Getting Started with CyberGIS from Coursera

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Syllabus

Course Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

Module 1: What is CyberGIS?

In this module, we will get introduced to the basics of CyberGIS and Geospatial Data Science. First, we'll learn about the definition of Geographic information science and systems, and related concepts. Next, we'll get introduced to the basics of advanced cyberinfrastructure and its components. Then we will see how CyberGIS combines Cyberinfrastructure and GIS to produce a sum that is greater than its parts. We will see the components of CyberGIS and the community and sciences it supports. Then, we look at geospatial big data, specifically the complexity and challenges it presents in terms of data representation, sharing, and privacy. We then look at how Geospatial Data Science provides tools to resolve the challenges posed by big geospatial data. Finally, we conclude the lesson by looking at scientific applications and drivers that require CyberGIS and Geospatial Data Science to address the problems posed by them.

Module 2: Geospatial Visualization using Python

In this module, students will get introduced to techniques for geospatial visualization and Web mapping using Python. First we'll learn about the basics of plotting geospatial data and creating maps using Matplotlib, Basemap, and Cartopy. Next, we will learn techniques to create and share our Web maps using Mplleaflet and Folium libraries. Lastly, we will see a brief introduction to GeoPandas and how to use it to do simple plot, simple geometry, and conduct basic spatial operations.

Module 3: Geospatial Object Manipulation and an Introduction to Taming Big Data with Hadoop

In this module, students will get first get introduced to techniques for manipulating geospatial objects using geospatial libraries in Python. Specifically, we will learn how to manipulate both vector and raster data objects using Shapely and RasterIO libraries. Next, students get introduced to using the Hadoop paradigm for taming big geospatial data. Specifically, we will learn the fundamentals of how to process big spatial data with Hadoop. Students will get a brief introduction to the Hadoop framework, its major components, and its characteristics, and will learn about Hadoop Distributed File System (HDFS), its architecture and simple commands to interact with it. We will also learn about the MapReduce computing paradigm and see an example of how it may be applied using Hadoop streaming API to process New York City taxi data.

Module 4: Theoretical Foundations and Future Trends

In this module, we will learn about the theoretical underpinnings of CyberGIS. We will start the module by looking into theoretical foundations of cyberGIS, specifically looking at the computational intensity calculations. Then we will apply the theoretical concepts to an application case study learning how to calculate this computational intensity. Lastly, we will conclude the module and course by looking at some future trends.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops core skills needed to apply cutting-edge advances of CyberGIS in contemporary geospatial data science industry and/or academic research

Taught by leading experts Shaowen Wang and Anand Padmanabhan

Strong focus on theoretical foundations of CyberGIS

Provides an introduction to taming big data

Covers cutting-edge topics not found in many other courses

Coursework requires students to come in with basic geospatial data science background knowledge

Reviews summary

Introductory cybergis concepts

Learners say this course offers a largely positive introduction to CyberGIS, covering its exciting and modern topics effectively. While some students would prefer more focus on GIS-type analysis and practical applications, others commend the course's ability to go hand in hand with cyber-geoint. Reviewers indicate engaging assignments and advanced computing infrastructure are included, but some mention that important texts and exercises are not provided.

Engaging assignments included.

Introduces learners to CyberGIS concepts.

"Course covers very exciting and modern GIS topic on integrating advanced computing infrastructure with spatial data and problems."

Some important texts/articles and exercises are not included.

"Does not include all text/articles discussed in lectures and also fails to include the exercises."

Could use more focus on GIS analysis.

"I thought the course was addressed to either GIS experts wanting to use python and distributed computing resources or data scientists wanting to move to the geospatial domain (my case)."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Getting Started with CyberGIS with these activities:

Practice with GeoPandas

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Practice using GeoPandas to strengthen your understanding of geospatial object manipulation.

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Install GeoPandas
Load a spatial dataset into a GeoDataFrame
Perform basic spatial operations (e.g., buffer, dissolve, union)

Tutorial on Geospatial Visualization with Python

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Follow a tutorial to enhance your skills in visualizing geospatial data using Python libraries such as Matplotlib and Cartopy.

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Set up the required Python environment
Import the necessary libraries
Create a map using Matplotlib and Basemap
Style the map using Cartopy

Exercises on Hadoop Fundamentals

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Complete exercises on Hadoop fundamentals to reinforce your understanding of its architecture, components, and functionalities.

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Install Hadoop and set up a Hadoop cluster
Write a simple MapReduce program
Run the program on a Hadoop cluster and analyze the results

Two other activities

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Build a Web Map with GeoJSON

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Create a web map using GeoJSON to gain hands-on experience in sharing and visualizing geospatial data on the web.

