00e5 ett bredare spektrum av information.<\/p>","protected":false},"excerpt":{"rendered":"

        Precisionsjordbruk kan generera stora m\u00e4ngder data i form av avkastningsdata, satellitbilder och jordb\u00f6rdighet, bland annat. Bristen p\u00e5 l\u00e4ttanv\u00e4nda molntj\u00e4nster\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":"","_crdt_document":"","content-type":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","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\/swe\/blogg\/flerskiktsanalys\/\" \/>\n<meta property=\"og:locale\" content=\"sv_SE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Multi layer (integrated) data analysis in precision agriculture\" \/>\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\/swe\/blogg\/flerskiktsanalys\/\" \/>\n<meta property=\"og:site_name\" content=\"GeoPard - 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