C\u00f3digo CLC<\/th>	Denomina\u00e7\u00e3o simplificada<\/th>	Grau de adequa\u00e7\u00e3o ap\u00edcola (\u03bc)<\/th>	Justificativa<\/th><\/tr><\/thead>
111\u2013142<\/td>	\u00c1reas urbanas\/artificializadas<\/td>	0.1<\/td>	Muito baixo, poucos recursos florais naturais<\/td><\/tr>
211\u2013244<\/td>	\u00c1reas agr\u00edcolas (culturas, mosaicos agr\u00edcolas)<\/td>	0.6<\/td>	Presen\u00e7a de prados e culturas mel\u00edferas poss\u00edveis<\/td><\/tr>
311\u2013313<\/td>	Florestas (folhosas, con\u00edferas, mistas)<\/td>	0.8<\/td>	Ricas em esp\u00e9cies mel\u00edferas, dependendo da esta\u00e7\u00e3o <\/td><\/tr>
321\u2013324<\/td>	Vegeta\u00e7\u00e3o natural (matagais, matorrais, etc.) <\/td>	0.9<\/td>	Muito favor\u00e1vel, flora\u00e7\u00e3o prolongada, poucas perturba\u00e7\u00f5es<\/td><\/tr>
331\u2013335<\/td>	Espa\u00e7os abertos, praias, zonas rochosas<\/td>	0.3<\/td>	Poucas flores, condi\u00e7\u00f5es dif\u00edceis<\/td><\/tr>
411\u2013423<\/td>	Zonas h\u00famidas<\/td>	0.4<\/td>	Ambientes inst\u00e1veis, por vezes ricos mas fr\u00e1geis<\/td><\/tr>
511\u2013523<\/td>	Massas de \u00e1gua \/ mar<\/td>	0.0<\/td>	Evidentemente n\u00e3o prop\u00edcio<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n \n\n\n\n <\/span>\u00c9tape 3 : Transformation floue<\/span><\/h3>\n\n\n\n Avec le plugin FuzzyAttributes<\/strong> \u2192 module Classes \u2192 Fuzzy<\/strong> :<\/p>\n\n\n\n <\/span>1-Charger le raster CLC (reclass\u00e9 ou original).<\/span><\/h4>\n\n\n\n $\"L\u2019attribut$ <\/a><\/figure>\n\n\n\n <\/span>2-D\u00e9finir la table de correspondance ci-dessus (codes et \u03bc).<\/span><\/h4>\n\n\n\n $\"L\u2019attribut$ <\/a><\/figure>\n\n\n\n <\/span>3-G\u00e9n\u00e9rer le raster flou `fzy_corine.tif<\/code>.<\/span><\/h4>\n\n\n\n`<\/span>4-Visualiser : les zones favorables (\u03bc proches de 1) appara\u00eetront plus claires.<\/span><\/h4>\n\n\n\n<\/a><\/figure>\n\n\n\n \n\n\n\n<\/span>\u00c9tape 4 : Interpr\u00e9tation<\/span><\/h3>\n\n\n\n\nOn obtient une carte continue de convenance apicole<\/strong>, au lieu d\u2019un patchwork de classes rigides.<\/li>\n\n\n\n Elle peut ensuite \u00eatre combin\u00e9e avec d\u2019autres crit\u00e8res flous<\/strong> :\n\nproximit\u00e9 de l\u2019eau (besoin d\u2019abreuvement)<\/li>\n\n\n\n altitude \/ pente<\/li>\n\n\n\n distance aux routes (accessibilit\u00e9)<\/li>\n\n\n\n absence de cultures trait\u00e9es<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\nUne agr\u00e9gation floue de ces crit\u00e8res produira une carte multicrit\u00e8re d\u2019implantation optimale des ruches<\/strong>.<\/p>\n\n\n\n \n\n\n\n<\/span>En r\u00e9sum\u00e9<\/span><\/h3>\n\n\n\n\nTransformer un raster de classes en raster flou, c\u2019est passer d\u2019une logique \u201ccat\u00e9gorique\u201d \u00e0 une logique \u201cgraduelle\u201d \u2014 on quitte le \u201ctout ou rien\u201d pour repr\u00e9senter le degr\u00e9 de pertinence<\/strong> de chaque classe vis-\u00e0-vis d\u2019un objectif.<\/p>\n<\/blockquote>\n\n\n\n \n","protected":false},"excerpt":{"rendered":"Em alguns casos, os dados n\u00e3o s\u00e3o cont\u00ednuos (altitude, inclina\u00e7\u00e3o, dist\u00e2ncia…), mas discretos, ou seja, constitu\u00eddos por classes. Cada pixel corresponde ent\u00e3o a uma categoria: um tipo de solo, um uso do solo, um n\u00edvel de…<\/p>\n","protected":false},"author":1,"featured_media":15762,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"give_campaign_id":0,"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"sfsi_plus_gutenberg_text_before_share":"","sfsi_plus_gutenberg_show_text_before_share":"","sfsi_plus_gutenberg_icon_type":"","sfsi_plus_gutenberg_icon_alignemt":"","sfsi_plus_gutenburg_max_per_row":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"jetpack_post_was_ever_published":false,"_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":""},"categories":[3418,2134],"tags":[3634,3134,3733],"class_list":["post-15830