{"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":"koristenje-izrezanih-rasterskih-podataka-za-agrobiznis","status":"publish","type":"post","link":"https:\/\/geopard.tech\/hr\/blog\/use-of-cropped-raster-data-for-agribusiness\/","title":{"rendered":"Upotreba obrezanih rasterskih podataka za poljoprivredno poslovanje"},"content":{"rendered":"

Obrezani rasterski podaci temeljeni na granicama polja zvu\u010de vrlo jednostavno. Neki izvori podataka su rasterske slike s pikselima i rezolucijom od 3m\/10m\/30m, drugi su vektori s poligonima ili multipoligonima.<\/p>\r\n\r\n\r\n\t\t

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\"WDRVI<\/figure><\/div>
\"Blisko-infracrvena<\/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

To\u010dna granica obra\u0111enih rasterskih podataka je \u0161kakljiva. Zadani izlaz koji ve\u0107ina GIS i softvera za preciznu poljoprivredu ima je pikselizirani raster. Precizna evaluacija podataka blizu granice polja poma\u017ee vam bolje razumjeti, na primjer, stanje kro\u0161anja, vrijednost nagiba.\u00a0<\/p>\r\n\r\n\r\n\r\n

Primjeri pikseliziranih rasterskih slika:<\/p>\r\n\r\n\r\n\r\n

\"Blisko\r\n
Blisko infracrveni pikselizirani raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
\"Nadmorska\r\n
Nadmorska visina pikselizirani raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

Je li mogu\u0107e pobolj\u0161ati i u\u010diniti ga to\u010dnijim?<\/p>\r\n\r\n\r\n\r\n

Da, GeoPard to radi i \u010dak pru\u017ea podatke za daljnju integraciju putem API-ja. Nekoliko primjera:<\/p>\r\n\r\n\r\n\r\n

    \r\n
  • Isek s sirovih (pogledi crveno-zeleno-plavo i bliskog infracrvenog zra\u010denja) satelitskih snimaka na temelju granice parcele:<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n
    \"RGB\r\n
    GeoPard Agriculture RGB izrezani raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
    \"Bliski\r\n
    GeoPard Agriculture Bliski infracrveni usjevni raster<\/em><\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

     <\/p>\r\n

      \r\n
    • Izrez satelitske snimke s indeksom vegetacije poput WDRVI temeljen na granicama parcele:<\/li>\r\n<\/ul>\r\n

       <\/p>\r\n\r\n\r\n\r\n

      \"WDRVI\r\n
      GeoPard Poljoprivreda WDRVI izrezani raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

       <\/p>\r\n

        \r\n
      • Urez digitalnog topografskog skupa podataka (nadmorska visina i hrapavost) na temelju granice parcele:<\/li>\r\n<\/ul>\r\n

         <\/p>\r\n\r\n\r\n\r\n

        \"Podizanje\r\n
        GeoPard Agriculture Nadmorska visina usitnjeno rasterski<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
        \"Hrapavost\r\n
        GeoPard Agriculture Hrapavost izrezani raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n

        Kako to izgleda u GeoPard su\u010delju i kako se mo\u017ee integrirati u va\u0161e agrotehnolo\u0161ko rje\u0161enje:<\/p>\r\n\r\n\r\n\r\n

        \"GeoPard\r\n
        GeoPard Poljoprivreda NIR izrezana raster<\/em><\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n
        \"GeoPard\r\n
        GeoPard Poljoprivredno Olak\u0161anje Polo\u017eaj<\/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

        U GeoPardu razumijemo vrijednost takvih detalja i neprestano radimo na pobolj\u0161anju rje\u0161enja.<\/p>\r\n

        \u0160to je rasterski podatak?<\/h2>\r\n

        Rasterski podaci su vrsta podataka digitalne slike koja je predstavljena mre\u017eom piksela ili \u0107elija, gdje svaka \u0107elija odgovara odre\u0111enoj lokaciji na Zemljinoj povr\u0161ini. Svakom pikselu u rasterskoj slici dodijeljena je vrijednost koja predstavlja odre\u0111eni atribut ili karakteristiku te lokacije, kao \u0161to su nadmorska visina, temperatura ili pokrovnost tla.<\/p>\r\n

