ID: 2212
Presenting Author: Liam Bindle
Session: 665 - Planning Support Systems for Environmental Assessment and Urban Decision-Making
Status: pending
We present our approach for creating custom digital twins of Canadian landscapes for decision support tools and assessments of cumulative effects and development scenario modeling.
Landscape simulation models support environmental assessment by providing a strategic view of cumulative effects and forecasting ecological responses to development proposals. In this talk, we present our approach to building customizable digital twins of Canadian landscapes that power scenario-based decision support tools in the ALCES platform. Our data preparation framework uses computation graphs to assemble data from publicly available sources through standardized workflows that can be customized to incorporate non-public data when available. Landscape dynamics—including land-use change, forestry, and wildfire—are simulated using empirical models trained with machine learning on historical data. This approach avoids subjective parameterization and allows decision-makers to adjust factors such as development rates, zoning, and reclamation without requiring specialized modeling expertise. To support large-scale, high-resolution analyses, computation is distributed across multiple servers using the Message Passing Interface (MPI). Together, these design choices have greatly improved the cost-effectiveness and timeliness of developing decision support tools. By combining scalable computation, empirical modeling, open data integration, and custom user-interfaces, our framework is enabling exploration of future landscape scenarios to support informed, transparent decisions in a rapidly changing environment.
Liam Bindle works on the Cumulative Effects Team at Integral Ecology Group. He leads the development of the ALCES platform and he is based out of Sechelt, British Columbia.
Coauthor 1: Matt Carlson
Coauthor 2: Matt Bonnyman
Coauthor 3: Chad Belisle