{"id":5102,"date":"2024-07-15T12:59:36","date_gmt":"2024-07-15T12:59:36","guid":{"rendered":"https:\/\/pointly.ai\/vektordaten-aus-openstreetmap-in-4-einfachen-schritten-exportieren\/"},"modified":"2025-09-09T14:05:48","modified_gmt":"2025-09-09T14:05:48","slug":"vektordaten-aus-openstreetmap-in-4-einfachen-schritten-exportieren","status":"publish","type":"post","link":"https:\/\/pointly.ai\/de\/vektordaten-aus-openstreetmap-in-4-einfachen-schritten-exportieren\/","title":{"rendered":"Vektordaten aus OpenStreetMap in 4 einfachen Schritten exportieren"},"content":{"rendered":"
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< zur\u00fcck <\/i><\/a><\/p>\n<\/div>

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\"Titelbild<\/span><\/div>
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Vektordaten aus OpenStreetMap in 4 einfachen Schritten exportieren<\/span><\/strong><\/h1><\/div>
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ver\u00f6ffentlicht: 15.07.2024<\/p>\n<\/div>

Der Export von Vektordaten aus OpenStreetMap (OSM) \u00fcber die Overpass Turbo-Weboberfl\u00e4che ist eine nahtlose M\u00f6glichkeit, umfangreiche GeoJSON-Dateien zu erhalten, die sich problemlos in jedes GIS-System importieren lassen. Sie sind besonders n\u00fctzlich in Verbindung mit der Pointly-Plattform, um dem 3D-Punktwolken-Viewer eine zus\u00e4tzliche Ebene mit Kontextinformationen hinzuzuf\u00fcgen.<\/p>\n

In diesem Leitfaden f\u00fchren wir Sie durch den Prozess und stellen Ihnen Beispielabfragen zum Extrahieren verschiedener Datentypen zur Verf\u00fcgung.<\/p>\n<\/div>

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Schritt-f\u00fcr-Schritt-Anleitung zum Exportieren von GeoJSON aus Overpass Turbo<\/span><\/h2><\/div>

1. Zugang zu Overpass Turbo:<\/span><\/strong><\/h3><\/div>

Besuchen Sie Overpass Turbo<\/a> und richten Sie die Karte auf den Bereich aus, den Sie erkunden m\u00f6chten.<\/p>\n

Tipp: Es ist auch m\u00f6glich, einen bestimmten Bereich in der Abfrage zu definieren, z. B. eine Stadt, ein Bundesland oder ein Land, aus dem Daten extrahiert werden sollen.<\/p>\n<\/div>

2. Formulieren der Anfrage:<\/span><\/strong><\/h3><\/div>

Sie k\u00f6nnen Abfragen schreiben, um bestimmte Daten wie Br\u00fccken, Geb\u00e4udeumrisse und Gew\u00e4sser zu extrahieren. Nachfolgend finden Sie einige Beispielabfragen:<\/p>\n<\/div>

<\/i><\/i><\/span>a) Br\u00fccken<\/span><\/a><\/h4><\/div>
\n[out:json];
\n(
\nway[\"bridge\"=\"yes\"]();
\nrelation[\"bridge\"=\"yes\"]();
\n);
\nout body;
\n>;
\nout skel qt;<\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>b) Grundrisse von Geb\u00e4uden<\/span><\/a><\/h4><\/div>
\n[out:json];
\n(
\nway[\"building\"]();
\nrelation[\"building\"]();
\n);
\nout body;
\n>;
\nout skel qt;<\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>c) Gew\u00e4sser<\/span><\/a><\/h4><\/div>
\n[out:json];
\n(
\nway[\"natural\"=\"water\"]();
\nrelation[\"natural\"=\"water\"]();
\n);
\nout body;
\n>;
\nout skel qt;<\/p>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>d) Stromleitungen + Strommasten<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
way[\"power\"=\"line\"]();<\/div>\n
relation[\"power\"=\"line\"]();<\/div>\n
node[\"power\"=\"pole\"]();<\/div>\n
node[\"power\"=\"tower\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>e) Stra\u00dfen<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
way[\"highway\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>f) Gehwege<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
way[\"highway\"=\"footway\"]();<\/div>\n
way[\"highway\"=\"path\"]();<\/div>\n
way[\"highway\"=\"pedestrian\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>g) B\u00e4ume<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
node[\"natural\"=\"tree\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>h) Schienenwege<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
way[\"railway\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>i) Parkpl\u00e4tze<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
way[\"amenity\"=\"parking\"]();<\/div>\n
relation[\"amenity\"=\"parking\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div>

<\/i><\/i><\/span>j) Stra\u00dfenbeleuchtung<\/span><\/a><\/h4><\/div>
\n
[out:json];<\/div>\n
(<\/div>\n
node[\"highway\"=\"street_lamp\"]();<\/div>\n
);<\/div>\n
out body;<\/div>\n
>;<\/div>\n
out skel qt;<\/div>\n<\/div><\/div><\/div><\/div><\/div>

Tipp: ChatGPT kann Ihnen dabei helfen, pr\u00e4zise Overpass-Turbo-Abfragen zu erstellen. Beschreiben Sie einfach die Art der Daten, die Sie ben\u00f6tigen, und ChatGPT generiert die passende Abfrage.<\/p>\n<\/div>

