heat_and_trees
Using HoloViz to explore relationship between surface temperature and tree density
Visualizing and Analyzing Earth Science Data Using HoloViz and PyData
Earth Science presents interesting issues of large, multi-dimensional datasets stored in a variety of idiosyncratic file formats. In this talk, we'll work through some specific workflows and explore how various tools - such as intake, dask, xarray, and datashader - can be used to effectively analyze and visualize these data. Working from within the notebook, we'll iteratively build a product that is interactive, scalable and deployable.
Case Study: Heat and Street Trees
We'll be exploring the urban heat island effect by looking at the impact on surface temperature of roof color. We'll be replicating the process described here: http://urbanspatialanalysis.com/urban-heat-islands-street-trees-in-philadelphia/ but using Python tools rather than ESRI.
We'll also be adding interactivity and deploying the resulting application.
Run on binder
Run locally
conda env create --file environment.yml
conda activate trees
jupyter notebook
Relevant materials
Recording: https://youtu.be/-XMXNmGRk5c
Static version: https://jsignell.github.io/heat_and_trees
About me
I am a software developer at Anaconda Inc. currently working on developing best practices for Python-using earth scientists. I work on visualization tools within the HoloViz ecosystem and data ingestion and analysis tools in the broader PyData world. I live in Philadelphia and previously did hydrology research at Princeton - studying lightning and rain patterns, water movement through the landscape, and streamflow.