","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pluigin-pt","category-qgis","tag-fuzzyattributes-pt","tag-raster-pt","tag-v2-pt"],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/www.sigterritoires.fr\/wp-content\/uploads\/2025\/10\/fzy_exemple_raster_out.jpg?fit=1982%2C1649&ssl=1","jetpack_shortlink":"https:\/\/wp.me\/p6XU0A-47k","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts\/15830","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/comments?post=15830"}],"version-history":[{"count":0,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts\/15830\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/media\/15762"}],"wp:attachment":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/media?parent=15830"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/categories?post=15830"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/tags?post=15830"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

Contenu <\/p>\nToggle<\/span>

O princ\u00edpio<\/a>
- Etapas no plugin FuzzyAttributes<\/a><\/li><\/ul><\/li>
- Boas pr\u00e1ticas<\/a><\/li>
- Um exemplo concreto<\/a>
  - Etapa 1: Fonte dos dados<\/a><\/li>
  - Etapa 2: Correspond\u00eancia das classes<\/a><\/li>
  - \u00c9tape 3 : Transformation floue<\/a>
    - 1-Charger le raster CLC (reclass\u00e9 ou original).<\/a><\/li>
    - 2-D\u00e9finir la table de correspondance ci-dessus (codes et \u03bc).<\/a><\/li>
    - 3-G\u00e9n\u00e9rer le raster flou fzy_corine.tif.<\/a><\/li>
    - 4-Visualiser : les zones favorables (\u03bc proches de 1) appara\u00eetront plus claires.<\/a><\/li><\/ul><\/li>
    - \u00c9tape 4 : Interpr\u00e9tation<\/a><\/li>
    - En r\u00e9sum\u00e9<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<\/p>\n\n\n\n
      \n\n\n\n
      Em alguns casos, os dados n\u00e3o s\u00e3o cont\u00ednuos (altitude, inclina\u00e7\u00e3o, dist\u00e2ncia…), mas discretos, ou seja, constitu\u00eddos por classes.<\/p>\n\n\n\n
      Cada pixel corresponde ent\u00e3o a uma categoria: um tipo de solo, um uso do solo, um n\u00edvel de risco, etc.<\/p>\n\n\n\n
      Essas rasters \u201ccateg\u00f3ricas\u201d s\u00e3o muito frequentes na an\u00e1lise espacial, mas apresentam um problema:<\/p>\n\n\n\n
      como integr\u00e1-las em uma an\u00e1lise multicrit\u00e9rio difusa, uma vez que n\u00e3o cont\u00eam valores num\u00e9ricos cont\u00ednuos?<\/p>\n\n\n\n
      \u00c9 a\u00ed que entra o m\u00f3dulo Classes \u2192 Fuzzy do plugin FuzzyAttributes (vers\u00e3o 2).<\/p>\n\n\n\n
      \n\n\n\n
      <\/span>O princ\u00edpio<\/span><\/h2>\n\n\n\n
      Em vez de trabalhar diretamente com as classes (1, 2, 3… ou \u201cfloresta\u201d, \u201curbano\u201d, \u201c\u00e1gua\u201d), procuramos expressar para cada uma delas em que medida satisfaz um determinado crit\u00e9rio.<\/p>\n\n\n\n
      Exemplos:<\/p>\n\n\n\n
      \n
      Para um crit\u00e9rio \u201czonas favor\u00e1veis \u00e0 infiltra\u00e7\u00e3o\u201d,\n
      \n
      solos arenosos \u2192 satisfa\u00e7\u00e3o 0,9<\/li>\n\n\n\n
      solos argilosos \u2192 satisfa\u00e7\u00e3o 0,3<\/li>\n\n\n\n
      \u00e1reas urbanas \u2192 satisfa\u00e7\u00e3o 0,1<\/li>\n<\/ul>\n<\/li>\n\n\n\n
      Para um crit\u00e9rio \u201crisco de eros\u00e3o\u201d,\n
      \n
      declives acentuados \u2192 0,8<\/li>\n\n\n\n
      florestas \u2192 0,2<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n
      O resultado \u00e9 um raster difuso, no qual cada pixel assume um valor entre 0 e 1, representando o grau de satisfa\u00e7\u00e3o do crit\u00e9rio.<\/p>\n\n\n\n
      \n\n\n\n
      <\/span>Etapas no plugin FuzzyAttributes<\/span><\/h3>\n\n\n\n
      \n
      Menu: Classes \u2192 Fuzzy<\/li>\n\n\n\n
      Selecione um raster categ\u00f3rico (monobanda, do tipo inteiro).<\/li>\n\n\n\n
      O plugin l\u00ea os valores \u00fanicos presentes na camada.<\/li>\n\n\n\n
      Para cada classe, insira o grau de pertencimento difuso (entre 0 e 1).
