{"id":5598,"date":"2022-10-07T14:04:27","date_gmt":"2022-10-07T12:04:27","guid":{"rendered":"https:\/\/geopard.tech\/?p=5598"},"modified":"2023-05-27T19:43:58","modified_gmt":"2023-05-27T17:43:58","slug":"automatizuotos-paseliu-zvalgymo-uzduotys","status":"publish","type":"post","link":"https:\/\/geopard.tech\/lt\/blog\/automated-crop-scouting-tasks\/","title":{"rendered":"Automatizuotas pas\u0117li\u0173 steb\u0117jimas, derinant duomen\u0173 sluoksnius"},"content":{"rendered":"

\"GeoPard\" turime modul\u012f Automati\u0161kai sukurti pas\u0117li\u0173 duomen\u0173 \u017evalgybos zonas <\/strong>naudojant lanks\u010di\u0105 verslo ir agronomin\u0117s logikos konfig\u016bracij\u0105.<\/p>\r\n\r\n\r\n\r\n

Ji leid\u017eia kontroliuoti daugyb\u0119 lauk\u0173 ir atlikti \u017evalgyb\u0105 tik \u012fvykus avarinei situacijai.<\/p>\r\n

Verslo ir (arba) agronomin\u0117 logika gali b\u016bti lanksti. \u0160iame pavyzdyje - u\u017eduotys kuriamos tose vietov\u0117se, kuriose naujausiose palydovin\u0117se nuotraukose matome didelio istorinio lauko potencialo zonas ir ma\u017e\u0105 augmenijos kiek\u012f.<\/p>\r\n

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

Kito naudojimo atvejo pavyzdys: Ma\u017eo derliaus zona (i\u0161 derliaus failo) susikerta su \u017eemo pH zonomis - kad b\u016bt\u0173 galima koreguoti kalki\u0173 derlingumo lyg\u012f.<\/p>\r\n\r\n\r\n\r\n

 <\/p>\r\n\r\n\r\n\r\n

\"Automatizuotos\r\n
Didelio istorinio lauko na\u0161umo zonos susikerta su naujausiu planetos vaizdu, kuriame yra ma\u017ea augmenijos zona -> \u017evalgymo u\u017eduotys automati\u0161kai sukuriamos \"GeoPard\" programoje.<\/figcaption>\r\n<\/figure>\r\n\r\n\r\n\r\n\r\n\r\n

Pas\u0117li\u0173 prekybos bendrov\u0117ms ir duomen\u0173 modeliuotojams istori\u0161kai stabiliausi\u0173 ir didelio derlingumo zon\u0173 sankirta gali b\u016bti geras rodiklis derliaus prognoz\u0117ms ekstrapoliuoti.<\/p>\r\n\r\n\r\n\r\n

Jei esate \u016bkininkas, agronomas ar tiksliosios \u017eemdirbyst\u0117s specialistas, \u017einote, kokia svarbi yra pas\u0117li\u0173 duomen\u0173 \u017evalgyba. Ji labai svarbi stebint pas\u0117li\u0173 b\u016bkl\u0119 ir nustatant bet kokias galimas problemas, kol jos netapo didel\u0117mis.<\/p>\r\n

Ta\u010diau tradicin\u0117 pas\u0117li\u0173 \u017evalgyba gali pareikalauti daug laiko ir darbo s\u0105naud\u0173. \u0160tai kur ateina automatizuotos \u017evalgybos u\u017eduotys.<\/p>\r\n\r\n\r\n\r\n

\"GeoPard\" yra revoliucin\u0117 automatizuota tiksliosios \u017eemdirbyst\u0117s programin\u0117 \u012franga, kuri naudoja pa\u017eangius algoritmus ir palydovinius vaizdus, kad automati\u0161kai steb\u0117t\u0173 j\u016bs\u0173 pas\u0117lius. Naudodamiesi \"GeoPard\" galite lengvai nustatyti automatines \u017evalgymo u\u017eduotis, kurios \u012fsp\u0117s jus apie galimas problemas, pavyzd\u017eiui, kenk\u0117jus, ligas ar maistini\u0173 med\u017eiag\u0173 tr\u016bkum\u0105.<\/p>\r\n\r\n\r\n\r\n

Vienas i\u0161 pagrindini\u0173 automatin\u0117s \u017evalgybos u\u017eduo\u010di\u0173 privalum\u0173 - galimyb\u0117 greitai ir tiksliai nustatyti pas\u0117li\u0173 problemas. Programa \"GeoPard\" naudoja pa\u017eangius algoritmus, kad i\u0161analizuot\u0173 j\u016bs\u0173 lauk\u0173 palydovines nuotraukas ir aptikt\u0173 net ma\u017eiausius pas\u0117li\u0173 poky\u010dius.<\/p>\r\n

