{"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":"analyse-multicouche","status":"publish","type":"post","link":"https:\/\/geopard.tech\/fr\/blog\/multi-layer-analytics\/","title":{"rendered":"Analyse de donn\u00e9es multicouches (int\u00e9gr\u00e9es) en agriculture de pr\u00e9cision"},"content":{"rendered":"

L'agriculture de pr\u00e9cision est capable de g\u00e9n\u00e9rer\u00a0de vastes quantit\u00e9s de donn\u00e9es<\/span>\u00a0sous forme de donn\u00e9es sur les rendements, d'images satellites et de donn\u00e9es sur la fertilit\u00e9 des sols, entre autres.<\/p>\r\n

L\u2019absence de kits logiciels de pr\u00e9cision en nuage faciles \u00e0 utiliser qui aident les producteurs agricoles \u00e0 convertir les couches de donn\u00e9es de terrain en connaissances utiles et en recommandations exploitables limite l\u2019application des technologies agricoles de pr\u00e9cision.<\/p>\r\n

En agriculture de pr\u00e9cision, les zones de gestion sont des zones au sein d'un champ qui pr\u00e9sentent un potentiel de rendement similaire en fonction du type de sol, de la pente, de la chimie du sol, du microclimat et\/ou d'autres facteurs influen\u00e7ant la production agricole.<\/p>\r\n

Les\u00a0connaissance du champ par le producteur<\/span>\u00a0Il s'agit d'un \u00e9l\u00e9ment tr\u00e8s important du processus. Les zones de gestion sont consid\u00e9r\u00e9es comme un m\u00e9canisme permettant d'optimiser les intrants agricoles et le potentiel de rendement.<\/p>\r\n\t\t

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\"Carte<\/figure><\/div>
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\"carte<\/figure><\/div>
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\"cartes<\/figure><\/div>
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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

Cartes g\u00e9n\u00e9r\u00e9es avec une seule couche de donn\u00e9es et plusieurs couches de donn\u00e9es.<\/em><\/p>\r\n

Le principal d\u00e9fi consiste \u00e0 d\u00e9finir des zones de gestion qui refl\u00e8tent parfaitement la variabilit\u00e9 des parcelles. La prochaine \u00e9tape logique pour g\u00e9n\u00e9rer ces zones repose sur la combinaison de diff\u00e9rentes couches d'information, telles que l'imagerie satellite, la fertilit\u00e9 des sols, les donn\u00e9es topographiques et les donn\u00e9es de suivi des rendements. zones de gestion plus r\u00e9actives<\/span>.<\/p>\r\n\r\n\r\n\r\n

L'analyse multicouche (\u00e9galement connue sous le nom de analyse int\u00e9gr\u00e9e<\/span>) devient une partie du moteur d'analyse g\u00e9ospatiale GeoPard.<\/p>\r\n\r\n\r\n\r\n

Les combinaisons classiques de param\u00e8tres d'analyse int\u00e9gr\u00e9e comprennent une ou plusieurs donn\u00e9es de rendement, une carte NDVI, l'altitude et les caract\u00e9ristiques physico-chimiques des capteurs de sol.\u00a0<\/p>\r\n

GeoPard prend en charge ces param\u00e8tres et permet en outre l'inclusion d'autres couches de donn\u00e9es de terrain, soit d\u00e9j\u00e0 disponibles dans le syst\u00e8me, soit t\u00e9l\u00e9charg\u00e9es directement par l'utilisateur (\u00e9chantillonnage du sol, jeux de donn\u00e9es de rendement, etc.).<\/p>\r\n

Par cons\u00e9quent, vous \u00eates libre d'utiliser le\u00a0ensemble complet de param\u00e8tres<\/span>\u00a0r\u00e9alisation d'analyses int\u00e9gr\u00e9es\u00a0:<\/p>\r\n\r\n\r\n\r\n

Analyse multicouche des donn\u00e9es de rendement<\/strong><\/p>\r\n

Donn\u00e9es de t\u00e9l\u00e9d\u00e9tection\u00a0:<\/p>\r\n

    \r\n
  • Carte de productivit\u00e9 potentielle (annuelle et pluriannuelle)<\/li>\r\n
  • Carte de stabilit\u00e9\/variation<\/li>\r\n
  • Indices de v\u00e9g\u00e9tation NDVI, EVI2, WDRVI, LAI, SAVI, OSAVI, GCI, GNDVI<\/li>\r\n<\/ul>\r\n

    Topographie:<\/p>\r\n

      \r\n
    • \u00c9l\u00e9vation num\u00e9rique<\/li>\r\n
    • Pente<\/li>\r\n
    • Courbure<\/li>\r\n
    • Indice d'humidit\u00e9<\/li>\r\n
    • Hillshades<\/li>\r\n<\/ul>\r\n

