Highway 255 Samoa Mitigation Parcel: I published a paper in the Cal Poly Humboldt Ideafest journal about investigating the efficacy of Digital Aerial Photography (DAP) advancements facilitated by small Unmanned Aerial Systems (sUAS), with a focus on the DJI Mavic 3 Multispectral (M) quadcopter. Utilizing high-resolution RGB and multispectral cameras, alongside Real-Time Kinematic (RTK) capabilities, the Mavic 3M enables precise georeferencing without ground control points (GCPs). A drone flight mission over the Samoa Mitigation Parcel (SMP) on March 8th, 2024, showcased the Mavic 3M's ability to capture centimeter-grade resolution imagery for vegetation remote sensing. Spectral indices derived from the collected imagery, including NDWI, NDRE, and NDVI, facilitated analysis of water content, vegetation chlorophyll content, and overall vegetation health within the SMP. Results highlight the potential of sUAS-based remote sensing techniques to inform land management and environmental conservation efforts with detailed and precise information at a reliable temporal resolution.

Link to paper: https://www.nardigeospatial.com/s/sUAS_Applications.pdf

Schatz Demonstration Tree Farm: In collaboration with Dr. Tawanda Gara at Cal Poly Humboldt, I contributed to the development of Leaf Area Index (LAI) prediction rasters by integrating field-derived spectrometer data with satellite imagery, aimed at improving forest management practices at the Schatz Demonstration Tree Farm. This study offered an innovative approach to modeling LAI within California’s Mixed Evergreen forests by utilizing Sentinel-2 Multispectral Instrument (MSI) data in combination with ground-based LAI measurements. Using the Random Forest machine learning algorithm, we sought to create a robust LAI prediction model to better understand forest health dynamics in the context of ecological threats. Through rigorous data acquisition, preprocessing, and validation, we constructed a comprehensive LAI modeling framework tailored to the specific characteristics of the study area. The results demonstrated strong performance metrics, showcasing the model's ability to accurately capture LAI variability. This research was presented by Dr. Tawanda Gara at the Association of Pacific Coast Geographers (APCG) conference on October 3rd, 2024.

Link to paper: https://www.nardigeospatial.com/s/LAI.pdf

Link to presentation: https://www.nardigeospatial.com/s/LAI_Presentation.pdf