GIS in Action 2025

Can you confidently find your next conference session, the nearest exit, or a restroom? Come learn about options for navigating the venue. Sorry, no cheese… Have a map instead!

We’ll get familiar with the venue while evaluating strengths, weaknesses, and trade-offs of this year’s conference maps and apps. Consider it a case study for technology selection, indoor reality capture, oriented imagery, and challenges in human wayfinding.

Bring your critical eye and thinking cap! Your questions and feedback will help improve next year’s experience.

An overview of the GIS analyses that are a part of Metro's Cooling Corridors study, which is aimed at understanding the distribution of cool and hot, natural and built corridors in the region, and identifying opportunities for connecting existing cool areas or conversely identifying the hot areas that would most benefit from cooling interventions.

Every year, Oregon’s Department of Environmental Quality publishes a general statistical overview of status and tends of water quality across Oregon using the Oregon Water Quality Index. The index, which DEQ has calculated for more than three decades, analyzes a defined set of water quality parameters and produces scores that describe the general water quality within a network of 160 stations located in streams throughout the State of Oregon. GIS plays a critical role in not only understanding where changes are occurring in the State, but also to communicate the overall water quality of Oregon’s rivers in an easy-to-understand, non-technical manner to the public, agency managers, and the Oregon Legislature.

Using geoprocessing tools available in ArcGIS Pro and published layers from ESRI’s Living Atlas and ArcGIS Online, DEQ is able to map wildfire perimeters, land use changes, and watershed boundaries to determine which recent changes are likely negatively impacting the water quality within the OWQI’s network of stations. DEQ uses tools available through ArcGIS Online such as Experience Builder, Story Maps, and Dashboards to communicate the results of the OWQI with members of the public and Oregon Legislators who are interested in monitoring water quality throughout the State.

This presentation highlights the importance of accessibility in GIS and mapping, emphasizing design considerations for users with diverse abilities. It covers practical strategies for creating accessible maps and apps, including planning, color contrast, basemap selection, and symbology.

In 2024 the Department of Justice issued a new rule on the accessibility of web content and mobile apps provided by state and local governments. This rule updates regulations for Title II of the Americans with Disabilities Act (ADA) and requires that most state and local government website content meet the Web Content Accessibility Guidelines (WCAG) Version 2.1, Level AA standards. In this presentation I’ll discuss LPRO's response upon learning about the rule, as well as how we’re assessing our currently available products and reviewing our processes to create new maps and apps.

The DOJ released new rules to make web applications accessible following the WCAG 2.1 by April 2026. The City of Portland is currently going through the process of developing standards and guidelines to comply with the new rule. We will be sharing our approach, the roadblocks, barriers, take aways, and more.

We developed and tested a method for mapping shade cast on water channels by riparian vegetation using imagery sources that are affordable and regularly available across Oregon. We validated the optical imagery-based results against lidar-based shade estimates that, while more accurate, are not viable for ongoing statewide monitoring due to their expense. This work provides insights toward determining a viable strategy for statewide monitoring of riparian vegetation condition, which could in turn support a data-driven prioritization and assessment framework to increase the efficiency, effectiveness and accountability of riparian restoration efforts.

We created a model to predict shade from 1-foot Oregon Statewide Imagery Program (OSIP) imagery and 10-meter Sentinel-2 satellite imagery, trained from shade estimated using solar-path modeling applied to lidar data collected over three disparate study areas. The model explains nearly 77% of the variation in lidar-derived shade across the study areas. NAIP-based models significantly outperformed Sentinel-2 models; we found that multi-scale image textural information derived from NAIP was important in creating accurate shade estimates. Maps of shade from the optical-based model were created over the entire Johnson Creek watershed in metropolitan Portland; visual inspection of the results shows a very high correspondence to photo-interpreted NAIP imagery, including accurate response to subtle and fine-scale variation in conditions.

What do fish, ecological restoration, and drones have in common? They all play a vital role in the Stage 0 restoration of Wasson Valley!
Stage 0 restoration is an innovative approach aimed at returning landscapes to their initial state, allowing nature to restore itself. Using drones to monitor these areas allows for landscape level analysis of the imagery collected, enhancing our ability to track and support the recovery process. This method of monitoring could reduce the amount of field work for future restoration sites. Scientific monitoring of habitat restoration has generally occurred on-the-ground with time-intensive efforts. Monitoring by UAS will allow for landscape-wide monitoring using multispectral, LiDAR and thermal sensors to track environmental changes resulting from the restoration, such as vegetation growth rate, sediment movement, elevation changes, and surface temperature of soil and water.

Debris flows are natural hazards that can damage ecosystems and infrastructure, especially in mountainous areas after wildfires. Debris flow mapping and inventory development provide the groundwork for understanding the frequency, spatial distribution, and key influencing parameters that help identify high-risk areas. This study evaluates parameters associated with post-fire debris flow mapping by analyzing lidar differencing, satellite imagery, and machine learning (ML) applications. The study area includes seven watersheds in the Columbia River Gorge, Oregon, USA. The combination of wildfires in 2017, followed by an intense rainstorm in 2021, led to multiple debris flow events in the area. Lidar and satellite imagery datasets from 2018 and 2021 are analyzed using machine learning algorithms: Random Forest, XGBoost, SVM, and logistic regression. In implementing these models, we focus on feature selection optimization and handling class imbalance. Random Forest and XGBoost performed best, achieving an F1 score of 85% to 90% in mapping debris flow locations. Spatial visualization of the results validated the models against historical data. Adding soil burn severity to the analysis highlights its influence on sediment erosion and vegetation patterns. The study showed that the watersheds with higher burn severity areas experienced more significant sediment erosion.