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Gerade weil damit ein so großes Spektrum an Personen (vom GIS-Profi bis zum Laien) angesprochen wird, ist es wichtig die Anwendungsoberfläche möglichst einfach und für jeden passend zu gestalten. Per Konfiguration kannst Du das sehr gut umsetzen. Wenn Du aber mehr willst, kannst Du einige Optionen noch auf eine andere Art und Weise anpassen. Welche Optionen das sind und wie Du damit noch flexibler werden kannst in der Gestaltung der Portal-Website stelle ich in diesem Blog vor.


Welche Optionen kann ich anpassen?

In der sehr gut dokumentierten Online-Hilfe kannst Du Dich informieren, welche einzelnen Optionen Du beeinflussen kannst. Hier findest Du die Liste zu einigen Parametern.


Wie kann ich dies Optionen anpassen?

Im Portal for ArcGIS-Installationsverzeichnis findest Du im Ordner

...\customizations\<version number>\webapps\arcgis#home\js\arcgisonline\

die Datei config.js. Öffne diese mit einem Texteditor. Hier kannst Du nun beeinflussen welche Optionen Du noch setzen willst.


Ich habe mir für diesen Blog zwei Optionen herausgepickt, die ich Dir nun kurz vorstellen werde.


Nachdem Du die Parameter geändert hast, musst Du das Portal neu starten und den Browser-Cache leeren.



Einstellungen und detaillierte Informationen zum gesamten Portal dürfen in vielen Fällen nur von Administratoren anpassbar bzw. einsehbar sein. Um das zu gewährleisten, kannst Du die Schaltfläche Organization für alle Nutzer, die keine Administratoren-Rolle innehaben, deaktivieren. Setze dazu den Parameter restrictOrganizationPageToAdmin von false auf true. Schon erscheint die Schaltfläche Organization nur noch für Administratoren.




Auf jeder Portal-Seite wird im unteren Bereich eine Link-Zeile eingeblendet. Per UI-Konfiguration kannst Du hier eine Kontakt E-Mail-Adresse angeben. Mit Hilfe des footerLinks-Parameters lassen sich hier zusätzlich weitere URLs oder Kontaktdaten angeben. Hier im Beispiel habe ich Links eingefügt auf die Esri Deutschland Homepage, GeoNet, die GeoDev Germany Gruppe meine und die Kontaktadresse des Supports. So haben die Benutzer auf allen Seiten die Möglichkeit auf diese Ressourcen zuzugreifen.




Schau Dir doch gleich mal Deine config.js-Datei an und finde heraus, welche Optionen für Deine Installation interessant seien könnten.


Viele Spaß beim Ausprobieren! 

We all love open data!
And we love them even more if we can turn them into meaningful maps faster than I can put my make-up on.


So, it was clear that, as soon as Berlin shares their GTFS data on their open data portal, magic will happen.


The General Transit Feed Specification (GTFS) is a standardized data format for storing public transit routes, stops, and schedules. GTFS data is used in Google Maps transit trip planning. What can you do with GTFS data, you ask? Here are a few examples of applications you can build based on this type of data:

  • Trip planing and maps
  • Timetable
  • Data visualizations
  • Accessibility
  • Real-time transit information

 GTFS Data is GIS Data, so you can use this data to visualize the public transit system, perform spatial analysis, reveal patterns, identify hot spots and white spaces, conduct time-based analysis and get powerful insight.


Based on the Berlin Transit Open Data, I used ArcGIS Pro to answer following question: how many trips per hour are there at the stops on a Monday morning between 6 A.M. and 9 A.M. and what is the maximum wait time for this time window?


I started off by downloading the Display GTFS in ArcGIS Toolbox that Melinda Morang created. Using this tool, I was able to visualize my GTFS open data and discover the public transportation network and stations from Berlin and the surroundings. Given a geodatabase path, all you have to do is run the scripts and it automatically creates feature classes for both transit routes and stops.



To better understand my data, I categorized my transit shapes based on the type of route (e.g. bus, tram, metro).



But this level of insight was not quite enough, so I decided to use some more tools Melinda developed. After downloading the BetterBusBuffer Toolbox, I ran the Count High Frequency Routes At Stops Script and got some amazing results. In the picture down below, the rectangles represent the trip frequency per hour for a typical Monday morning. 



To get a better understanding of the waiting times at the bus and train stations in Berlin, I just adjusted the symbology to MaxWaitTime. I then blended out the stops where the waiting time was greater than 60 min. and got the following results:


As you can see, inside of the MP of Berlin, there are no rectangles. This means that the next step in analysis should focus on reducing the waiting times in the rural areas around Berlin, for the public transportation segments going to downtown Berlin. 


