Resume
Cell: 716-429-6087
Yang Qing
Creekside Village, University at Buffalo,
NY, 14261
yangqing@buffalo.edu
Education
University at Buffalo, the State University of New York
May 2016
Master of Science in Geography Information Science
GPA: 3.8/4.0, Dean’s list: 3 semesters.
Relevant Coursework:
Spatial Statistics
Web Mapping
Cartography and Visualization
Environmental modeling and analysis
Technical Skills
Computer: Windows OS, Microsoft Office.
Programming languages: R, Java, Javascript, CSS, SQL
Software and Platforms: ArcGIS, ENVI, Rstudio, Eclipse, Programmer’s notepad
Relevant Projects
Glacier Information Extraction from Satellite Image, Fall 2014
 Performed calibration and transformation on Landsat images of Greenland in
August and February.
 Classified the surface substances into multiple categories, namely white ice, ashy
snow, fresh snow, and so forth.
 Computed the surface substances’ area and percentage of the whole area, as well
as their area change in the two months.
Weighted Shortest Path Program with User interface, Spring 2015
 Transformed population layer, land-use layer, and road base layer of Erie and
Niagara County into raster layers, then categorized them into multiple levels based on
cost-weighted distance.
 Integrated the previous layers as one layer based on the weight assigned, then
applied cost distance algorithms to find the shortest path between any pair of origin and
destination.
 Created an executable Java file with an interface which could be used to click and
select origins and destinations, then the shortest path would automatically be generated,
so as to better serve users’ convenience.
Grassroots Gardens of Buffalo, Spring 2015
 Categorized Buffalo vacancy parcel data into several levels, namely good,
moderate, and not good for potential future gardens, based on property values,
population, distance to schools and other facilities.
 Created a web-based interactive map showing all the attributes and existing gardens,
with Bing map base layer and clickable pop-up information.
Public Transport Route Assessment, Fall 2015
 Obtained public transport data from Google Transport Feed Specification (GTFS),
which were specially formatted text files.
 Converted the data to spatial data on R program, then got them compiled so that they
could be ready for spatial analysis and visualization.

Performed spatial analysis and visualization on the data, revealing some
characteristics of the whole transport network as well as their spatial variations. These
characteristics include: speed, frequency, population coverage, and spatial coverage.