        \u010cesto se koristi u geografskim informacijskim sustavima (GIS) i primjenama daljinskih istra\u017eivanja za predstavljanje i analizu raznih vrsta prostornih podataka. Mo\u017ee se prikupljati iz razli\u010ditih izvora, uklju\u010duju\u0107i satelitske i zra\u010dne snimke, digitalne kamere i senzore temeljene na zemlji.<\/p>\r\n

        \u010cesto se pohranjuje u raznim formatima, kao \u0161to su GeoTIFF, JPEG i PNG, koji su dizajnirani za u\u010dinkovito komprimiranje i pohranu podataka. GIS softver i alati za obradu slika mogu se koristiti za manipulaciju i analizu podataka, na primjer izvo\u0111enjem izra\u010duna na vrijednostima piksela ili primjenom filtara za pobolj\u0161anje odre\u0111enih zna\u010dajki.<\/p>\r\n

        Primjeri primjene uklju\u010duju mapiranje kori\u0161tenja i pokrivenosti zemlji\u0161ta, analizu promjena u vegetaciji tijekom vremena te predvi\u0111anje prinosa usjeva na temelju okoli\u0161nih \u010dimbenika.<\/p>\r\n

        Kako se rasterski podaci koriste u preciznom poljoprivredi?<\/h2>\r\n

        Klju\u010dna je komponenta preciznog poljodjelstva, jer pru\u017ea detaljne informacije o zdravlju usjeva, svojstvima tla i \u010dimbenicima okoli\u0161a koji se mogu koristiti za dono\u0161enje informiranijih odluka o upravljanju usjevima. Evo nekoliko primjera kako se rasterski podaci koriste u preciznom poljodjelstvu:<\/p>\r\n

          \r\n
        • Analiza zdravlja usjeva:<\/strong> Podatci daljinskih istra\u017eivanja u obliku satelitskih snimaka ili snimaka iz bespilotnih letjelica mogu se koristiti za generiranje slojeva podataka koji prikazuju indekse vegetacije kao \u0161to su NDVI (Normalizirani razdijeljeni indeks vegetacije) ili NDRE (Normalizirani razdijeljeni indeks crvenog ruba). Ovi indeksi poma\u017eu u identificiranju podru\u010dja polja sa zdravom vegetacijom, kao i podru\u010dja gdje usjevi mogu biti pod stresom zbog bolesti, \u0161tetnika ili nedostatka hranjivih tvari.<\/li>\r\n
        • Analiza tla:<\/strong> Podaci o tlu, kao \u0161to su sadr\u017eaj vlage ili tekstura tla, mogu se prikupljati pomo\u0107u senzora koji generiraju podatkovne slojeve. Ti slojevi mogu pomo\u0107i u identificiranju podru\u010dja polja s razli\u010ditim karakteristikama tla, \u0161to mo\u017ee poslu\u017eiti kao osnova za dono\u0161enje odluka o gnojidbi, navodnjavanju i drugim praksama upravljanja tlom.<\/li>\r\n
        • Analiza okoli\u0161a:<\/strong> Slojevi podataka koji prikazuju faktore okoli\u0161a poput temperature, oborina i brzine vjetra mogu se koristiti za modeliranje rasta usjeva i predvi\u0111anje prinosa. Ovi slojevi tako\u0111er mogu pomo\u0107i u identificiranju podru\u010dja polja koja su sklona eroziji, poplavama ili drugim ekolo\u0161kim problemima.<\/li>\r\n
        • Primjena promjenjivom brzinom:<\/strong> Mo\u017ee se koristiti za generiranje receptnih karata za primjenu unosa poput gnojiva ili pesticida promjenjivim normama. Primjenom unosa promjenjivim normama prema potrebama razli\u010ditih dijelova polja, poljoprivrednici mogu smanjiti otpad i optimizirati rast usjeva.<\/li>\r\n<\/ul>\r\n

          Sveukupno, rasterski podaci su klju\u010dni alat u preciznoj poljoprivredi, jer pru\u017eaju detaljne informacije o stanju usjeva i tla koje se mogu koristiti za dono\u0161enje informiranijih odluka o upravljanju usjevima.<\/p>","protected":false},"excerpt":{"rendered":"

          Izrezani rasterski podaci na temelju granice polja zvu\u010de vrlo jednostavno. Neki izvori podataka su rasteri s pikselima i rezolucijom od 3m\/10m\/30m, drugi - su...<\/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_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 Agriculture<\/title>\n<meta name=\"description\" content=\"Cropped raster data based on field boundary sounds very simple. 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