Tai rei\u0161kia, kad galite greitai nustatyti visas galimas problemas ir imtis veiksm\u0173 joms spr\u0119sti, kol jos netapo rimtesn\u0117s.<\/p>\r\n\r\n\r\n\r\n

Dar vienas automatin\u0117s \u017evalgybos u\u017eduo\u010di\u0173 privalumas - galimyb\u0117 reguliariai steb\u0117ti pas\u0117lius. Atliekant tradicin\u0119 \u017evalgyb\u0105, gali b\u016bti sunku reguliariai lankytis laukuose ir tikrinti galimas problemas.<\/p>\r\n

Ta\u010diau naudodami program\u0105 \"GeoPard\" galite nustatyti automatines u\u017eduotis, kurios kasdien arba kas savait\u0119 steb\u0117s j\u016bs\u0173 pas\u0117lius ir suteiks i\u0161samesn\u012f j\u0173 b\u016bkl\u0117s vaizd\u0105.<\/p>\r\n\r\n\r\n\r\n

\"GeoPard\" automatin\u0117s \u017evalgybos u\u017eduotys taip pat gali b\u016bti pritaikomos, tod\u0117l galite jas pritaikyti pagal savo konkre\u010dius poreikius. Galite nustatyti u\u017eduotis, skirtas konkre\u010dioms problemoms, pavyzd\u017eiui, kenk\u0117jams ar ligoms, steb\u0117ti, arba nustatyti u\u017eduotis, skirtas konkre\u010dioms lauko sritims steb\u0117ti. Tai rei\u0161kia, kad galite gauti informacij\u0105, kurios jums reikia, kad gal\u0117tum\u0117te priimti pagr\u012fstus sprendimus d\u0117l savo pas\u0117li\u0173.<\/p>\r\n\r\n\r\n\r\n

\"GeoPard\" si\u016blo ne tik automatizuotas \u017evalgymo u\u017eduotis, bet ir daugyb\u0119 kit\u0173 funkcij\u0173, kurios gali pad\u0117ti valdyti tiksliosios \u017eemdirbyst\u0117s operacijas. Naudodamiesi GeoPard galite planuoti s\u0117j\u0105 ir tr\u0119\u0161im\u0105, steb\u0117ti dirvo\u017eemio dr\u0117gm\u0117s lyg\u012f ir steb\u0117ti derli\u0173.<\/p>\r\n\r\n\r\n\r\n

Apskritai \"GeoPard\" automatizuotos \u017evalgymo u\u017eduotys yra galingas \u012frankis \u016bkininkams, agronomams ir tiksliosios \u017eemdirbyst\u0117s specialistams. Naudodami \"GeoPard\" galite greitai ir lengvai steb\u0117ti savo pas\u0117lius ir nustatyti galimas problemas, o tai padeda priimti geresnius sprendimus d\u0117l savo veiklos.<\/p>\r\n

Kas yra pas\u0117li\u0173 \u017evalgyba?<\/h2>\r\n

Pas\u0117li\u0173 \u017evalgyba - tai \u017eem\u0117s \u016bkio praktika, kai sistemingai tikrinami ir stebimi pas\u0117liai, siekiant \u012fvertinti j\u0173 sveikat\u0105, augim\u0105 ir galimas problemas. Paprastai fizi\u0161kai vaik\u0161toma po laukus arba duomenims rinkti naudojamos tokios technologijos kaip dronai ar jutikliai.<\/p>\r\n

Pas\u0117li\u0173 \u017evalgai stebi ir renka informacij\u0105 apie tokius veiksnius kaip kenk\u0117j\u0173 antpl\u016bdis, lig\u0173 protr\u016bkiai, maistini\u0173 med\u017eiag\u0173 tr\u016bkumas ir pikt\u017eoli\u0173 plitimas.<\/p>\r\n

\u0160ie duomenys padeda \u016bkininkams priimti pagr\u012fstus sprendimus, susijusius su pas\u0117li\u0173 valdymu, pvz., taikyti tikslin\u012f apdorojim\u0105, koreguoti tr\u0105\u0161\u0173 naudojim\u0105 arba \u012fgyvendinti kenk\u0117j\u0173 kontrol\u0117s strategijas. Tai labai svarbu siekiant padidinti derli\u0173 ir u\u017etikrinti bendr\u0105 pas\u0117li\u0173 b\u016bkl\u0119.<\/p>\r\n\r\n\r\n\r\n

