RedCastle Resources (RCR) partnered with the USFS to produce forest inventory models across the full extent of North Kaibab Ranger District (655,000 acres) bordering Grand Canyon National Park. Using a combination of Bayesian variable selection and linear regression modeling, we produced eight forest inventory models at a 20-meter spatial resolution. In addition, we worked with pre- and post-fire lidar data to detect post-fire changes in vegetation cover and height. We also produced a burn severity map based on canopy cover differencing and qualitatively compared it to existing fire severity products, including Monitoring Trends in Burn Severity and Rapid Assessment of Vegetation Condition after Wildfire data.

Following a catastrophic wildfire in New Mexico, monsoonal debris flows clogged stream channels and destroyed infrastructure. While scoping the project, we worked closely to understand the data needs of our customer and select the sensor type and UAS platform most appropriate for the project and site. By comparing high-resolution UAS lidar-measured elevation products with pre-event lidar sources, RedCastle Resources was able to estimate the depth and volume of eroded and deposited sediment with <10 cm vertical accuracy. Our analysts’ expertise in every step of the lidar processing pipeline and their familiarity with other remote sensing data sources allowed us to deliver on this project, providing change estimates, DEMs, DSMs, hydrological analysis, and aerial imagery.

Highly detailed terrain and imagery provides critical information for safety and sustainability. We conducted a comprehensive aerial lidar and imagery survey covering 1,800 acres across three active mining sites and two geohazard sites near Bozeman, Montana and West Yellowstone, Wyoming. Utilizing a UAS-based lidar sensor, we captured high-resolution elevation data and imagery. This centimeter-level accuracy dataset allows stakeholders to understand the terrain and vegetation to minimize environmental disturbances, identify potential hazards, and implement mitigation measures to ensure safety. This data supports the effectiveness of remediation efforts and helps optimize long-term stability.