Getting Started with CyberGIS
Explore advanced geospatial analysis techniques using CyberGIS tools and Python programming for effective big data visualization and processing.
Explore advanced geospatial analysis techniques using CyberGIS tools and Python programming for effective big data visualization and processing.
This course introduces students to CyberGIS, combining advanced cyberinfrastructure with Geospatial Information Science and Systems (GIS). It covers the fundamentals of CyberGIS, geospatial data visualization using Python libraries, geospatial object manipulation, and big data processing with Hadoop. Students will learn to create maps, manipulate vector and raster data, and process large geospatial datasets. The course also explores theoretical foundations of CyberGIS and future trends in the field, providing a comprehensive introduction to geospatial data science and high-performance computing in GIS.
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What you'll learn
Understand the principles and components of CyberGIS
Create geospatial visualizations and web maps using Python libraries
Manipulate vector and raster data objects with geospatial libraries
Process big geospatial data using Hadoop framework
Apply theoretical concepts of CyberGIS to real-world applications
Explore future trends in geospatial data science
Skills you'll gain
This course includes:
1 Hours PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course provides a comprehensive introduction to CyberGIS, combining advanced cyberinfrastructure with Geospatial Information Science and Systems. Students will learn the fundamentals of CyberGIS, geospatial data visualization using Python libraries like Matplotlib and Cartopy, and geospatial object manipulation with Shapely and RasterIO. The curriculum covers big data processing using Hadoop for geospatial applications, theoretical foundations of CyberGIS, and future trends in the field. Participants will gain practical skills in creating maps, analyzing geospatial data, and handling large-scale geospatial datasets using cutting-edge technologies.
Course Orientation
Module 1 · 1 Hours to complete
Module 1: What is CyberGIS?
Module 2 · 1 Hours to complete
Module 2: Geospatial Visualization using Python
Module 3 · 1 Hours to complete
Module 3: Geospatial Object Manipulation and an Introduction to Taming Big Data with Hadoop
Module 4 · 1 Hours to complete
Module 4: Theoretical Foundations and Future Trends
Module 5 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructors
Pioneer in CyberGIS and Geospatial Data Science
Dr. Anand Padmanabhan serves as a Research Associate Professor in the Department of Geography and Geographic Information Science at the University of Illinois, where he leads groundbreaking research in advanced cyberinfrastructure and geospatial data science. With a Ph.D. in Computer Science from the University of Iowa, he has established himself as a leading expert in CyberGIS, distributed computing, and geospatial solutions. At the CyberGIS Center for Advanced Digital and Spatial Studies, he manages research infrastructure and operations, developing innovative solutions on platforms like NSF XSEDE and Open Science Grid. His significant contributions include creating software tools such as CyberGISX, CDC Malaria Map Application, and GISolve middleware. His research, funded by the National Science Foundation and Environmental Protection Agency, has produced numerous peer-reviewed publications with over 1,766 citations. He teaches courses in CyberGIS, Advanced GIS, and Geospatial Data Science, while leading the spatial algorithms and systems team to harness advanced cyberinfrastructure for geospatial discovery and innovation
Professor and Head of Geography and Geographic Information Science at the University of Illinois Urbana-Champaign
Shaowen Wang is a distinguished Professor and Head of the Department of Geography and Geographic Information Science at the University of Illinois Urbana-Champaign (UIUC), where he also holds positions as Richard and Margaret Romano Professorial Scholar and Affiliate Professor in multiple departments, including Computer Science and Urban and Regional Planning. He has been the Founding Director of the CyberGIS Center for Advanced Digital and Spatial Studies since 2013, and previously served as Associate Director of the National Center for Supercomputing Applications (NCSA) for CyberGIS. His research interests encompass geographic information science (GIS), advanced cyberinfrastructure, complex environmental problems, and spatial analysis, with a focus on developing scalable solutions for sustainability challenges. Dr. Wang has secured significant funding from various U.S. government agencies and has led numerous multi-institution projects aimed at advancing cyberGIS. He has published over 150 peer-reviewed papers and has served in editorial roles for several scientific journals. Recognized for his contributions to the field, he has received numerous awards, including the NSF CAREER Award and the AAG Distinguished Scholarship Honors. Dr. Wang is also actively involved in mentoring graduate students and postdoctoral fellows, many of whom have gone on to prominent positions in academia and industry.
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4.1 course rating
26 ratings
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