{"id":286,"date":"2021-01-18T17:57:00","date_gmt":"2021-01-18T16:57:00","guid":{"rendered":"https:\/\/geopard.tech\/?p=286"},"modified":"2024-12-01T21:40:34","modified_gmt":"2024-12-01T20:40:34","slug":"karbitud-rasterandmete-kasutamine-pollumajanduses","status":"publish","type":"post","link":"https:\/\/geopard.tech\/est\/blog\/use-of-cropped-raster-data-for-agribusiness\/","title":{"rendered":"K\u00e4rbitud rasterandmete kasutamine p\u00f5llumajanduses"},"content":{"rendered":"

P\u00f5llupiiridel p\u00f5hinevad k\u00e4rbitud rasterandmed k\u00f5lavad v\u00e4ga lihtsalt. M\u00f5ned andmeallikad on pikslitega rasterid resolutsiooniga 3m\/10m\/30m, teised aga hulknurkade v\u00f5i multihulknurkadega vektorid.<\/p>\r\n\r\n\r\n\t\t

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\"WDRVI<\/figure><\/div>
\"L\u00e4hiinfrapuna<\/figure><\/div>\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t<\/path><\/svg>\t\t\t\t\t<\/div>\n\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\n\r\n\r\n\r\n

K\u00e4rbitud rasterandmete t\u00e4pse piiri leidmine on keeruline. Enamiku GIS- ja t\u00e4ppisp\u00f5llumajanduse tarkvarade vaikev\u00e4ljund on pikslitega raster. P\u00f5llupiiri l\u00e4hedal asuv t\u00e4pne andmete hindamine aitab paremini m\u00f5ista n\u00e4iteks v\u00f5ra tingimusi ja kallet.\u00a0<\/p>\r\n\r\n\r\n\r\n

Pikseldatud rastri n\u00e4ited:<\/p>\r\n\r\n\r\n\r\n

\"L\u00e4hiinfrapuna\r\n
L\u00e4hiinfrapuna pikseldatud raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
\"Pikseldatud\r\n
Pikseldatud k\u00f5rgusraster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

Kas seda on v\u00f5imalik paremaks muuta ja t\u00e4psemaks muuta?<\/p>\r\n\r\n\r\n\r\n

Jah, GeoPard teeb seda ja teeb andmed API kaudu isegi edasiseks integreerimiseks k\u00e4ttesaadavaks. M\u00f5ned n\u00e4ited:<\/p>\r\n\r\n\r\n\r\n

    \r\n
  • P\u00f5llupiiril p\u00f5hinevate satelliidipiltide (punane, roheline, sinine ja l\u00e4hiinfrapunavaated) k\u00e4rpimine:<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n
    \"RGB\r\n
    GeoPard Agriculture RGB k\u00e4rbitud raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
    \"L\u00e4hiinfrapuna\r\n
    GeoPard Agriculture L\u00e4hiinfrapuna k\u00e4rbitud raster<\/em><\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

     <\/p>\r\n

      \r\n
    • Satelliidipiltide k\u00e4rpimine koos taimestikuindeksiga, n\u00e4iteks WDRVI-ga, mis p\u00f5hineb p\u00f5llu piiril:<\/li>\r\n<\/ul>\r\n

       <\/p>\r\n\r\n\r\n\r\n

      \"WDRVI\r\n
      GeoPard Agriculture WDRVI k\u00e4rbitud raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

       <\/p>\r\n

        \r\n
      • Digitaalse topograafilise andmestiku k\u00e4rpimine (k\u00f5rgus ja karedus) p\u00f5llupiiri p\u00f5hjal:<\/li>\r\n<\/ul>\r\n

         <\/p>\r\n\r\n\r\n\r\n

        \"K\u00f5rguse\r\n
        GeoPard Agriculture'i k\u00e4rbitud raster k\u00f5rguste kohta<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
        \"Karedusest\r\n
        GeoPard Agriculture'i karedus k\u00e4rbitud raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

        Kuidas see GeoPardi liideses v\u00e4lja n\u00e4eb ja kuidas seda saab teie p\u00f5llumajandustehnoloogia lahendusse integreerida:<\/p>\r\n\r\n\r\n\r\n

        \"GeoPard\r\n
        GeoPard Agriculture'i NIR-k\u00e4rbitud raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
        \"GeoPardi\r\n
        GeoPardi p\u00f5llumajanduse abipositsioon<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
        \"GeoPard\r\n
        GeoPard Agriculture WDRVI<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

        Meie GeoPardis m\u00f5istame selliste detailide v\u00e4\u00e4rtust ja t\u00f6\u00f6tame pidevalt lahenduse t\u00e4iustamise nimel.<\/p>\r\n

        Mis on rasterandmed?<\/h2>\r\n

        Rasterandmed on digitaalsete piltide andmet\u00fc\u00fcp, mida esitatakse pikslite v\u00f5i lahtrite ruudustikuna, kus iga lahter vastab kindlale asukohale Maa pinnal. Igale rasterpildi pikslile on m\u00e4\u00e4ratud v\u00e4\u00e4rtus, mis esindab selle asukoha konkreetset atribuuti v\u00f5i karakteristikut, n\u00e4iteks k\u00f5rgust, temperatuuri v\u00f5i maakatet.<\/p>\r\n