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Prepare your geospatial data in GeoJSON format
Create a web mapping application using a library like Leaflet or OpenLayers
Deploy the web map on a platform like GitHub Pages

Project: Develop a Geospatial Application

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Embark on a project to build a geospatial application, integrating concepts from CyberGIS and Geospatial Data Science, to address a real-world problem.

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Identify a problem that can be addressed with geospatial data and analysis
Design and plan the application
Implement the application using appropriate geospatial tools and libraries
Test and evaluate the application's functionality and performance
Deploy the application and share it with others

Career center

Learners who complete Getting Started with CyberGIS will develop knowledge and skills that may be useful to these careers:

Geospatial Data Analyst

Geospatial Data Analysts are responsible for collecting, managing, analyzing, and interpreting geospatial data. They use their knowledge of GIS and data science to solve problems and make informed decisions. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Data Analysts.

See salaries and explore the career path for Geospatial Data Analyst

Geospatial Developer

Geospatial Developers are responsible for designing, developing, and maintaining geospatial applications. They use their knowledge of GIS and programming to create tools and solutions that help users visualize, analyze, and interact with geospatial data. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Developers.

See salaries and explore the career path for Geospatial Developer

GIS Manager

GIS Managers are responsible for overseeing the implementation and use of GIS technology within an organization. They work with users to identify needs, develop strategies, and implement solutions. This course provides a strong foundation in CyberGIS, which is essential for managing big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for GIS Managers.

See salaries and explore the career path for GIS Manager

Geospatial Scientist

Geospatial Scientists use their knowledge of GIS and data science to study the Earth's surface. They use geospatial data to identify patterns, trends, and relationships. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Scientists.

See salaries and explore the career path for Geospatial Scientist

Urban Planner

Urban Planners use their knowledge of GIS and planning to design and manage cities and towns. They use geospatial data to identify problems and opportunities, and to develop plans for future development. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Urban Planners.

See salaries and explore the career path for Urban Planner

Transportation Planner

Transportation Planners use their knowledge of GIS and transportation planning to design and manage transportation systems. They use geospatial data to identify problems and opportunities, and to develop plans for future development. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Transportation Planners.

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Environmental Scientist

Environmental Scientists use their knowledge of GIS and environmental science to study the environment. They use geospatial data to identify and assess environmental problems, and to develop solutions. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Environmental Scientists.

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Land Surveyor

Land Surveyors use their knowledge of GIS and surveying to measure and map land. They use geospatial data to create accurate maps and plans. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Land Surveyors.

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Geospatial Intelligence Analyst

Geospatial Intelligence Analysts use their knowledge of GIS and intelligence analysis to analyze geospatial data. They use geospatial data to identify and assess threats, and to develop strategies for应对. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for Geospatial Intelligence Analysts.

See salaries and explore the career path for Geospatial Intelligence Analyst

GIS Technician

GIS Technicians use their knowledge of GIS to create and maintain maps and other geospatial data. They use geospatial data to support a variety of applications, such as planning, engineering, and environmental management. This course provides a strong foundation in CyberGIS, which is essential for working with big geospatial data. The course also covers topics such as geospatial visualization, object manipulation, and Hadoop, which are all important skills for GIS Technicians.

See salaries and explore the career path for GIS Technician

Statistician

Statisticians use their knowledge of statistics to collect, analyze, and interpret data. They use statistics to solve problems, make predictions, and develop new products and services. This course may be helpful for Statisticians who want to learn about CyberGIS and its applications in geospatial data science.

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Data Scientist

Data Scientists use their knowledge of statistics, machine learning, and data mining to analyze data and extract insights. They use data to solve problems, make predictions, and develop new products and services. This course may be helpful for Data Scientists who want to learn about CyberGIS and its applications in geospatial data science.

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Operations Research Analyst

Operations Research Analysts use their knowledge of mathematics and computer science to solve problems in a variety of industries. They use mathematical models to analyze data, identify inefficiencies, and develop solutions to improve operations. This course may be helpful for Operations Research Analysts who want to learn about CyberGIS and its applications in geospatial data science.

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Computer Scientist

Computer Scientists use their knowledge of computer science to study the theory and practice of computation. They develop new algorithms and theories to solve problems and improve the efficiency of computing systems. This course may be helpful for Computer Scientists who want to learn about CyberGIS and its applications in geospatial data science.

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Software Engineer

Software Engineers use their knowledge of computer science to design, develop, and maintain software applications. They use software to solve problems, improve efficiency, and create new products and services. This course may be helpful for Software Engineers who want to learn about CyberGIS and its applications in geospatial data science.

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Getting Started with CyberGIS

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Syllabus

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Reviews summary

Introductory cybergis concepts

Activities

Career center

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