Team Name:
AfterRealism
Team Members:
AfterRealism
We wanted to build a system that ingest spatial information at scale and aid us in making decision. In short we want to build skynet :) We started with baby steps; for starter we need a platform that can visualize large datasets. It will be used by diverse group of people, so it has to be a web platform.
we experimented with training deep learning model to predict 3D building
we downloaded building footprint data set and merged it with OSM data
we got high resolution aerial imagery and protected it on top of DEM
we used WebGL technology to project large scale datasets in browser
Description of Use This was a fundamental dataset that we used to build our map and plot building 3D buildings. We used it along with OSM to extract building labels.
Description of Use we plotted these on map this was good fun seeing which parks are where along with bike route to plan a weekend outing
Description of Use This is such a cool dataset. We ploted places were street art had been done. We wanted to find images online of those street art as well. so you can click on map and see what the painting is like :)
Description of Use We thought it would be really cool to plot all the routes and try to figure out which residential buildings are furthest away, like show a change of color tone.
Description of Use This was pretty cool dataset. Building footprint on there own don't tell you what kind of building it is. this dataset merged with building footprint tells exactly what the role of a particular building is in the city.
Description of Use Initially we thought this would be awesome like places marked in it are landmarks but it identified too places. It was useful in labeling building footprint dataset.
Description of Use We download DEM files from here. But there were in chucks and it looked like a lot of work to stitch them together so for our final project we used the other source mentioned above.
Description of Use We used this dataset to create a Digital elevation model(DEM). Then we "stitched" high resolution aerial images on top of it to create 3D a model.
Description of Use We imported it as a restful service in QGIS, and used it in our attempt to train a model to prediction 3D buildings.
Go to Challenge | 3 teams have entered this challenge.
