Development of an open-source analytical Digital Twin framework for environmental modelling and management
Identification
- Public canonical key
- doi:10.5194/isprs-archives-l-4-w1-2026-227-2026
- Authors
- Luke Parkinson · Matthew D. Wilson
- Reported year
- 2026
- Reported language
- en
- Source type
- article
- First detected
- 2026-11-09T19:04:47.777372+00:00
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- 2026-11-09T19:04:47.777372+00:00
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Institutions reported by the source
University of Canterbury
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NZ
Documentary abstract — original language
Abstract. Environmental Digital Twins are dynamic virtual representations of physical environments that support real-time monitoring, scenario modelling, and community decision-making, that hold significant promise for addressing complex environmental challenges. Yet the development of each new system typically requires substantial duplicated engineering effort, and open-source frameworks specifically designed for environmental applications remain scarce. We present the Environmental Digital Data Intelligence Engine (EDDIE), a free and open-source framework (AGPL-3.0) for building environmental Digital Twins, developed at the Geospatial Research Institute Toi Hangarau. EDDIE assembles proven free and open-source geospatial (FOSS4G) components including PostGIS, GeoServer, TerriaJS, and a Python processing stack into a modular, containerised architecture. A plugin-based module system allows domain-specific environmental models to be registered and orchestrated within a shared infrastructure, while OGC-standard service interfaces (WPS, WFS, WMS) ensure interoperability with external tools and other Digital Twin instances. EDDIE underpins three operational applications: the Flood Resilience Digital Twin (FReDT), which automates compound flood inundation modelling under climate change scenarios; the Ōtākaro Digital Twin, an environmental monitoring and modelling platform for the Ōtākaro/Avon River developed with hapū Ngāi Tūāhuriri and Christchurch City Council; and Te Awarua Kai Ora, a community hydrodynamic modelling and story-mapping platform for Te Awarua / Porirua Harbour. We describe the EDDIE architecture, present performance benchmarks for FReDT, and discuss EDDIE’s potential as a reusable community framework for the open environmental Digital Twin ecosystem.
Identifiers
- OPENALEX
- W7204644334
- DOI
- 10.5194/isprs-archives-l-4-w1-2026-227-2026
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- Scholarship
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- article
- Natural entities mentioned
- River · Ecosystem
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OpenAlex · Record 1 · Record 2
- DOI · https://doi.org/10.5194/isprs-archives-l-4-w1-2026-227-2026
- OpenAlex · https://openalex.org/W7204644334
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Cite this reference
Luke Parkinson; Matthew D. Wilson. Development of an open-source analytical Digital Twin framework for environmental modelling and management. 2026. https://doi.org/10.5194/isprs-archives-l-4-w1-2026-227-2026
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- APA
- Luke Parkinson; Matthew D. Wilson. (2026). Development of an open-source analytical Digital Twin framework for environmental modelling and management. https://doi.org/10.5194/isprs-archives-l-4-w1-2026-227-2026
- Chicago
- Luke Parkinson; Matthew D. Wilson. Development of an open-source analytical Digital Twin framework for environmental modelling and management. 2026. https://doi.org/10.5194/isprs-archives-l-4-w1-2026-227-2026
- ISO 690
- Luke Parkinson; Matthew D. Wilson. Development of an open-source analytical Digital Twin framework for environmental modelling and management. 2026. https://doi.org/10.5194/isprs-archives-l-4-w1-2026-227-2026
UDTR Global Rights of Nature Legal Library. Development of an open-source analytical Digital Twin framework for environmental modelling and management. Documentary record: https://www.declarationuniverselledesdroitsdelarbre.org/global-rights-of-nature-radar/reference/r-7adedfb2d7a8b0c078b68f1ef5c34efe/ · Last HTTP verification: not performed
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Version a82a978ff18e65f2 · udtr-reference-1.1.2
- Title
- OpenAlex · source · 2026-11-09T19:04:47.777372+00:00
- Authors
- OpenAlex · source · 2026-11-09T19:04:47.777372+00:00
- Year
- OpenAlex · source · 2026-11-09T19:04:47.777372+00:00
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- OpenAlex · source · 2026-11-09T19:04:47.777372+00:00
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- OpenAlex · source · 2026-11-09T19:04:47.777372+00:00
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aeb08e9b00a825cb · 2026-11-09T19:04:47.777372+00:00
a4ce41c27ad443f2 · 2026-11-09T19:04:47.777372+00:00
0ee3dd46697afd2f · 2026-11-09T19:04:47.777372+00:00
a82a978ff18e65f2 · 2026-11-09T19:04:47.777372+00:00
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Discovery source · https://doi.org/10.5194/isprs-archives-l-4-w1-2026-227-2026
Discovery source · https://openalex.org/W7204644334
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