2026 Big Sky GeoCon - From Data to Design

Illegal dumping in remote areas has surged by up to 30%, threatening ecosystems and public health. Traditional monitoring methods can’t keep pace—limited access and resources leave agencies reactive instead of proactive. This presentation highlights how satellite imagery and AI analytics revolutionize enforcement. Using Antelope Valley, CA as a case study, we’ll show how high-resolution imagery, cloud-based detection, and GIS dashboards cut patrol time, improve safety, and accelerate investigations. We’ll share a vision for AI-driven tools that turn complex geospatial data into actionable strategies, enabling agencies to protect natural resources and combat dumping with unprecedented efficiency.

A large rainfall event triggered multiple landslides across Bridger Bowl Ski Area in southwest Montana on July 29, 2025. The Geospatial Core Facility at Montana State University conducted a UAV-based LiDAR survey over a landslide path along the northern boundary of Bridger Bowl and generated a 1-m resolution post-event digital elevation model (DEM). A pre-event 1-m DEM was obtained from the U.S. Geological Survey. Raster differencing between the pre- and post-event DEMs was used to estimate a volumetric displacement of 16,000 m3. These results demonstrate the value of UAV LiDAR for post-event landslide assessment and terrain management in alpine environments.

Extreme heat and rapid urbanization are converging challenges for the Arabian Peninsula, yet their fine-grained interactions remain poorly understood. We present a high-resolution assessment of land-cover land-use change, population growth, and land surface temperature (LST) from 2000 to 2020. We found that newly urbanized areas converted from desert exhibited significantly lower warming (+1.78°C) than existing urban areas (+2.39°C) and unchanged desert (+2.97°C). However, these newly urbanized areas maintained higher mean LST than existing urban areas by 2020 (42.68°C versus 41.29°C), creating a counter intuitive thermal where 13.1 million new residents live in places that experienced relative cooling yet higher absolute LST exposure. We furthermore identified distinct population-thermal pathways: small Gulf states achieved population growth with minimal warming through densification, while larger countries showed sprawl-dominated patterns with varied thermal outcomes. Our findings demonstrate that desert cities experience fundamentally different thermal dynamics than temperate regions and require a revised adaptation framework accounting for urban cooling potential and extreme baseline temperatures.

Federal wildfire fuel reduction projects lack systematic methods for identifying affected populations. The Wildfire Adapted Missoula project authorizes hazardous fuels treatments without environmental justice analysis despite federal mandates. This study develops a parcel-level, terrain-aware distance decay framework to identify affected populations based on spatial accessibility. Using the Blue Mountain treatment area, three distance metrics are compared: Euclidean (baseline planar distance), topographic (slope-adjusted), and fire transmission (cost-distance accounting for terrain and fuel conditions that constrain fire spread). Results inform environmental justice screening where spatial equity assessment remains absent from federal wildfire decision-making.

This presentation will focus on the GIS methods and challenges involved in structure surveying and inventory in the Yellowstone River Basin for Montana DNRC for the purpose of updating regulatory floodplain maps and how our GIS team utilized ArcGIS Field Maps to deploy structure and data forms for field crews to reference and collect data in the field. GIS field solutions proved themselves invaluable for daily and long-range planning for this project. Data collected was delivered in FEMA complaint databases comprised of structure location, information, and dimensions for 482 structures and 1446 bathymetric cross sections on 641 miles of river.

Many of the major themes within Environmental Education rely upon remote sensing and orbital data collection. This unit was developed to introduce students in grades 11-12 to the science behind the maps and graphics they see in class. It ranges from a review of the physics of the electromagnetic spectrum to data manipulation, ground-truthing, and ArcGIS workflows.
The unit begins with a physical modeling of active vs. passive sensing and spectral signatures, teaching students to recognize that every land cover—from healthy forest to impervious urban surfaces—possesses a unique "spectral fingerprint." Students use resources from NASA and the USGS to develop an understanding of how global change can be detected remotely.
As the unit progresses, students access primary data via USGS EarthExplorer, perform change-detection analysis of their local area using Landsat time-series data, and calculate the Normalized Burn Ratio (NBR) to model ecological disturbance. An infrared sensor and an air quality sensor are used to collect data around the school campus. This field data is crowdsourced via ArcGIS Survey123 and visualized alongside satellite imagery in ArcGIS Living Atlas in an attempt to demonstrate "ground-truthing." The unit culminates in an ArcGIS workflow that helps students build a comprehensive ArcGIS StoryMap portfolio detailing their learning progress throughout the unit.

Climate projection datasets pose major challenges for traditional GIS workflows due to their size and dimensionality. This study uses the NASA NEX-GDDP-CMIP6 dataset, comprising 65 years of historical simulations and four 85-year future scenarios across multiple models, totaling approximately 7.4 TB of data. To enable scalable analysis, we employ Dask and Xarray to construct spatiotemporal data cubes with lazy loading, chunking, and pixelwise computation. This workflow enables mesoscale GIS-ready analysis of changes in the thermodynamic drivers of humid-heat across the Arabian Peninsula.