Project | 01

The General Transit Feed Specification (GTFS) is a data specification that allows public transit agencies to publish their transit data. As it is written in text, it is difficult to grasp all the information easily. This tool was built to transform the GTFS feed into spatial data. It was built by Python and can be run in Esri program.

Project | 02

The Research & Analytics Group at the Atlanta Regional Commission developed the 2017 data release of more than 700 layers across statewide geography. I assisted data cleaning, publishing, and sharing process. Using the URL query, I could sort the 700 data into subsets by geographies and by topics. Two ArcGIS custom tools were used to update the ACS (2013-2017) data. These tools were written in Python.

Project | 03

Little is known about long-term rainfall trends and related atmospheric dynamics in western Uganda. Using high-dimension rainfall and atmospheric data sets, this study examines the controls of and trends in seasonal rainfall across western Uganda for the 1983-2017 period. R and Python were used for data processing. ArcGIS and Adobe Illustrator were used for the data visulization.

Project | 04

Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, but relying on patterns and inference. I trained ML models using 4 types of predictive ML classifiers. This project was a part of the final project of 'Fundamentals of Data Science' class at the Computer Sciences Department, Georgia State University, in Fall 2018.

Project | 05

The ecological footprint measures human demand on nature. Korea Ecological Footprint Report 2016 illustrates the amount of natural resources that have been consumed in South Korea (1961-2012). The aim of this report was to invite public, private, and other parties to rethink natural assets with increasing resource constraints and climate change threats. My role was analyzing data, and writing paragraphs on page 20, 32-37, and 48-49.

© 2019 by Hae Seung Sung


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