Tech Day
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Tech Day

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Explore the cutting edge of technology in practice and tools for site analysis, visualization, design, and collaboration. Moving beyond the basics, Tech Day starts with a deep dive into Geospatial AI with Esri, where you will discover how to harness machine learning and satellite imagery to track shifting environments, from forest loss to urban sprawl, even when traditional data is unavailable. Learn to extract intricate landscape patterns using pre-trained and self-trained models, empowering you to make data-driven design decisions for ecological preservation and long-term land-use strategies. This session will be complemented by technical demonstrations from industry leaders SiteMarker and Land F/X. Tech Day provides the high-tech toolkit you need to master complex sites and redefine the boundaries of your practice. 

Tech Day: Thursday, August 20, 2026

1:00-2:00pm ET: Mapping Change: How Machine Learning Reveals Shifting Landscapes
1.0 PDH (LA CES/non-HSW)
ASLA Online Learning Lab presented by Esri

Tech Demo’s 
2:15-2:45pm ET: SiteMarker
3:00-3:30pm ET: Land F/X

Tech Day registration is FREE for ASLA members.

Image: Lagos, Nigeria City. Growth from 2013 to 2024 / Renia Kagkou, Esri, Satellite Data: USGS, Landsat 8

  • Contains 1 Component(s) Includes a Live Web Event on 08/20/2026 at 1:00 PM (EDT)

    Learn how Geospatial AI can be used to identify land cover patterns and measure landscape change when data is limited or unavailable. This session explores approaches for extracting land cover data and analyzing, measuring, and visualizing landscape changes, such as forest loss and urban growth. Through the process, the presentation will highlight the limitations and strengths of machine learning for analysis and supporting design decisions.

    As human and natural environments are becoming increasingly intertwined and complex, understanding and visualizing landscape changes such as land cover changes, forest loss, and urban sprawl is a crucial part of our discipline. When data is not available or up to date, how can one begin to unpack and track these changes? This presentation explores how Geospatial AI (GIS and AI) can be used to generate data, track changes, measure them, and visualize them.  

    Attendees will learn how to extract landscape patterns and transformations from satellite imagery, to support analyses and design decisions. The presentation will first make an introduction to satellite imagery resources, color band compositions, and the appropriate use cases for each color band composition. Participants will learn about pre-trained machine learning models (MLM), the process of creating self-trained models, as well as the strengths and limitations of each method. Lastly, the session will cover how to measure landscape changes using the data created with machine-learning processes.  

    Whether addressing ecological preservation, development pressures, or long-term land use strategies, this presentation will demonstrate how emerging GIS technologies can help landscape architects better understand their sites and inform their design strategies.

    Learning objectives:

    • Generate actionable landscape information from satellite imagery using machine learning techniques. 
    • Evaluate the strengths and limitations of pre-trained machine learning models and identify when custom-trained models may be needed.
    • Identify and measure landscape changes over time, including forest loss, city expansion, and land-use transformation. 

    ASLA Online Learning Labs, available exclusively to ASLA members, allow you to learn from the best in the business. Tap into the knowledge of the people and companies that are transforming the future of our industry through emerging trends and techniques. Discover real world applications that will put your projects above the rest. 

    This Online Learning Lab is brought to you by: Esri

    Image: Oregon Land Cover 2015 (left) vs 2025 (right) / Renia Kagkou, Esri, Satellite Data: USGS, Landsat 8

    Renia Kagkou

    Renia Kagkou

    Senior Solution Engineer | Architecture, Urban Design, Planning - AEC

    Esri

    Renia Kagkou works at the intersection of spatial analysis (GIS), cartography, and urban planning and design. She is currently a Senior Lead at Esri for GIS tools that support the disciplines of Architecture, Urban Design, Landscape Architecture, and Urban Planning. She consults AEC firms on leveraging these tools to better understand project context, and to support decisions on planning the built environment. She also disseminates the value of GIS to the urban planning disciplines through conferences, panels, and academic engagements. 

    Renia is from Athens, Greece. She holds a Master of Architecture in Urban Design (MAUD) and a Master of Design Studies in Urbanism, Landscape, and Ecology (MDes ULE) from Harvard University, and a Bachelor of Architecture from Pratt Institute, New York. Prior to joining Esri, she worked as an architect in New York, and as a Geospatial consultant for firms and research projects in Massachusetts. Renia has also taught Mapping and GIS courses at SCI-Arc (Los Angeles), and for the Master Program on Architecture, European Urbanization and Globalization, at the University of Luxembourg (Belval).

  • Contains 1 Component(s) Includes a Live Web Event on 08/20/2026 at 2:15 PM (EDT)

    Description coming soon!

    Description coming soon!

  • Contains 1 Component(s) Includes a Live Web Event on 08/20/2026 at 3:00 PM (EDT)

    If you’re being asked more and more if you can collaborate in Revit, this is the session for you! We’ll showcase the multi-platform landscape architecture drafting tools in Land F/X, with a focus on the new Revit expansion. See how approachable it is if you already use AutoCAD or SketchUp.

    If you’re being asked more and more if you can collaborate in Revit, this is the session for you! We’ll showcase the multi-platform landscape architecture drafting tools in Land F/X, with a focus on the new Revit expansion. See how approachable it is if you already use AutoCAD or SketchUp.