{"id":177428,"date":"2025-06-04T10:41:10","date_gmt":"2025-06-04T10:41:10","guid":{"rendered":"https:\/\/flypix.ai\/?p=177428"},"modified":"2025-06-04T12:18:08","modified_gmt":"2025-06-04T12:18:08","slug":"open-data-for-wind-farm-site-identification","status":"publish","type":"post","link":"https:\/\/flypix.ai\/fr\/open-data-for-wind-farm-site-identification\/","title":{"rendered":"Donn\u00e9es ouvertes pour l'identification des sites de parcs \u00e9oliens"},"content":{"rendered":"
\"Donn\u00e9es<\/figure>\n\n\n

Introduction<\/h2>\n\n\n\n

Il n'est pas surprenant qu'identifier les emplacements id\u00e9aux pour la construction d'un nouveau parc \u00e9olien ne soit pas aussi simple que de trouver le terrain vague le plus proche, d\u00e9pourvu d'\u00e9olienne imposante. En r\u00e9alit\u00e9, identifier les emplacements les plus adapt\u00e9s n\u00e9cessite de conna\u00eetre une multitude de caract\u00e9ristiques propres au site concern\u00e9. Certaines sont d'ordre r\u00e9glementaire\u00a0: \u00ab\u00a0Sommes-nous suffisamment \u00e9loign\u00e9s de la ville la plus proche\u00a0?\u00a0\u00bb, \u00ab\u00a0Quel est le degr\u00e9 de protection naturelle prescrit pour cette zone\u00a0?\u00a0\u00bb. D'autres sont d'ordre pratique\u00a0: \u00ab\u00a0Le terrain est-il constructible\u00a0?\u00a0\u00bb, \u00ab\u00a0Cette zone re\u00e7oit-elle suffisamment de vent pour rentabiliser une nouvelle \u00e9olienne\u00a0?\u00a0\u00bb. R\u00e9pondre avec pr\u00e9cision \u00e0 ces questions, conform\u00e9ment aux exigences des principales parties prenantes, est une condition pr\u00e9alable \u00e0 la r\u00e9ussite de tout projet de construction d'envergure. Dans le cadre de ce projet, nous avons exploit\u00e9 les donn\u00e9es climatiques, l'imagerie d'observation de la Terre et la r\u00e9glementation afin d'identifier efficacement les zones de Salzbourg r\u00e9pondant \u00e0 un ensemble de crit\u00e8res pr\u00e9d\u00e9finis. Cet exemple illustre l'exploitation du big data dans un cas d'usage concret et donne un aper\u00e7u des nombreux \u00e9l\u00e9ments \u00e0 prendre en compte \u00e0 chaque \u00e9tape du processus.<\/p>\n\n\n\n

Source des donn\u00e9es<\/h2>\n\n\n\n

Naturellement, la premi\u00e8re \u00e9tape de toute t\u00e2che visant \u00e0 exploiter des jeux de donn\u00e9es g\u00e9ospatiales pour r\u00e9pondre \u00e0 une question pratique ou commerciale est l'approvisionnement des donn\u00e9es. Comme tout data scientist le sait, c'est l'\u00e9tape la plus cruciale\u00a0: chaque probl\u00e8me qui en d\u00e9coule d\u00e9coule en fin de compte des d\u00e9cisions\/choix effectu\u00e9s. Lors du d\u00e9veloppement d'une solution pour une application commerciale, il est particuli\u00e8rement important que les donn\u00e9es obtenues soient non seulement exactes, mais aussi id\u00e9alement certifi\u00e9es par les autorit\u00e9s comp\u00e9tentes. Une carte d\u00e9taill\u00e9e des informations de zonage, par exemple, n'a aucune valeur si elle ne peut \u00eatre certifi\u00e9e comme provenant directement de l'autorit\u00e9 comp\u00e9tente. C'est pourquoi les sources de donn\u00e9es officielles sont extr\u00eamement pr\u00e9cieuses, car elles fournissent non seulement les informations de terrain n\u00e9cessaires, mais aussi la l\u00e9gitimit\u00e9 des conclusions ou pr\u00e9visions qui en d\u00e9coulent. Dans le cadre de ce projet, le Bundesamt f\u00fcr Eich- und Vermessungswesen (Office f\u00e9d\u00e9ral de m\u00e9trologie et de topographie) d'Autriche, ainsi que la ressource Open Government Data (OGD) fournie par le Land de Salzbourg, ont constitu\u00e9 une excellente base pour le d\u00e9veloppement de notre \u00e9tude fonci\u00e8re exploitable sur les parcs \u00e9oliens.<\/p>\n\n\n\n

Tirer parti des connaissances<\/h2>\n\n\n\n

Comme mentionn\u00e9 pr\u00e9c\u00e9demment, l'identification des sites id\u00e9aux pour la construction de nouveaux parcs \u00e9oliens repose sur un ensemble de crit\u00e8res quantifiables qui permettent de caract\u00e9riser binairement une zone d'int\u00e9r\u00eat donn\u00e9e (\u00ab\u00a0adapt\u00e9e \u00e0 la construction d'un parc \u00e9olien\u00a0\u00bb, \u00ab\u00a0inadapt\u00e9e \u00e0 la construction d'un parc \u00e9olien\u00a0\u00bb). Ainsi, le non-respect de l'un de ces crit\u00e8res entra\u00eenerait l'exclusion de la zone de toute analyse ult\u00e9rieure. Cette m\u00e9thodologie permet d'\u00e9tablir un syst\u00e8me de classification simple et rapide pour d\u00e9terminer l'aptitude d'une r\u00e9gion \u00e0 la construction d'un parc \u00e9olien.<\/p>\n\n\n\n

