2023 Note:
This is a portfolio (circa 2019) for GIS, map-making, and data analysis projects created by Daniel Chi Cook. Daniel is now a professional ELA teacher who also writes, takes photographs, and plays the banjo. 
This website will be updated in the future to reflect the author’s current activities and interests. Thank you and come again.



Selected Projects:



"sliceNYC"

A menu of tasty political and administrative boundaries used in the City of New York
Each of the options in the dropdown menu at the top right feeds a url to the map's JavaScript code which corresponds to the NYC Open Data portal's SODA API query for each particular boundary data set. I made this as a way to easily visualize the concept of geographic boundaries. It could also be used to guide or inform various types of spatial-based or community-based planning. You could even use these as a guide to developing your own way to slice up the city! I am thinking of calling it “sliceNYC”, which up until now only seems to be used as a tag in Instagram posts about pizza. Here is a link to the map's code on GitHub.


NYC Street Trees Remix

A different visual and interactive take on the Street Trees data set
My favorite part of this map is scrolling over a point and seeing all the trees of the same species light up. Also--how about aggregating results of the tree census according to counts within (human) census tracts? This map pulls data from the 2015 Street Tree Census. I invite you also to compare this to NYC Department of Parks and Recreation's Street Tree Map, which is in my opinion one of the most impressive maps currently out there. This was completed in part through a course I took at Pratt's Spatial Analysis and Visualization Initiative (SAVI) on interactive web mapping, programming, and design with Eric Brelsford and it is inspired by work that I completed at the Battery Park City Authority. Here is a link to my map's code on GitHub.


Mapping personal satisfaction using public data

What parts of NYC give me a sense of satisfaction? I used the presence of cafes with outdoor (sidewalk) seating, community gardens, and publicly operated restrooms as indicators for how much satisfaction I might expect to feel across the city. Construction noise (measured as 311 complaints) served as an indicator for the opposite of satisfaction. This is my attempt to map these things in ArcGIS using publicly available data.


Imagine if there was a public website that visualized datasets like this - perhaps residents could use such a platform to explore the city and plan where they would like to visit (or live!).
The data in this attempt were originally points. They were converted in ArcGIS to kernel density rasters and then added together. The subsequent raster was then classified into these color-coded "satisfaction" categories. Here are the datasets I used:
Restrooms
Gardens
Sidewalk cafes
311 complaints




Stalled construction complaints in NYC Community Districts

Exploration, visualization, and analysis with the R statistical programming language!


I found evidence of a statistically significant relationship between the number of stalled construction complaints and the number of educational and youth facilities within community districts. This finding, in my opinion, could warrant further research into the relationship between things like zoning laws and construction projects in the city.







Exploring and analyzing large building energy use in NYC

By visualizing the energy use intensity of large buildings, we can explore how efficiently these buildings are using their energy, and over what areas in the city certain patterns might be occurring. This can help agencies and stakeholders improve performance and meet goals such as OneNYC’s 80x50 emissions reduction target. Try it out! Scroll to your favorite part of NYC, zoom in on a building, and click it to see its stats.
I produced several CARTO web maps which allow users to explore building performance data across the city.  I made these maps, like the one shown above, after finishing a project that I worked on with a group of 8 other students at Columbia University for NYC Housing Preservation and Development (HPD). Our goal was to help HPD evaluate one of their green building programs by acquiring, cleaning, and analyzing Local Law 84 data, which tracks performance metrics for buildings over 50,000 square feet in size. My role involved developing a methodology for the analysis, getting the data, putting the data into a file that could be used by my team, and doing some of the initial analyses. Along the way, I produced presentations, R scripts for data exploration and visualization, and a massive Excel file which we later gave to HPD.  The CARTO map above visualizes a 2016 LL84 dataset that I cleaned for the project by joining it with NYC MapPLUTO tax lot data.







Solar radiation in lower Manhattan

Using arcgis to model solar resources!These images are the end product of my attempts to use arcgis's "solar radiation" spatial analyst tool. In essence, the tool uses elevation data (a georeferenced raster image called a digital elevation model) to estimate the quantity of sunlight that an area will receive over a period of time, in Watt-hours per square meter.
Planners, developers, and others can use this data for a variety of purposes including solar panel installation, recreational planning, horticultural planting. NYS uses this same sort of modeling to build its fascinating "NY Solar Map" platform. Since I was using this tool in an urban environment, it was first necessary to place buildings (their shapes and heights) on top of the elevation data. It is common practice to use this tool to calculate solar radiation during time periods where the sun will either be strongest, weakest, or moderate in the area of interest. Typically these are times that include the summer solstice, the winter solstice, and either one of the equinoxes. One thing missing in this is the tree canopy, which would theoretically decrease the calculated solar radiation reaching areas where there are trees. For open source options there is GRASS's "r.sun" tool (available packaged with QGIS).
NYC Building Footprints (height and shape data)