      Voc\u00ea tamb\u00e9m pode carregar uma tabela de correspond\u00eancia a partir de um arquivo CSV<\/a> existente.<\/li>\n\n\n\n
      Escolha um nome para o raster difuso de sa\u00edda (por exemplo, fzy_classes.tif).<\/li>\n\n\n\n
      Clique em Criar raster difuso.<\/li>\n<\/ol>\n\n\n\n
      \n\n\n\n
      <\/span>Boas pr\u00e1ticas<\/span><\/h2>\n\n\n\n
      \n
      A coer\u00eancia depende do crit\u00e9rio estudado: uma mesma classe pode ser favor\u00e1vel em uma an\u00e1lise e desfavor\u00e1vel em outra.<\/li>\n\n\n\n
      Evite valores absolutos 0 e 1, a menos que tenha certeza absoluta: a l\u00f3gica difusa permite expressar nuances.<\/li>\n\n\n\n
      Documente suas correspond\u00eancias: elas podem ser registradas em um arquivo CSV ou em uma tabela do GeoPackage<\/a> para serem reutilizadas.<\/li>\n<\/ul>\n\n\n\n
      \n\n\n\n
      <\/span>Um exemplo concreto<\/span><\/h2>\n\n\n\n
      Objetivo:<\/strong><\/p>\n\n\n\n
      Criar um mapa de adequa\u00e7\u00e3o para a instala\u00e7\u00e3o de colmeias a partir do raster CORINE Land Cover.<\/p>\n\n\n\n
      Princ\u00edpio:<\/strong><\/p>\n\n\n\n
      Cada tipo de ocupa\u00e7\u00e3o do solo (floresta, pastagem, zona agr\u00edcola, urbana, etc.) recebe um grau de satisfa\u00e7\u00e3o entre 0 e 1, de acordo com seu interesse ap\u00edcola.<\/p>\n\n\n\n
      \n\n\n\n<\/span>Etapa 1: Fonte dos dados<\/span><\/h3>\n\n\n\n
      Voc\u00ea pode baixar o raster CLC diretamente aqui:
      https:\/\/land.copernicus.eu\/pan-european\/corine-land-cover\/clc2018<\/a><\/p>\n\n\n\n
      Formatos dispon\u00edveis: GeoTIFF, resolu\u00e7\u00e3o de 100 m.<\/p>\n\n\n\n
      Em seguida, voc\u00ea pode recort\u00e1-lo de acordo com a \u00e1rea de estudo (por exemplo, a C\u00f3rsega).<\/p>\n\n\n\n
      \n\n\n\n
      <\/span>Etapa 2: Correspond\u00eancia das classes<\/span><\/h3>\n\n\n\n
      Aqui est\u00e1 uma tabela de correspond\u00eancia de exemplo para a avalia\u00e7\u00e3o ap\u00edcola:<\/p>\n\n\n\n
      C\u00f3digo CLC<\/th> Denomina\u00e7\u00e3o simplificada<\/th> Grau de adequa\u00e7\u00e3o ap\u00edcola (\u03bc)<\/th> Justificativa<\/th><\/tr><\/thead>
      111\u2013142<\/td> \u00c1reas urbanas\/artificializadas<\/td> 0.1<\/td> Muito baixo, poucos recursos florais naturais<\/td><\/tr>
      211\u2013244<\/td> \u00c1reas agr\u00edcolas (culturas, mosaicos agr\u00edcolas)<\/td> 0.6<\/td> Presen\u00e7a de prados e culturas mel\u00edferas poss\u00edveis<\/td><\/tr>
      311\u2013313<\/td> Florestas (folhosas, con\u00edferas, mistas)<\/td> 0.8<\/td> Ricas em esp\u00e9cies mel\u00edferas, dependendo da esta\u00e7\u00e3o <\/td><\/tr>
      321\u2013324<\/td> Vegeta\u00e7\u00e3o natural (matagais, matorrais, etc.) <\/td> 0.9<\/td> Muito favor\u00e1vel, flora\u00e7\u00e3o prolongada, poucas perturba\u00e7\u00f5es<\/td><\/tr>
      331\u2013335<\/td> Espa\u00e7os abertos, praias, zonas rochosas<\/td> 0.3<\/td> Poucas flores, condi\u00e7\u00f5es dif\u00edceis<\/td><\/tr>
      411\u2013423<\/td> Zonas h\u00famidas<\/td> 0.4<\/td> Ambientes inst\u00e1veis, por vezes ricos mas fr\u00e1geis<\/td><\/tr>
      511\u2013523<\/td> Massas de \u00e1gua \/ mar<\/td> 0.0<\/td> Evidentemente n\u00e3o prop\u00edcio<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \n\n\n\n
      <\/span>\u00c9tape 3 : Transformation floue<\/span><\/h3>\n\n\n\n
      Avec le plugin FuzzyAttributes<\/strong> \u2192 module Classes \u2192 Fuzzy<\/strong> :<\/p>\n\n\n\n
      <\/span>1-Charger le raster CLC (reclass\u00e9 ou original).<\/span><\/h4>\n\n\n\n
