This session explores how geospatial technologies reveal change over time through the integration of remote sensing, UAV mapping, GIS, geodetic frameworks, and historical imagery. Presentations highlight applications in infrastructure management, shoreline monitoring, cultural resource documentation, and environmental assessment, demonstrating how past and present datasets can be combined to support better decisions and long-term stewardship.
1:30 PM – 1:45 PM
Remote Sensing as a Performance Assessment Tool: Monitoring Water Conveyance and Ecosystem Health in a Large-Scale River Restoration Project on the Middle Rio Grande
Presented by Suzanne Goldstein, Environmental Science Associates
On the Middle Rio Grande, a large-scale channel realignment project is addressing decades of sediment-driven river degradation, with the goal of improving conveyance efficiency while restoring habitat for species including the Rio Grande silvery minnow, the western yellow-billed cuckoo, and the southwestern willow flycatcher. The project area spans 20 river miles with limited road access, and river conditions can change significantly within days, which places practical limits on what field crews and fixed gage networks can monitor on their own.
This presentation describes the remote sensing framework developed to monitor hydrologic, geomorphic, and ecological performance across this river corridor following completion of realignment construction. It focuses on the role remote sensing will play alongside field data collection and hydraulic modeling in the overall monitoring program.
The monitoring plan will use daily high-resolution imagery as a primary data source, rather than as a periodic supplement to field visits. Daily image acquisition supports detection of short-duration events that occur between scheduled field visits or gage downloads, such as brief flood pulses, temporary channel drying during peak irrigation demand, or short-lived reconnection of side channels during snowmelt. This will be combined with SAR data from Sentinel-1 to supplement detection of floodplain activation during storm events, and high-resolution lidar to enhance habitat classification.
The framework relies on standard spectral indices, including NDVI for vegetation condition, and NDWI and NDTI for surface water presence and turbidity. Index values will be calibrated against historical field data, including past vegetation mapping and hydrologic records of known flood and drying events, to establish site-specific classification thresholds. Once thresholds are set, land cover classification can be produced automatically for each day that imagery is available, without manual interpretation of individual images. Time series analysis will provide additional insight on surface water continuity and ponding that threaten fish stranding. Floodplain activation combined with habitat classification provide additional data to support suitable habitat modeling. The remote sensing metrics will be used to identify pre-project baseline conditions and then conduct monitoring to support adaptive management and annual performance assessment.
The conditions driving this monitoring approach are common to other water systems in the Southwest, including the Colorado River Basin and other reaches of the Rio Grande, where drought, competing water demands, and endangered species requirements are recurring management considerations. A monitoring approach built around continuous, multi-sensor remote sensing can extend monitoring coverage across larger areas and longer time periods than field-based methods alone, at lower ongoing cost, while producing a continuous dataset suitable for adaptive management and regulatory reporting.
This presentation will cover the design of the monitoring framework, including sensor selection, the spectral index classification and thresholding approach, the combination of optical and radar data for habitat classification, and how these will be integrated with other in-situ and modeled measures of hydrologic and biologic conditions.
1:45 PM – 2:00 PM
From UAS-Based Shoreline Monitoring to Coastal Management: A Multi-Temporal Shoreline Change Assessment at Jupiter Inlet Lighthouse Outstanding Natural Area, Florida
Presented by Sudhagar Nagarajan and Varatharajaperumal Thangavel, Florida Atlantic University
Jupiter Inlet Lighthouse Outstanding Natural Area (ONA), located in Jupiter, southeast Florida, is managed by the Bureau of Land Management (BLM), and was designated as ONA by the U.S. Congress to preserve its nationally significant historic, natural, cultural, scientific, educational, scenic, and recreational values. Ecologically, the ONA supports over 700 documented plant and animal species. In addition, the site contains over 5,000 years of archaeological and cultural history.
Despite its protected status, shoreline erosion has emerged as one of the most significant threats to the long-term sustainability of the ONA. The northern part of the site is naturally protected by extensive mangrove vegetation serving as an effective buffer against wave action while limiting human disturbance. In contrast, the southern part lacks natural protection and has experienced progressive erosion over time, threatening coastal habitats. Understanding the magnitude, spatial variability, and driving mechanisms of shoreline change is therefore essential for developing scientifically informed coastal management strategies.
To address this need, Florida Atlantic University (FAU), has partnered with the BLM since 2017 to establish a long-term geospatial monitoring program aimed at documenting shoreline dynamics and providing quantitative evidence for coastal management decisions. Historical shorelines spanning 1953–2015 were extracted from archival aerial imagery, while biannual UAS surveys have been conducted before and after the Atlantic hurricane season each year since 2017 to capture 2D/3D changes.
