11-20, 16:00–16:25 (Pacific/Auckland), WA220
This presentation highlights the feasibility and impact of teaching “Cloud-based Open-source GIS Solutions” through student-developed applications. Featuring five selected apps, it demonstrates how project-based learning fosters practical skills, innovation, engagement with open geospatial technologies, preparing students to contribute effectively to the evolving landscape of open GIS.
This presentation shares the experience of designing and delivering a university course centered on Scaffolded Project-Based Learning (SPL) in the context of cloud-based open-source GIS. Drawing from Cloud-based Open-source GIS Solutions at RMIT University, the session highlights how SPL can be used to equip students with both foundational geospatial knowledge and cutting-edge technical skills, aligning their learning with the demands of a rapidly evolving geospatial industry.
Cloud-based, open-source GIS represents an emerging paradigm in geospatial science. It goes beyond teaching students to operate individual tools by emphasizing GIS as a system for spatial thinking and decision-making. Through the SPL framework, students are guided from being tool users to becoming system designers and tool builders. The course structure integrates theory, new technologies, and iterative, scaffolded practice to help students design cloud-native geospatial solutions to real-world challenges.
At the core of the course is a semester-long, individual project in which students conceptualize, develop, and deploy a functional GIS application. These projects are not just technical exercises—they are opportunities to design systems that perform spatial analysis, support decision-making, and address practical challenges such as urban heat islands, flooding, environmental degradation, and spatial inequality. Students use open-source tools and platforms such as PostGIS, QGIS, GitHub, Cesium Ion, Earth Engine Apps, Mapbox, Leaflet, and GeoAI frameworks, while learning deployment strategies using cloud infrastructure and serverless technologies.
The SPL pedagogy ensures students build confidence and competence through structured phases:
Early-stage assignments introduce essential tools, spatial data formats, and cloud workflows;
Mid-semester milestones guide system architecture, backend/frontend integration, and data sourcing;
Peer feedback and mentoring support project refinement and encourage collaborative learning.
This pedagogical strategy fosters not only technical fluency but also critical thinking about how to design geospatial systems that are scalable, interoperable, and user-focused. It reinforces the understanding that spatial technologies are most powerful when they are purposefully assembled to solve complex problems—something increasingly demanded by industry, government, and community sectors.
The presentation will feature lightning talks by five students whose applications reflect creativity, technical rigor, and engagement with real-world issues. While the applications are in progress, each talk will emphasize the problem addressed, the open-source stack used, and the design decisions made. This format aims to share process over product—highlighting learning outcomes, problem-solving strategies, and reflections on using open-source technologies in a cloud-native environment.
Additionally, this session will present a broader reflection on how scaffolded project-based learning can transform geospatial education. It will explore questions such as:
How can SPL help students move from passive users to active developers of spatial solutions?
What competencies are most critical for graduates entering cloud-native geospatial workforces?
How can open-source and academic communities better support each other in this transition?
Preliminary evaluations of the course indicate that this approach promotes student engagement, deepens understanding of geospatial systems architecture, and encourages students to see themselves as contributors to the open-source ecosystem. Several students have expressed interest in continuing their projects post-course or using them as part of a professional portfolio.
Real-world case studies—including the development of virtual flooding digital twins and visualizations for climate resilience—illustrate the alignment between classroom learning and industry needs. These examples demonstrate how SPL, combined with cloud-native open-source GIS, offers a scalable and adaptable model for preparing students to work at the intersection of spatial science, digital technologies, and societal challenges.
By sharing the design, philosophy, and outcomes of this course, the presentation aims to contribute to broader discussions on how to teach the next generation of geospatial professionals in ways that are future-ready, open, and grounded in systems thinking. It will be of particular interest to educators, developers, curriculum designers, and anyone engaged in building capacity in the FOSS4G ecosystem.
Associate Professor Qian (Chayn) Sun is a geospatial scientist specializing in urban informatics, GeoAI, and environmental health. She leads the GISail research group at RMIT University, focusing on developing advanced geospatial solutions to improve urban resilience and sustainability. Her research integrates spatial analytics, remote sensing, and machine learning to address complex challenges in urban planning, climate change mitigation, and public health. Chayn has led several key projects with AURIN, including the Integrated Heat Vulnerability Assessment Toolkit, and the development of a national database on Culturally and Linguistically Diverse (CALD) communities to analyze health and environmental inequalities, has published extensively on social vulnerability and heat-health risk in Australian cities. She is also dedicated to mentoring postgraduate students and fostering interdisciplinary collaboration.
Ryan Turner is a PhD student in Geospatial Science at RMIT University and a Research Assistant at the Centre for Urban Research (CUR) at RMIT University who develops digital interactive tools using various remote sensing and geospatial technologies.
Ryan's PhD research focuses on the development of a Global Urban Heat Vulnerability Index (GUHVI) which applies geospatial theory to unveil inequities in heat vulnerability at a global scale. This research addresses the ever increasing presence of heat on human populations by developing a framework to align and coordinate efforts to effectively respond to heat and reduce inequities for more equitable cities worldwide.
At CUR, he is currently developing an online interactive tool that combines agent-based modelling outputs with cycling infrastructure scenarios to quantify active travel investment in partnership with the Victorian Department of Transport and Planning and the City of Greater Bendigo. Also at CUR, Ryan has been involved in developing spatial indicators of large public green space and urban heat vulnerability for the Global Observatory of Healthy and Sustainable Cities. His research outputs involved international author teams to deliver well-designed and accessible outcomes at both the local and global scale.