Piperoll 3d new york4/19/2023 ![]() ![]() Here is a sample that explains how to do that. So I added the search widget and set the feature layer with the buildings as the source. Finding the Empire State Building just by looking at the map can be very difficult for users that are not familiar with Manhattan, so searching by name is what most people would do. One solution is to set a vertical offset to lift them up and add a line callout to make sure the location of the label is still clear to the user.Īnother very useful feature is the search functionality. Adding labels on a 3D map can be tricky because from most angles they will end up being hidden by buildings. In a first phase I decided to add the names of the most important negihbourhoods in Manhattan. I was pretty happy with the result so far, but realized that I needed to add more tools to help users easily find the buildings and orient themselves on the map. For more information about styling points in a city, have a look at this sample. I used several new features, among which the relative-to-scene elevationInfo mode and featureReduction to solve these problems. The problem was that these icons were hidden by the buildings and were overlapping quite a lot. That’s why I added an extra point layer with information icons that show which buildings have extra information. Not all the buildings have a Wikipedia article so I wanted to mark the buildings that have such information. Most of the skyscrapers are very famous and have their own Wikipedia page, so I used MediaWiki to search for it and get the abstract of the page. That’s why I decided to use the Wikipedia API (called MediaWiki) and the Flickr API. ![]() ![]() Here is a sample on how it works.Īlthough the original dataset was enriched with attributes like building name, construction year and building height, I was curious about some more information like what’s the current use or how does it look like. You can filter features in a FeatureLayer or a SceneLayer by using definitionExpression. Filtering out buildings below 500 feet leaves only skyscrapers in Lower and Midtown Manhattan. Let’s say for example I’m only interested in buildings above 500 feet. That’s why I added a filter to the SceneLayer that would allow me to only display buildings that exceed a certain height. Immediately spotting the tallest buildings on a 3D map is not straightforward. Highlighting is a new functionality in the version 4.4 of the JavaScript API. If a user selects a building in the timeline then the app will zoom to that building and display more information about it. The timeline is connected to the map: if a user selects a building on the map, the corresponding element will be highlighted in the timeline. It was interesting to confirm that fewer skyscrapers were built during the Great Depression and almost none during World War II. In this timeline each building is a circle with the color given by the construction period. Then I was curious to correlate construction year and height, so I built a timeline with Y axis representing the height. This way I could identify the areas with newer or older buildings, discover which buildings were built in the same period or see that in some neighbourhoods like Soho most of the buildings were built before 1925. I started by coloring the buildings based on the time period they were built in. All the new features in version 4.4 contributed to making this a really fun to use and intuitive app. I built an application looking for answers to these questions using ArcGIS API for JavaScript. I focused on Manhattan, because I was mostly interested in the highest and most popular buildings in New York: when were they built? how tall are they? what do they look like? what are they currently used for? This was also my goal when I started building the Manhattan Skyscraper Explorer. ![]() Therefore, building a web application based on such data seems like a natural solution to empower citizens and people around the world to find out more about the buildings in New York. However, to get to explore New York buildings, users should have access to the software that reads and visualizes the 3D models, which is often not the case. Examples of such datasets are the New York 3D city model and the Housing Information published by the New York City Department of Information Technology and Telecommunications. It’s amazing how many organizations publish their data to allow citizens to learn more about the city they live in. ![]()
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