A permanent baseline was established and transects spaced at 10-ft intervals were generated perpendicular to the baseline to quantify shoreline position through space and time. The extracted shorelines were analyzed using a shoreline change detection toolbox developed by the research team at FAU. The toolbox integrates the extracted shorelines with the predefined baseline and transects to automatically generate a matrix containing shoreline positions relative to the baseline for each transect across different time periods. This workflow significantly simplifies shoreline change analysis by organizing multi-temporal observations into a consistent analytical framework, enabling computation of average shoreline erosion, cumulative shoreline change, shoreline change rates for every transect, and long-term erosion trends.
In addition to quantifying shoreline dynamics, inferential analyses were performed to investigate relationships between shoreline change rates and oceanographic variables, providing insights into the environmental drivers of coastal erosion. The comprehensive dataset generated through this monitoring program has provided land managers with objective, quantitative evidence of shoreline vulnerability and erosion hotspots. These findings contributed to management actions initiated in 2025, including a hybrid shoreline stabilization project combining engineered shoreline protection with mangrove restoration and improved visitor management through designated trail systems and restricted beach access.
This presentation highlights the complete workflow from long-term UAS data acquisition to geospatial analysis, statistical interpretation, and management application, and demonstrates how sustained geospatial monitoring can directly support evidence-based coastal resilience planning and conservation of nationally significant coastal landscapes.
2:00 PM – 2:15 PM
A Modern Geodetic Framework for 1973 Aerial Photography: A Gallup, New Mexico Case Study
Presented by Robert Dzur, Bohannan Huston, Inc.
Historic aerial photography offers a unique point-in-time perspective, and its integration into present-day engineering studies is an emerging capability. Modern survey control, computational photogrammetry, and image-processing techniques are making it increasingly practical to transform archival film into usable historical geospatial context.
A practical, real-world use case using a 32-image block of 1973 Bureau of Land Management (BLM) color aerial photography acquired over Gallup, New Mexico, demonstrates a repeatable workflow for integrating historic aerial photography into an ongoing floodplain investigation. Project planning began with evaluation of original archival photography obtained from U.S. Government archives, image optimization, camera calibration reports, and documented photogrammetric theory developed during the original aerial mapping era. These principles were applied within today’s computational workflows to establish the capability of the historical imagery to develop orthophotography and terrain before field activities commenced. Preliminary orthophotography and terrain models then guided reconnaissance, identification of persistent candidate features, and development of field books for an RTK GNSS survey campaign.
The final photogrammetric adjustment integrates measured fiducial coordinates, original camera calibration parameters, and advanced deep-learning image masking for improved photogrammetric processing. These workflow components are then tied to the current control survey, establishing a field-supported geodetic reference framework for the reconstructed historical imagery and terrain. This geodetic framework makes the historical datasets directly compatible with modern geospatial products, allowing historical context to be incorporated into engineering investigations.
The resulting historical datasets provide a measurable predevelopment record of land use, terrain, and channel conditions that can be directly integrated with contemporary geospatial products. This additional historical context supports more informed interpretation of floodplain evolution and demonstrates how historic aerial photography can become a practical component of modern engineering workflows.
2:15 PM – 2:30 PM
The Power of Situational Awareness: Threading Geospatial Intelligence, Asset Visibility, and Machine Data Together to Build the Digital Mine
Presented by Elijah Williams, Epiroc
As mining operations continue their digital transformation journey, the challenge is no longer collecting data—it is turning data into actionable operational intelligence. While mines generate vast amounts of information from surveying, machine telemetry, and various monitoring systems, these data sources often remain siloed, limiting their value and impact. This presentation explores how the topic of situational awareness is transforming mining operations by integrating the most common data sources that provide the geospatial intelligence to paint a common operating picture. By combining real-time location information from personnel, fixed assets, equipment with machine health, operational status, and safety systems, mines can improve decision-making, enhance coordination, and gain unprecedented visibility across their operations.
Attendees will learn how integrated situational awareness supports safer operations through improved hazard recognition, collision avoidance, and emergency response readiness, while also driving productivity through better resource allocation, reduced downtime, and optimized workflows. The presentation will further examine how these connected data streams establish the digital foundation required for advanced automation and autonomous mining initiatives. Through practical industry examples and lessons learned, this session will demonstrate how modern mines are leveraging connected situational awareness to improve both safety and efficiency while accelerating the journey and growing the capabilities of today’s digital mining environment.