Feel free to download the rest of the transit toolboxes to unlock The Science Of Where and create the Maps That Change The World


If you any questions about this blog entry, you can reach me under this e-mail.

Follow me on Twitter and LinkedIn.

Last weekend I had the chance to attend HackZurich, one of the biggest hackathons in Europe. And what can I says? The event was a blast. Over 580 people from 58 countries showed to spend 3 days together at TechnoPark Zürich and work on various challenges. And that was actually only the tip of the iceberg. In fact, the organizers had to close applications already in June counting an unbelievable 4864 applications. Not bad, hm?



So many hackers of course attract a lot of sponsors too, be it now challenge or technology sponsors. I was really impressed by the breath of sponsors: Google, Microsoft, SNN, Thomson Reuters, Wikidata, Randstad, Rai Lab, Swiss Re, Swisscom, Zühlke and SBB were just a few of the big names.


They all had very diverse and interesting challenges. Here are 2 out of the 18(!) that really caught my attention:

  • Bühler Group, a manufacturer for food processing machines, asked for ideas to improve wheat production.
  • Reuters opened up their API to basically access their news database.


Talking about the challenges: I liked the clear instructions the organizers gave. team size between 2 and 4 and the clear goal to actually build something in the 3 days.


Esri was one of the technology sponsors and gave a tech talk on Saturday to inspire people. Additionally, Matthias Schenker (Esri Switzerland), John Yaist and David Martinez (both Esri Inc.) made themselves available at the Esri booth to support the various teams.



Curious about the outcome? In our next blog, we will describe a few of the teams and of course will tell you finally won the Esri price. Stay tuned :-) And be sure to reserve your seat early enough for next year. There won't be less hackers willing to go.


Finally, here are some more impressions:






On September 18th, the third GeoMonday of this year was held on the topic “artificial intelligence and geodata”. More than 30 good-humoured Geogeeks, well supplied with pizza and beer, listened to exciting lectures and discussed lively about them.



Did you miss this past GeoMonday? No problem, we have recorded all talks and took some pictures, see below. And don't worry, after GeoMonday is before GeoMonday. You can find all the details on or here on GeoNet.


See you again soon!

Your GeoDev Germany & GeoMonday Team!




Michael Marz, Esri Deutschland:

How neural networks make GIS-supported crop production more efficient

High-tech has already arrived in agriculture. Modern agricultural machinery and geographic information systems make precision farming possible. An important aspect in crop production is the basic fertilization with nutrients and additives. The pH value can already be determined in a small scale and during the crossing of a tractor with specific sensors. For essential macronutrients like phosphorus, on-site soil sampling as well as complex and cost-intensive determination of the content in the laboratory are still necessary. Phosphorus content depends on chemical and physical soil conditions. If these conditions are known, the content of phosphorus can be estimated. This paper provides extracts from a research project on how neural networks help to estimate local phosphorous content for fertilization by learning those nonlinear multilateral relationships in the soil.



Martin Wilden and Matthias Stein, con terra:

Natural language understanding in web mapping applications

"Will speech soon do away with typing?" - This question has recently been raised by a large German newspaper. Lately, more and more speech assistants like Google Assistant, Amazon's Alexa, Mircosoft's Cortana or Apple's Siri are reaching the market and allowing users to control many parts of their life by voice input. This technology is called natural language understanding (NLU) and may also be used to control Web mapping technology. Imagine that you could say "show me all schools in Berlin" instead of using a selection tool to select those features.




Some impressions:


Kreative Ideen für die intelligente Mobilität sind gefragt: Wie können mit GIS und Geodaten Mobilitätsprozesse, -verfahren und -abläufe sicherer und zuverlässiger gestaltet werden?


Der Deutsche Mobilitätspreis (#DMP17) ist eine Initiative des Digitalgipfels und des BMVI. In der diesjährigen Open Innovation Phase vom 4.9. bis zum 16.10. wird gefragt wie mit Geodaten Mobilität zuverlässiger und sicherer gestaltet werden kann. Daher unterstützt Esri diesen Wettbewerb.

Der von Deutschland – Land der Ideen ausgerichtete Wettbewerb spricht Einzelpersonen an, die mit geringem Aufwand ihre Ideen im Wettbewerbsportal darstellen können.

Nach dem 16.10 entscheidet eine Jury unter Leitung des BMVI über die Gewinner der drei Geldpreise.


Zum Wettbewerbsportal geht es hier: https://ideen.deutscher-mobilitä






Deutschland – Land der Ideen:

Twitter: #DMP17

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