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Applied DBSCAN | Columbia GSAPP
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README.md
queens-dbscan.R

README.md

DBSCAN | Spatiotemporal Analysis

DBSCAN

Included in this repo is part of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) methodology used in the spatiotemporal analysis "Signal or Noise? Qualified Opportunity Zones in Queens". The step not included here was the spatial join of intersecting census blocks to building permits and land parcel centroids of real estate sales. The methodology was conducted in R and was written without optimization or data frame lists in order to be explicit. Interpretability for those not familiar with coding was important.

All other data handling procedures and analyses, including the comparative methodology (Anselin Local Moran's I) was completed outside of the R environment (ArcGIS). The publicly available data has also been included in the link here for the raw reproduction of the DBSCAN methodology. In addition, the final report and poster has been included for distribution. Please observe the correct citations when using this information.

This analysis was conducted with Suprima Bhele and completed as a final project in partial fulfillment for the course Advanced Spatial Analysis at Columbia University GSAPP in 2019.

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