2026 Big Sky GeoCon - From Data to Design

Esri’s GeoAI capabilities fuse advanced machine learning, deep learning, and spatial analysis to automate feature extraction and accelerate insight generation across imagery, video, point clouds, text, and other geospatial data sources. By integrating pretrained models, configurable geoprocessing tools, and extensible Python APIs, ArcGIS empowers users to rapidly transform raw sensor data into actionable information. These capabilities now extend directly into field workflows through Survey123’s computer vision integration, image classification and feature detection to validate field observations, streamline QA/QC, and enrich survey data collection with automated intelligence.

Building on advancements in large language models, Esri is enhancing GeoAI with natural-language-driven analysis and intelligent assistants that help users discover data, generate workflows, and interact with GIS more intuitively. LLM-powered text AI complements traditional feature extraction by enabling semantic understanding of unstructured content while Survey123’s vision-based automation strengthens the connection between field capture and enterprise analysis. Together, these innovations make spatial AI more accessible, scalable, and efficient by unlocking new levels of productivity for analysts, field crews, and decision-makers across industries.

In the United States, the digital divide increasingly reflects uneven digital transformation within state government institutions rather than consumer connectivity. Many agencies continue to rely on paper-based workflows and siloed legacy systems, limiting data sharing, interoperability, and enterprise decision-making. This presentation examines the transition from fragmented analog environments to integrated enterprise platforms, using DOT right-of-way mapping and statewide broadband mapping as case studies. These examples illustrate how inconsistent data standards, governance models, funding constraints, and workforce capacity slow modernization. The session emphasizes data democratization and workforce education as critical drivers of resilient, transparent, and effective state government enterprise systems.

This session highlights how GeoAI and 3D street-level data are transforming modern infrastructure management. Using high-fidelity mobile mapping, road networks are driven, digitized, and analyzed at scale—capturing assets and conditions with unprecedented detail. From traffic signs and guardrails to pavement analysis, computer vision and AI unlock actionable insights that enhance safety, support long-term planning, and improve public works operations. Attendees will gain a clear view of how street-level digital twins and AI analytics are modernizing asset management, including real project use cases from City of Bozeman.

Street Sweeping and Winter Weather Operations empower public works agencies to monitor real-time service activity, measure performance, and keep communities informed. By tracking sweeper and snowplow routes, organizations can improve service levels, meet regulatory requirements, and optimize responses to storms and seasonal conditions. Sharing clear schedules and status updates increases transparency, supports resident planning, and strengthens public trust. Together, these solutions streamline operations, enhance roadway safety, and help agencies manage resources efficiently while maintaining cleaner, safer, and more resilient transportation networks.

Join us for an open GIS Imagery Forum dedicated to answering your toughest questions about imagery-driven workflows. Whether you're working with UAV, aerial, or satellite data, building digital twins, leveraging geospatial video or oriented imagery, or supporting inspection and asset management workflows, this session provides a collaborative space to explore best practices, emerging capabilities, and real‑world applications. Bring your questions and challenges and let’s work together to tackle the full spectrum of questions around modern GIS imagery workflows.

Geospatial tools play a crucial role in modern stream restoration by supporting accurate assessment, design, construction, and monitoring. This presentation highlights the integrated use of UAS, surveying, LiDAR, GPS enabled equipment, and GIS to collect, analyze, and implement high-resolution spatial data for stream and floodplain restoration. These technologies improve design efficiency, reduce time/cost, and support informed decision-making throughout the restoration project, from initial assessment through post-construction monitoring.

SWCA Environmental Consultants (formerly River Design Group) was retained by MT Fish, Wildlife, and Parks and the Jefferson Local Development Corporation to design a wetland restoration project at the Piedmont Wetlands south of Whitehall, Montana. Data collection for wetland restoration design development included pond bathymetry, topography, vegetation, wetland delineation and wetland functional assessment. Field data were used for the basis of restoration design, and the supporting GIS analysis included LiDAR surface analysis and clarification of historical alterations to the system. Spatial and 3D analysis as well as conceptual design drafting were completed in the ArcGIS Pro platform.

Vibe coding is an ongoing conversation between human intuition and machine generation, merging precision with perception. In this talk, we’ll explore how that dialogue shapes the development of a web mapping application built with Esri’s Maps SDK for JavaScript and Calcite Design System. By iteratively refining prompts, evaluating AI-generated code, and tuning the design, we’ll trace how the “feel” of a GIS app can emerge from the workflow itself. Whether you write code already or just appreciate good vibes, this session invites you to explore how subtle process shifts can make geospatial tech come alive.