      Donn\u00e9es sur le sol :<\/p>\r\n

        \r\n
      • pH<\/li>\r\n
      • CEC (capacit\u00e9 d'\u00e9change cationique)<\/li>\r\n
      • SOM (mati\u00e8re organique du sol)<\/li>\r\n
      • K (potassium)<\/li>\r\n
      • Faible \u00e9paisseur de la couche arable, capacit\u00e9 de r\u00e9tention d'eau r\u00e9duite (sol sujet \u00e0 la s\u00e9cheresse)<\/li>\r\n
      • CE (conductivit\u00e9 \u00e9lectrique)<\/li>\r\n
      • et d'autres attributs chimiques disponibles dans l'ensemble de donn\u00e9es t\u00e9l\u00e9charg\u00e9<\/li>\r\n<\/ul>\r\n\r\n\r\n\r\n

        Il est important de souligner que des facteurs personnalis\u00e9s sont configur\u00e9s au-dessus de chaque couche de donn\u00e9es pour attribuer les valeurs souhait\u00e9es.\u00a0poids de la couche<\/span>.Nous vous invitons \u00e0 partager vos cas d'utilisation d'analyses int\u00e9gr\u00e9es et \u00e0 cr\u00e9er des cartes de zones de gestion en fonction de votre connaissance du domaine, tout en s\u00e9lectionnant les sources de donn\u00e9es et leur pond\u00e9ration dans GeoPard.<\/p>\r\n\r\n\r\n\r\n

        Les images de ce blog contiennent un exemple de champ avec des couches de donn\u00e9es (comme une carte de productivit\u00e9 couvrant 18 ans, un mod\u00e8le num\u00e9rique d'\u00e9l\u00e9vation, la pente, l'ombrage du relief, les donn\u00e9es de rendement de 2019) et diverses combinaisons de cartes d'analyse d'int\u00e9gration.\u00a0<\/p>\r\n

        Vous pouvez suivre les \u00e9tapes de l'\u00e9volution des zones de gestion tout en \u00e9tendant l'analyse d'int\u00e9gration avec une couche de donn\u00e9es suppl\u00e9mentaire.<\/p>\r\n

        \r\n

        Questions fr\u00e9quemment pos\u00e9es<\/h2>\r\n
        \r\n

        1. Que sont les couches de donn\u00e9es ?<\/strong><\/p>\r\n

        Les couches de donn\u00e9es d\u00e9signent les composants ou \u00e9l\u00e9ments de donn\u00e9es individuels qui sont organis\u00e9s et empil\u00e9s pour cr\u00e9er une repr\u00e9sentation compl\u00e8te d'un domaine ou d'un sujet sp\u00e9cifique.<\/p>\r\n

        Chaque couche repr\u00e9sente un aspect sp\u00e9cifique des donn\u00e9es, comme les caract\u00e9ristiques g\u00e9ographiques, l'occupation des sols, la densit\u00e9 de population ou les facteurs environnementaux. Ces couches peuvent \u00eatre combin\u00e9es et analys\u00e9es conjointement pour obtenir des informations, visualiser des tendances et prendre des d\u00e9cisions \u00e9clair\u00e9es.<\/p>\r\n

        Les couches de donn\u00e9es sont couramment utilis\u00e9es dans les syst\u00e8mes d'information g\u00e9ographique (SIG) et l'analyse spatiale pour mieux comprendre et repr\u00e9senter des donn\u00e9es complexes de mani\u00e8re visuelle et interpr\u00e9table.<\/p>\r\n

        2. Qu'est-ce que l'analyse int\u00e9gr\u00e9e ?<\/strong><\/p>\r\n

        L'analyse int\u00e9gr\u00e9e d\u00e9signe le processus de combinaison et d'analyse de donn\u00e9es provenant de sources ou de disciplines multiples afin d'obtenir une compr\u00e9hension plus globale et plus compl\u00e8te d'un probl\u00e8me ou d'un ph\u00e9nom\u00e8ne particulier.<\/p>\r\n

        Cela implique la fusion d'ensembles de donn\u00e9es, l'application de techniques statistiques et l'exploration des relations entre diff\u00e9rentes variables ou diff\u00e9rents domaines.<\/p>\r\n

        L'analyse int\u00e9gr\u00e9e permet une vision plus nuanc\u00e9e et interconnect\u00e9e des syst\u00e8mes complexes, facilitant l'identification des sch\u00e9mas, des tendances et des relations causales qui peuvent ne pas \u00eatre \u00e9videntes lors de l'analyse de donn\u00e9es isol\u00e9es.<\/p>\r\n

        Cette approche permet aux chercheurs et aux d\u00e9cideurs de prendre des d\u00e9cisions plus \u00e9clair\u00e9es et plus efficaces, fond\u00e9es sur un \u00e9ventail d'informations plus large.<\/p>","protected":false},"excerpt":{"rendered":"

        L'agriculture de pr\u00e9cision est capable de g\u00e9n\u00e9rer d'\u00e9normes quantit\u00e9s de donn\u00e9es, notamment sur les rendements, l'imagerie satellitaire et la fertilit\u00e9 des sols. Le manque de solutions cloud faciles d'utilisation\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\/fr\/blog\/analyse-multicouche\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\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\/fr\/blog\/analyse-multicouche\/\" \/>\n<meta property=\"og:site_name\" content=\"GeoPard - 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