3. Ausf\u00fchren der Abfrage<\/span><\/strong><\/h3><\/div>

Klicken Sie auf die Schaltfl\u00e4che \u201eAusf\u00fchren\u201c, um Ihre Abfrage auszuf\u00fchren.<\/p>\n<\/div>

\"Software<\/a><\/span><\/div>

Erstellen und f\u00fchren Sie die Abfrage aus, um eine Vorschau der Ergebnisse anzuzeigen.<\/em><\/p>\n<\/div>

4. Exportieren der Daten<\/span><\/strong><\/h3><\/div>

Sobald Ihre Abfrage Ergebnisse liefert, klicken Sie auf die Schaltfl\u00e4che \u201eExportieren\u201c und w\u00e4hlen Sie das Format \u201eGeoJSON\u201c, um Ihre Datei herunterzuladen.<\/p>\n<\/div>

\"Software-Screenshot<\/a><\/span><\/div>

Die abgefragten Objekte k\u00f6nnen in eine einzige GeoJSON-Datei exportiert werden.<\/em><\/p>\n

 <\/p>\n<\/div>

Weitere Funktionsmerkmale<\/span><\/h2><\/div>

Um weitere Attribute und Funktionen zu entdecken, die \u00fcber OpenStreetMap abgefragt werden k\u00f6nnen, besuchen Sie die umfassende Seite \u201eMap Features\u201c im OSM-Wiki<\/a>. Diese Ressource enth\u00e4lt detaillierte Informationen zu verschiedenen Tags und Attributen, die in OSM-Daten verwendet werden, und erm\u00f6glicht so detailliertere und individuellere Abfragen zur Datenextraktion.<\/p>\n<\/div>

Importieren von GeoJSON in Pointly<\/span><\/h2><\/div>

Wenn Ihre GeoJSON-Datei fertig ist, k\u00f6nnen Sie sie nun direkt aus dem Punktwolken-Viewer in Pointly importieren:<\/p>\n

Verwenden Sie die Importfunktion in Pointly, um die GeoJSON-Datei hochzuladen. Die zus\u00e4tzlichen Vektordaten werden \u00fcber Ihrer bestehenden 3D-Punktwolke angezeigt und liefern Ihnen so umfangreichere Kontextinformationen. Sie k\u00f6nnen auch die Farbe und die Anzeigeh\u00f6he der 2D-Vektorobjekte anpassen.<\/p>\n<\/div>

\"Software<\/a><\/span><\/div>

Die Vektordatei kann \u00fcber den Pointly Viewer hochgeladen werden.<\/em><\/p>\n<\/div>

Durch die Integration von OSM-Vektordaten in Pointly k\u00f6nnen Sie das kontextuelle Verst\u00e4ndnis und die Analyse Ihrer 3D-Punktwolken erheblich verbessern. Probieren Sie es aus und sehen Sie selbst, wie diese zus\u00e4tzlichen Informationsebenen Ihren Projekten zugute kommen k\u00f6nnen!<\/p>\n<\/div>

\"Software-Screenshot<\/a><\/span><\/div>

Importierte Objekte werden in der Punktwolke angezeigt (dieses Beispiel zeigt Br\u00fccken).<\/em><\/p>\n<\/div>

Weitere Tipps und Tutorials zur Nutzung der Funktionen von Pointly finden Sie in unserem Blog. Bei Fragen oder Anregungen k\u00f6nnen Sie sich gerne an uns wenden.<\/p>\n<\/div>

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Pointly \u2013 Zeigen, was wichtig ist.<\/span><\/strong><\/p>\n<\/div>

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<\/div>\u21e7 zur\u00fcck zum Anfang<\/a>
<\/div><\/div><\/div>
<\/div>
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\"Pointly<\/span><\/div>
<\/div>
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<\/div>
\u00dcber Pointly<\/span><\/strong><\/div>\n<\/div>
<\/div>
<\/div>
<\/div>
\n

Pointly is an intelligent, cloud-based software solution to manage and classify 3D point clouds \u2013 faster and more precise than ever before.<\/p>\n

With Pointly Services you can get on-demand advanced 3D point cloud solutions tailormade for you.<\/p>\n<\/div>\n<\/div>\n

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In diesem Leitfaden f\u00fchren wir Sie durch den Vorgang und stellen Ihnen Beispielabfragen zum Extrahieren verschiedener Datentypen zur Verf\u00fcgung.<\/p>\n","protected":false},"author":1,"featured_media":4523,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[38],"tags":[],"class_list":["post-5102","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-anleitung"],"yoast_head":"\nVektordaten aus OpenStreetMap in 4 einfachen Schritten exportieren<\/title>\n<meta name=\"description\" content=\"In diesem Leitfaden f\u00fchren wir Sie durch den Prozess und stellen Ihnen Beispielabfragen zum Extrahieren verschiedener Datentypen zur Verf\u00fcgung.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/pointly.ai\/de\/vektordaten-aus-openstreetmap-in-4-einfachen-schritten-exportieren\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Vektordaten aus OpenStreetMap in 4 einfachen Schritten exportieren\" \/>\n<meta property=\"og:description\" content=\"In diesem Leitfaden f\u00fchren wir Sie durch den Prozess und stellen Ihnen Beispielabfragen zum Extrahieren verschiedener Datentypen zur Verf\u00fcgung.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/pointly.ai\/de\/vektordaten-aus-openstreetmap-in-4-einfachen-schritten-exportieren\/\" \/>\n<meta property=\"og:site_name\" content=\"3D point cloud classification made smart, fast and easy - 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