Kas yra automatin\u0117 pas\u0117li\u0173 duomen\u0173 \u017evalgyba?<\/h2>\r\n

Automatizuota pas\u0117li\u0173 \u017evalgyba - tai pa\u017eangiausi\u0173 technologij\u0173, \u012fskaitant robotik\u0105, bepilotes skraidykles, \u012fvairius jutiklius ir dirbtin\u012f intelekt\u0105, taikymas siekiant steb\u0117ti ir vertinti pas\u0117li\u0173 b\u016bkl\u0119 ir vystym\u0105si \u017eem\u0117s \u016bkio aplinkoje.<\/p>\r\n

Tikslas - padidinti efektyvum\u0105, suma\u017einti i\u0161laidas ir supaprastinti pas\u0117li\u0173 valdym\u0105, automatizuojant u\u017eduotis, kurias tradici\u0161kai atlieka \u017emon\u0117s - pas\u0117li\u0173 \u017evalgai.<\/p>\r\n

Automatizuotos pas\u0117li\u0173 duomen\u0173 \u017evalgybos procesas apima kelis etapus, pvz:<\/p>\r\n

    \r\n
  • Duomen\u0173 rinkimas:<\/strong> Bepilo\u010diai orlaiviai arba ant\u017eeminiai robotai su \u012fvairiais jutikliais (pvz., kameromis, daugiaspektriais jutikliais, LIDAR) renka informacij\u0105 apie pas\u0117li\u0173 b\u016bkl\u0119, \u012fskaitant augal\u0173 sveikat\u0105, kenk\u0117j\u0173 ir lig\u0173 paplitim\u0105, dirvo\u017eemio savybes ir maistini\u0173 med\u017eiag\u0173 koncentracij\u0105.<\/li>\r\n
  • Duomen\u0173 analiz\u0117<\/strong>: V\u0117liau surinkti duomenys apdorojami ir tikrinami naudojant dirbtinio intelekto ir ma\u0161ininio mokymosi algoritmus, kad b\u016bt\u0173 galima aptikti su pas\u0117li\u0173 sveikata ir vystymusi susijusius d\u0117sningumus, pa\u017eeidimus ir tendencijas.<\/li>\r\n
  • Sprendim\u0173 pri\u0117mimas:<\/strong> Duomen\u0173 analiz\u0117s rezultatai gali b\u016bti naudojami priimant pagr\u012fstus sprendimus d\u0117l pas\u0117li\u0173 valdymo, \u012fskaitant laistymo, tr\u0119\u0161imo, kenk\u0117j\u0173 kontrol\u0117s ir kit\u0173 intervencini\u0173 priemoni\u0173 optimizavim\u0105.<\/li>\r\n
  • Imkit\u0117s veiksm\u0173:<\/strong> \u016akininkai, remdamiesi automatin\u0117s pas\u0117li\u0173 steb\u0117senos metu gautomis \u017einiomis, gali \u012fgyvendinti tikslines priemones, skirtas konkre\u010dioms lauko problemoms spr\u0119sti, pavyzd\u017eiui, naudoti pesticidus ar maisting\u0105sias med\u017eiagas tik ten, kur reikia, taip suma\u017einant atliek\u0173 kiek\u012f ir poveik\u012f aplinkai.<\/li>\r\n<\/ul>\r\n

    \u016akininkams realiuoju laiku teikiant tikslius duomenis, galima gerokai padidinti \u017eem\u0117s \u016bkio produktyvum\u0105 ir tvarum\u0105, priimti geresnius sprendimus ir taikyti tikslesnius valdymo metodus.<\/p>\r\n\r\n\r\n\r\n

    Kaip nustatyti \u017evalgybos zon\u0105?<\/h2>\r\n

    Nustatant pas\u0117li\u0173 duomen\u0173 \u017evalgybos zonas, \u016bkio laukas padalijamas \u012f ma\u017eesnes, lengvai valdomas dalis, atsi\u017evelgiant \u012f tokius aspektus kaip dirvo\u017eemio sud\u0117tis, reljefas, ankstesni pas\u0117li\u0173 rezultatai ar kiti svarb\u016bs veiksniai.<\/p>\r\n

    Tikslas - nustatyti vienodas pana\u0161ias s\u0105lygas atitinkan\u010dias teritorijas, kad b\u016bt\u0173 galima tikslingiau atlikti \u017evalgyb\u0105, steb\u0117jimus ir valdymo praktik\u0105. Toliau pateikiamas \u017eingsnis po \u017eingsnio metodas, kaip nustatyti pas\u0117li\u0173 \u017evalgymo zon\u0105:<\/p>\r\n

