Associating 3D point clouds from the 2017 topobathymetric lidar survey with the 2015 street tree census, and making (almost) every street tree in NYC viewable in a web interface.
In understanding the equity of street tree impact as a distributed cellular natural infrastructure, it was clear we needed to better document the morphology of the trees themselves.
Point cloud statistics populate fields of the web page upon request. Shadow paths are cast in-browser to visualize cooling and shading at different times of year.
Extraction and association are performed in Python.
Points are visualized in a customized Mapbox interface using deck.gl.
Folio pages for every member of that tree species in the same zipcode are built on the fly by passing values as query parameters to a javascript page and utilizing D3.js.
Project for Design Across Scales Lab, Cornell University.
