This site contains information on the research and teaching activities by Dr R E Sieber and her team at McGill University.

Our newest masters student, Jin Xing

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Welcome to Jin Xing, who officially joins our group. He is studying for a masters degree in Computer Science. In his research he will investigate the use of cloud computing for remote sensing. Specifically, he will examine the challenges of building a hybrid cloud for analyzing large hyperspectral remote sensed imagery files.

 

Welcome to our newest postdoc, Nama

Our new postdoc, Nama Budhathoki, holds a Bachelors degree in Computer Science. He worked as an information and communication technology (ICT) specialist for two years for the government of Nepal before he went to the Netherlands to pursue graduate study. He completed a Master of Science degree in Geographic Information Science (GIS) from the International Institute of Geo- Information Science and Earth Observation (ITC) in 1999. Following the Master of Science degree, he continued working for the development of a national land information system in Nepal for five years. He began his PhD studies at the University of Illinois at Urbana-Champaign in 2005 and successfully completed in 2010.

Sieber attends Microsoft Research Faculty Summit

Prof Sieber was invited to attend the the Microosft Research Faculty Summit, which "brings together more than 400 thought leaders from academia, government, and Microsoft to reflect on how current computing disciplines open new opportunities for research and development".

The following day she presented at Microsoft Research's Environmental Research Workshop on "Citizen Environmental Science and the Geospatial Web 2.0".

Jian Zhou presents at GEOIDE

Masters student Jian Zhou presented his work on integrating Ferret with the Google Earth API at the Annual GEOIDE meeting.

Design and Implementation of a Script to Integrate Ferret with KML

Jian Zhou and Renee Sieber

Climate change is considered an urgent concern for society yet a very complex and difficult process to understand scientifically. Computer-driven climate models are simplifications of the real world and the primary tools used today in climate change research. Many excellent visualization and data analysis tools have been developed for the study and evaluation of large climate model outputs that are mainly in NetCDF format.

Recent years have seen scientists publicize climate data on earth browsers (e.g., Google Earth, NASA World Wind) for the users to visualize and analysis in three dimensional spaces. The data is being transferred into the earth browsers via KML. KML, an international standard maintained by the Open Geospatial Consortium (OGC year). Because climate data is georegistered to a common base, KML files allow users to overlay and expose this data in new ways.

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