La mise en \u0153uvre du processus d\u00e9crit ci-dessus peut \u00eatre d\u00e9compos\u00e9e comme suit :<\/p>\n\n\n\n

Tout d'abord, chaque crit\u00e8re a \u00e9t\u00e9 associ\u00e9 \u00e0 une source de donn\u00e9es fournissant suffisamment d'informations de base pour r\u00e9pondre positivement ou n\u00e9gativement \u00e0 la question. Ensuite, pour chaque crit\u00e8re, les informations de base associ\u00e9es ont \u00e9t\u00e9 trait\u00e9es afin de classer l'ad\u00e9quation de chaque r\u00e9gion de Salzbourg par rapport au crit\u00e8re en question. Une couche vectorielle a ainsi \u00e9t\u00e9 g\u00e9n\u00e9r\u00e9e pour chaque crit\u00e8re, classant les zones de Salzbourg en r\u00e9gions \u00ab\u00a0adapt\u00e9es\u00a0\u00bb ou \u00ab\u00a0inadapt\u00e9es\u00a0\u00bb. Nous allons maintenant examiner rapidement la g\u00e9n\u00e9ration de deux de ces couches.<\/p>\n\n\n\n

Identification des zones r\u00e9sidentielles<\/h3>\n\n\n\n

L'un des crit\u00e8res cl\u00e9s \u00e0 respecter pour la construction d'un nouveau parc \u00e9olien est sa distance appropri\u00e9e par rapport aux grandes zones r\u00e9sidentielles. Ce crit\u00e8re est indispensable dans la plupart des r\u00e9gions, en raison de la r\u00e9glementation gouvernementale en vigueur pour r\u00e9pondre aux pr\u00e9occupations en mati\u00e8re de pollution sonore, d'urbanisme et d'impact visuel de ces installations. L'utilisation de donn\u00e9es de terrain provenant du Bundesamt f\u00fcr Eich- und Vermessungswesen constitue un bon point de d\u00e9part pour tenter de g\u00e9n\u00e9rer une couche appropri\u00e9e segmentant Salzbourg en zones d\u00e9finies selon leur pertinence par rapport \u00e0 ce crit\u00e8re.<\/p>\n\n\n\n

\n
\n
\"\"<\/figure>\n<\/div>\n\n\n\n
\n
\"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n

Comme on peut le constater dans ce cas, les donn\u00e9es de terrain se composent de plusieurs polygones correspondant \u00e0 des structures existantes dans le Land de Salzbourg. Cela constitue un point de d\u00e9part prometteur, mais plusieurs questions doivent encore \u00eatre r\u00e9solues afin de transformer ces donn\u00e9es en une couche de classification binaire appropri\u00e9e. Par exemple, comment faire une distinction significative entre une ville, apparaissant ici comme un regroupement serr\u00e9 de polygones, et deux maisons isol\u00e9es dans un champ\u00a0? Dans ce cas, nous avons utilis\u00e9 l'algorithme Density-Based Spatial Clusterring, qui fournit une classification intuitive, bas\u00e9e sur la densit\u00e9, d'une zone en \u00ab\u00a0r\u00e9sidentielle\u00a0\u00bb ou \u00ab\u00a0non r\u00e9sidentielle\u00a0\u00bb, en fonction de la densit\u00e9 de ces polygones structurels et de leur nombre de voisins. Ainsi, nous pouvons par exemple obtenir la classification suivante.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
\n
\n

Identification des r\u00e9gions de niveau<\/h3>\n\n\n\n

Un autre crit\u00e8re important pour tout projet de construction est la qualit\u00e9 du terrain. En r\u00e8gle g\u00e9n\u00e9rale, les projets de construction doivent \u00eatre construits \u00e0 niveau afin de fournir des fondations ad\u00e9quates \u00e0 la structure pr\u00e9vue. Au-del\u00e0 d'une certaine pente, les co\u00fbts de nivellement deviennent prohibitifs pour la faisabilit\u00e9 du projet. Heureusement, des donn\u00e9es raster open source, issues de relev\u00e9s laser, sont disponibles \u00e0 une r\u00e9solution de 5 m.<\/p>\n\n\n\n

Dans ce cas, puisqu'il s'agit de donn\u00e9es raster et non vectorielles, la conversion de cette couche en un masque de classification binaire est l\u00e9g\u00e8rement plus complexe. Pour ce faire, nous avons d\u00e9fini un angle seuil au-del\u00e0 duquel un point d'int\u00e9r\u00eat \u00e9tait consid\u00e9r\u00e9 comme \u00ab trop raide \u00bb. L'interrogation des donn\u00e9es raster pour toutes ces r\u00e9gions, leur extraction en vecteurs avec OpenCV et le seuillage des zones extraites nous ont permis d'obtenir la classification souhait\u00e9e.<\/p>\n<\/div>\n\n\n\n

\n
\"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n

Conclusion<\/h2>\n\n\n\n

Apr\u00e8s avoir extrait avec succ\u00e8s un masque de classification binaire pour chacun des crit\u00e8res d\u00e9finissant l'aptitude d'une r\u00e9gion \u00e0 la construction d'un parc \u00e9olien, il suffit de combiner tous les masques de classification en un seul. Les r\u00e9gions obtenues sont les r\u00e9gions optimales, telles que d\u00e9termin\u00e9es par les donn\u00e9es officielles de terrain fournies par le gouvernement du Land de Salzbourg et le gouvernement f\u00e9d\u00e9ral autrichien. Une v\u00e9ritable d\u00e9couverte\u00a0!<\/p>\n\n\n\n

<\/p>","protected":false},"excerpt":{"rendered":"

Introduction It may come as no surprise that identifying ideal locations for the construction of a new wind farm is not as trivial as finding the nearest open field without a towering wind turbine. 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