Geospatial Big Data Lab.
Department of Geography, Kyung Hee University, South Korea
WELCOME
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Welcome to our website :)
Geospatial Big Data Lab is a team of passionate and enthusiastic students and researchers in the Department of Geography, Kyung Hee University. Since its foundation in 2016, the lab has focused on the use of spatial data analysis and modelling for urban studies. On this website, you can find out about our publications, research projects and contact details. This is also a place where we put step-by-step tutorials and example data for an R package 'seg'. If you have any questions about our work, please feel free to contact us at the email addresses listed in the People page. |
OUR WORK
Our lab members have come from a variety of disciplines with diverse research interests. Some of us work on developing new (possibly better) methods for visualising and analysing the geographic distribution of social and environmental events in cities, while some of us focus more on the applications of state-of-art technologies to real-world, urban problems.
A common thread that runs through our research topics is that they are all data-driven. Essentially, we are all interested in understanding and explaining spatial patterns of urban activities and phenomena with large-scale data from various sources. Our recent works, which can be broadly classified into the following three categories, reflect this underlying theme.
A common thread that runs through our research topics is that they are all data-driven. Essentially, we are all interested in understanding and explaining spatial patterns of urban activities and phenomena with large-scale data from various sources. Our recent works, which can be broadly classified into the following three categories, reflect this underlying theme.
parallel computing for spatial analysis on cloud platforms
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modelling urban dynamics using machine learning approaches
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population segregation in activity spaces
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Please check out the Work page if you need more information on our current and past research activities. We support reproducible research. Therefore, we are trying to provide the source code we used for our publications whenever we can using our GitHub repository.
MEASURING SEGREGATION USING R
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The seg package is a collection of population segregation measures and visualisation tools in R. Implemented measures range from simple, traditional indices like the index of dissimilarity (1955) to more sophisticated, spatial approaches such as Reardon and O'Sullivan's spatial segregation measures (2004).
The package is available to download from the Comprehensive R Archive Network (CRAN). On this website, we will provide step-by-step tutorials that illustrate basic features and example data for demonstration. |
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JOINING THE LAB
Working in a collaborative and supportive learning environment, we focus on developing quantitative and computational methods suitable for big data analytics and applying them to solve various social problems in cities.
We welcome prospective graduate students and post-docs who will be a good fit for our team and research. If you are interested in working and studying with us, please send us an email to syhong@khu.ac.kr with your CV and a brief statement of research interests.
We welcome prospective graduate students and post-docs who will be a good fit for our team and research. If you are interested in working and studying with us, please send us an email to syhong@khu.ac.kr with your CV and a brief statement of research interests.
CONTACT US
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Address:
Room 523, Science Building (Space 21) Kyung Hee University 26 Kyungheedae-ro, Dongdaemun-gu, Seoul, South Korea 02447 |
Phone:
+82 2-961-9344 +82 2-961-0848 (fax only) |
Email:
gbdl.info [at] gmail.com |