      $\"L\u2019attribut$ <\/a><\/figure>\n\n\n\n
      <\/span>2-D\u00e9finir la table de correspondance ci-dessus (codes et \u03bc).<\/span><\/h4>\n\n\n\n
      $\"L\u2019attribut$ <\/a><\/figure>\n\n\n\n
      <\/span>3-G\u00e9n\u00e9rer le raster flou `fzy_corine.tif<\/code>.<\/span><\/h4>\n\n\n\n`<\/span>4-Visualiser : les zones favorables (\u03bc proches de 1) appara\u00eetront plus claires.<\/span><\/h4>\n\n\n\n<\/a><\/figure>\n\n\n\n \n\n\n\n<\/span>\u00c9tape 4 : Interpr\u00e9tation<\/span><\/h3>\n\n\n\n\nOn obtient une carte continue de convenance apicole<\/strong>, au lieu d\u2019un patchwork de classes rigides.<\/li>\n\n\n\n Elle peut ensuite \u00eatre combin\u00e9e avec d\u2019autres crit\u00e8res flous<\/strong> :\n\nproximit\u00e9 de l\u2019eau (besoin d\u2019abreuvement)<\/li>\n\n\n\n altitude \/ pente<\/li>\n\n\n\n distance aux routes (accessibilit\u00e9)<\/li>\n\n\n\n absence de cultures trait\u00e9es<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\nUne agr\u00e9gation floue de ces crit\u00e8res produira une carte multicrit\u00e8re d\u2019implantation optimale des ruches<\/strong>.<\/p>\n\n\n\n \n\n\n\n<\/span>En r\u00e9sum\u00e9<\/span><\/h3>\n\n\n\n\nTransformer un raster de classes en raster flou, c\u2019est passer d\u2019une logique \u201ccat\u00e9gorique\u201d \u00e0 une logique \u201cgraduelle\u201d \u2014 on quitte le \u201ctout ou rien\u201d pour repr\u00e9senter le degr\u00e9 de pertinence<\/strong> de chaque classe vis-\u00e0-vis d\u2019un objectif.<\/p>\n<\/blockquote>\n\n\n\n \n","protected":false},"excerpt":{"rendered":"Em alguns casos, os dados n\u00e3o s\u00e3o cont\u00ednuos (altitude, inclina\u00e7\u00e3o, dist\u00e2ncia…), mas discretos, ou seja, constitu\u00eddos por classes. Cada pixel corresponde ent\u00e3o a uma categoria: um tipo de solo, um uso do solo, um n\u00edvel de…<\/p>\n","protected":false},"author":1,"featured_media":15762,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"give_campaign_id":0,"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"sfsi_plus_gutenberg_text_before_share":"","sfsi_plus_gutenberg_show_text_before_share":"","sfsi_plus_gutenberg_icon_type":"","sfsi_plus_gutenberg_icon_alignemt":"","sfsi_plus_gutenburg_max_per_row":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"jetpack_post_was_ever_published":false,"_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":""},"categories":[3418,2134],"tags":[3634,3134,3733],"class_list":["post-15830","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-pluigin-pt","category-qgis","tag-fuzzyattributes-pt","tag-raster-pt","tag-v2-pt"],"aioseo_notices":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/www.sigterritoires.fr\/wp-content\/uploads\/2025\/10\/fzy_exemple_raster_out.jpg?fit=1982%2C1649&ssl=1","jetpack_shortlink":"https:\/\/wp.me\/p6XU0A-47k","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts\/15830","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/comments?post=15830"}],"version-history":[{"count":0,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/posts\/15830\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/media\/15762"}],"wp:attachment":[{"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/media?parent=15830"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/categories?post=15830"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.sigterritoires.fr\/index.php\/wp-json\/wp\/v2\/tags?post=15830"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}