Hoyt Architects

Research and White Papers

We offer research-driven insights at the intersection of architectural visualization, digital twin technology, and artificial intelligence. Each publication below reflects Hoyt Architects’ commitment to advancing the field through rigorous inquiry and forward-thinking perspectives, providing practitioners, academics, and industry partners with a valuable resource for navigating the evolving built environment.

Decision Intelligence for the Florida Wildlife Corridor

Advancing Digital Twins for Conservation & Land-Use Planning

Overview

As Florida continues to experience rapid growth, nearly 60,000 acres of natural and agricultural land are lost each year. This research initiative, led by the University of Florida Center for Landscape Conservation Planning, explores how digital twin technology and decision intelligence can support more informed, transparent conservation and land-use planning across the Florida Wildlife Corridor Foundation.

The project aims to develop a scalable ecological digital twin — an interactive planning environment that integrates GIS modeling, ecological data, and scenario analysis to help stakeholders evaluate conservation, resilience, connectivity, and future growth impacts over time.

Key Objectives

  • Develop a scalable ecological digital twin framework
  • Support scenario-based conservation and land-use planning
  • Identify fragmentation risks and ecological tipping points
  • Integrate resilience, ecosystem services, and connectivity analysis
  • Create a transferable model for future conservation planning initiatives

Research Focus Areas

  • Ecological digital twin development
  • Scenario planning and conservation modeling
  • Wildlife corridor resilience and connectivity
  • GIS and spatial intelligence integration
  • Land-use and infrastructure impact analysis

Why It Matters

Conservation decisions often rely on fragmented datasets and static planning tools. This initiative seeks to create a collaborative, data-driven environment where planners, agencies, nonprofits, and communities can test “what-if” scenarios and better understand long-term tradeoffs before decisions are made.

The framework supports:

  • Future growth and development analysis
  • Conservation prioritization
  • Regional resilience planning
  • Cross-jurisdiction collaboration
  • More transparent decision-making

 

 

 

 

Dunnellon Bottleneck Digital Twin

Pilot Project for the Florida Wildlife Corridor

Project Overview

The Dunnellon Bottleneck Pilot Project serves as the proof-of-concept for the broader Florida Wildlife Corridor Digital Twin initiative. Located across Marion, Levy, and Citrus Counties, the study area includes more than 18,000 acres of critical ecological linkages connecting waterways, habitats, and regional conservation networks.

As development pressure increases throughout Central Florida, the pilot explores how ecological digital twins can help guide proactive conservation and growth decisions before irreversible fragmentation occurs.

Pilot Goals

  • Develop an interactive digital twin for the Dunnellon region
  • Test conservation and growth-related scenarios
  • Support collaborative regional planning
  • Evaluate visualization and decision-support tools
  • Establish a scalable framework for statewide expansion

Initial Activities

  • Stakeholder and community engagement
  • Spatial data integration and modeling
  • Corridor connectivity analysis
  • Scenario development and testing
  • Visualization and planning tool exploration

Long-Term Vision

The Dunnellon pilot represents the first step toward a statewide ecological digital twin capable of supporting Florida’s long-term conservation, resilience, and land management goals across the full Florida Wildlife Corridor system.

 

 

Belinda B. Nettles, Ph.D., ASLA

Assistant Scholar

College of Design, Construction & Planning | Department of Landscape Architecture

University of Florida

Zoning-Aware Street View Image Generation

Research Initiative

Exploring how artificial intelligence can translate zoning codes into realistic street-level visualizations. By combining zoning data with real-world street imagery, this research investigates how AI-generated environments can help planners, designers, and communities better understand the visual impact of urban development patterns.

Focus Areas

  • AI-driven urban visualization
  • Zoning-informed image generation
  • Street-view and satellite data integration
  • Urban morphology and planning analysis
  • Public engagement and design communication

Research Goals

  • Generate realistic street-view imagery based on zoning classifications
  • Compare generated environments with existing urban conditions
  • Differentiate visual characteristics across zoning types such as residential, commercial, and mixed-use districts

Potential Applications

  • Urban planning and scenario testing
  • Community engagement and visualization tools
  • Design education and research
  • Digital twin and smart city initiatives

 

Shenhao Wang

Assistant Professor in Urban AI

Department of Urban and Regional Planning, DCP

University of Florida