      \r\n
    • Surinkite istorin\u0119 informacij\u0105:<\/strong> Surinkite duomenis apie ankstesni\u0173 pas\u0117li\u0173 derli\u0173, dirvo\u017eemio analiz\u0117s rezultatus, kenk\u0117jus ir ligas bei kit\u0105 svarbi\u0105 informacij\u0105 apie lauk\u0105. \u0160ie duomenys gali pad\u0117ti atpa\u017einti vietoves, kuriose yra pana\u0161ios s\u0105lygos ar na\u0161umas.<\/li>\r\n
    • I\u0161nagrin\u0117kite dirvo\u017eemio sud\u0117t\u012f ir reljef\u0105:<\/strong> I\u0161tirkite savo lauko dirvo\u017eemio tipus ir reljef\u0105, kad suprastum\u0117te nat\u016bralius skirtumus. Skirtinga dirvo\u017eemio sud\u0117tis ir auk\u0161tis vir\u0161 j\u016bros lygio gali tur\u0117ti \u012ftakos pas\u0117li\u0173 augimui, maisto med\u017eiag\u0173 \u012fsisavinimui ir vandens prieinamumui, o tai savo ruo\u017etu daro \u012ftak\u0105 pas\u0117li\u0173 sveikatai.<\/li>\r\n
    • Pasinaudokite nuotolinio steb\u0117jimo technologijomis:<\/strong> Naudokite palydovinius arba dronais gautus vaizdus, kad gautum\u0117te papildomos informacijos apie lauko s\u0105lygas, pvz., augmenijos rodiklius, dirvo\u017eemio dr\u0117gm\u0117s lyg\u012f ir temperat\u016bros svyravimus. \u0160i informacija gali pad\u0117ti patikslinti \u017evalgymo zonas, nes suteikia i\u0161samesn\u012f lauko vaizd\u0105.<\/li>\r\n
    • \u012ediegti tiksliosios \u017eemdirbyst\u0117s metodus:<\/strong> Naudokite tiksliosios \u017eemdirbyst\u0117s programin\u0119 \u012frang\u0105 surinktiems duomenims apdoroti ir analizuoti. \u0160ios priemon\u0117s gali pad\u0117ti nustatyti d\u0117sningumus ir nustatyti duomenimis pagr\u012fstas \u017evalgymo sritis, atsi\u017evelgiant \u012f tokius veiksnius kaip pas\u0117li\u0173 sveikata, dirvo\u017eemio kintamumas ir reljefas.<\/li>\r\n
    • Nustatyti \u017evalgybos zonas<\/strong>: Remdamiesi duomen\u0173 analize, suskirstykite lauk\u0105 \u012f ma\u017eesnius vienodus plotus, kuriems b\u016bdingi pana\u0161\u016bs po\u017eymiai. \u0160ie plotai tur\u0117t\u0173 b\u016bti lengvai valdomi ir pritaikyti konkretiems j\u016bs\u0173 veiklos reikalavimams.<\/li>\r\n
    • Reguliariai atnaujinkite ir koreguokite:<\/strong> Pasikeitus aplinkyb\u0117ms ir gavus nauj\u0173 duomen\u0173, i\u0161 naujo \u012fvertinkite ir pakeiskite \u017evalgybos rajonus, kad jie i\u0161likt\u0173 aktual\u016bs ir tiksl\u016bs. Tai gali b\u016bti susij\u0119 su plot\u0173 atnaujinimu, atsi\u017evelgiant \u012f naujus derliaus duomenis, kenk\u0117j\u0173 ir lig\u0173 paplitim\u0105 ar kitus pas\u0117li\u0173 na\u0161umui \u012ftakos turin\u010dius veiksnius.<\/li>\r\n<\/ul>\r\n

      Taigi, nustat\u0119 ir suk\u016br\u0119 pas\u0117li\u0173 \u017evalgymo zon\u0105, \u016bkininkai gali veiksmingiau sutelkti steb\u0117senos pastangas ir taikyti tiksling\u0105 valdymo praktik\u0105, tod\u0117l geriau panaudojami i\u0161tekliai ir pager\u0117ja pas\u0117li\u0173 b\u016bkl\u0117.<\/p>","protected":false},"excerpt":{"rendered":"

      \u201eGeoPard\u201c sistemoje turime modul\u012f, skirt\u0105 automati\u0161kai kurti pas\u0117li\u0173 duomen\u0173 \u017evalgybos zonas, naudojant lanks\u010di\u0105 verslo ir agronomin\u0117s logikos konfig\u016bracij\u0105. Tai leid\u017eia valdyti\u2026<\/p>","protected":false},"author":210157960,"featured_media":5600,"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":[1377,1378,1379,1370,1367,1368],"tags":[1618],"class_list":["post-5598","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-crop-monitoring","category-remote-sensing","category-soil-data","category-scouting","category-use-cases","category-yield","tag-crop-monitoring"],"acf":[],"yoast_head":"\nAutomated Crop Scouting with Intersection of Data Layers - 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