        Seda kasutatakse tavaliselt geograafilistes infos\u00fcsteemides (GIS) ja kaugseire rakendustes erinevat t\u00fc\u00fcpi ruumiandmete esitamiseks ja anal\u00fc\u00fcsimiseks. Seda saab koguda mitmesugustest allikatest, sealhulgas satelliidi- ja \u00f5hupiltidest, digikaameratest ja maapealsetest anduritest.<\/p>\r\n

        Seda salvestatakse sageli erinevates vormingutes, n\u00e4iteks GeoTIFF, JPEG ja PNG, mis on loodud andmete t\u00f5husaks tihendamiseks ja salvestamiseks. GIS-tarkvara ja pildit\u00f6\u00f6tlust\u00f6\u00f6riistu saab kasutada andmete manipuleerimiseks ja anal\u00fc\u00fcsimiseks, n\u00e4iteks piksliv\u00e4\u00e4rtuste arvutuste tegemiseks v\u00f5i filtrite rakendamiseks teatud funktsioonide t\u00e4iustamiseks.<\/p>\r\n

        Rakenduste n\u00e4ideteks on maakasutuse ja maakatte kaardistamine, taimestiku muutuste anal\u00fc\u00fcsimine aja jooksul ning saagikuse ennustamine keskkonnategurite p\u00f5hjal.<\/p>\r\n

        Kuidas kasutatakse rasterandmeid t\u00e4ppisp\u00f5llumajanduses?<\/h2>\r\n

        See on t\u00e4ppisp\u00f5llumajanduse oluline komponent, kuna see annab \u00fcksikasjalikku teavet p\u00f5llukultuuride tervise, mulla omaduste ja keskkonnategurite kohta, mida saab kasutada teadlikumate otsuste tegemiseks p\u00f5llukultuuride majandamise osas. Siin on m\u00f5ned n\u00e4ited rasterandmete kasutamisest t\u00e4ppisp\u00f5llumajanduses:<\/p>\r\n

          \r\n
        • Saagi tervise anal\u00fc\u00fcs:<\/strong> Satelliidipiltide v\u00f5i droonipiltide kujul olevaid kaugseireandmeid saab kasutada selliste andmekihtide genereerimiseks, mis n\u00e4itavad taimestiku indekseid, n\u00e4iteks NDVI (Normalized Difference Vegetation Index) v\u00f5i NDRE (Normalized Difference Red Edge). Need indeksid aitavad tuvastada p\u00f5llu alasid, kus taimestik on terve, samuti alasid, kus p\u00f5llukultuurid v\u00f5ivad olla haiguste, kahjurite v\u00f5i toitainete puuduse t\u00f5ttu stressi all.<\/li>\r\n
        • Pinnase anal\u00fc\u00fcs:<\/strong> Mullaandmeid, n\u00e4iteks mulla niiskusesisaldust v\u00f5i mulla tekstuuri, saab koguda andurite abil, mis genereerivad andmekihte. Need kihid aitavad tuvastada p\u00f5llu alasid, millel on erinevad mullaomadused, mis aitab langetada otsuseid v\u00e4etamise, niisutamise ja muude mullaharimise tavade kohta.<\/li>\r\n
        • Keskkonnaanal\u00fc\u00fcs:<\/strong> Andmekihte, mis n\u00e4itavad keskkonnategureid, nagu temperatuur, sademed ja tuule kiirus, saab kasutada p\u00f5llukultuuride kasvu modelleerimiseks ja saagikuse ennustamiseks. Need kihid aitavad tuvastada ka p\u00f5llu alasid, mis on altid erosioonile, \u00fcleujutustele v\u00f5i muudele keskkonnaprobleemidele.<\/li>\r\n
        • Muutuva normiga pealekandmine:<\/strong> Seda saab kasutada ettekirjutuskaartide loomiseks sisendite, n\u00e4iteks v\u00e4etiste v\u00f5i pestitsiidide, muutuva koguse lisamiseks. Sisendite erineva koguse lisamisega vastavalt p\u00f5llu eri piirkondade vajadustele saavad p\u00f5llumehed v\u00e4hendada j\u00e4\u00e4tmeid ja optimeerida p\u00f5llukultuuride kasvu.<\/li>\r\n<\/ul>\r\n

          \u00dcldiselt on rasterandmed t\u00e4ppisp\u00f5llumajanduses \u00fclioluline t\u00f6\u00f6riist, kuna need annavad \u00fcksikasjalikku teavet p\u00f5llukultuuride ja mulla seisundi kohta, mida saab kasutada teadlikumate otsuste tegemiseks p\u00f5llukultuuride majandamise osas.<\/p>","protected":false},"excerpt":{"rendered":"

          P\u00f5llupiiridel p\u00f5hinevad k\u00e4rbitud rasterandmed k\u00f5lavad v\u00e4ga lihtsalt. M\u00f5ned andmeallikad on pikslitega rasterid resolutsiooniga 3m\/10m\/30m, teised aga\u2026<\/p>","protected":false},"author":210157960,"featured_media":1352,"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":[1377,1366],"tags":[1618],"class_list":["post-286","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-crop-monitoring","category-topography","tag-crop-monitoring"],"acf":[],"yoast_head":"\nUse of Cropped Raster Data for Agribusiness - GeoPard<\/title>\n<meta name=\"description\" content=\"Cropped raster data based on field boundary sounds very simple. 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