Below are some drone-related publications by faculty and students affiliated with the Drone Lab.

Zhang, J., Okin, G. S., Zhou, B., & Karl, J. W. (2021). UAV‐derived imagery for vegetation structure estimation in rangelands: validation and application. Ecosphere, 12(11). Cite
Yoon, J., & Ryu, J. H. (2024). STEM Talk: Cultivating students’ STEM affinity and careers. Contemporary Mathematics and Science Education, 5(1), ep24006. Cite Download
Winford, E. M. (2024). Effects of Low-Tech Process-Based Restoration Approaches on the Hydrology, Geomorphology, and Vegetation of a Rangeland Riparian Complex [PhD Thesis]. University of Idaho - College of Graduate Studies. Cite
Whiting, M., Salley, S. W., James, D. K., Karl, J. W., & Brungard, C. W. (2020). Rapid bulk density measurement using mobile device photogrammetry. Soil Science Society of America Journal, saj2.20063. Cite
Weygint, W. A., Eitel, J. U. H., Maguire, A. J., Vierling, L. A., Johnson, D. M., Campbell, C. S., & Griffin, K. L. (2023). Leaf temperatures and environmental conditions predict daily stem radial variations in a temperate coniferous forest. Ecosphere, 14(3), e4465. Cite Download
Steinwurtzel, M. R., Karl, J. W., & Kennedy, B. (in prep). Mapping the Thermal Flow: Best Practices in River and Riparian Temperature Monitoring  with TIR Imagery. Remote Sensing in Ecology and Conservation. Cite
Shrestha, A., Hicke, J. A., Meddens, A. J. H., Karl, J. W., & Stahl, A. T. (2024). Evaluating a Novel Approach to Detect the Vertical Structure of Insect Damage in Trees Using Multispectral and Three-Dimensional Data from Drone Imagery in the Northern Rocky Mountains, USA. Remote Sensing, 16(8), 1365. Cite
Ryu, J. H., Clements, J., & Neufeld, J. (2022). Low-Cost Live Insect Scouting Drone: iDrone Bee. Journal of Insect Science, 22(4), 5. Cite
Ryu, J. H. (2022). UAS-based real-time water quality monitoring, sampling, and visualization platform (UASWQP). HardwareX, 11, e00277. Cite Download
Ryu, J. H. (2022). Prototyping a low-cost open-source autonomous unmanned surface vehicle for real-time water quality monitoring and visualization. HardwareX, 12, e00369. Cite
Lad, L. E., Tinkham, W. T., Sparks, A. M., & Smith, A. M. S. (2023). Evaluating Predictive Models of Tree Foliar Moisture Content for Application to Multispectral UAS Data: A Laboratory Study. Remote Sensing, 15(24), 5703. Cite
Kobziar, L. N., Vuono, D., Moore, R., Christner, B. C., Dean, T., Betancourt, D., Watts, A. C., Aurell, J., & Gullett, B. (2022). Wildland fire smoke alters the composition, diversity, and potential atmospheric function of microbial life in the aerobiome. ISME Communications, 2(1), 8. Cite Download
Kobziar, L. N., Lampman, P., Tohidi, A., Kochanski, A. K., Cervantes, A., Hudak, A. T., McCarley, R., Gullett, B., Aurell, J., Moore, R., Vuono, D. C., Christner, B. C., Watts, A. C., Cronan, J., & Ottmar, R. (2024). Bacterial Emission Factors: A Foundation for the Terrestrial-Atmospheric Modeling of Bacteria Aerosolized by Wildland Fires. Environmental Science & Technology, 58(5), 2413–2422. Cite
Karl, J. W., Gillan, J. K., Barger, N. N., Herrick, J. E., & Duniway, M. C. (2014). Interpretation of high-resolution imagery for detecting vegetation cover composition change after fuels reduction treatments in woodlands. Ecological Indicators, 45, 570–578. Cite
Karl, J. W., Yelich, J. V., Ellison, M. J., & Lauritzen, D. (2020). Estimates of Willow (Salix Spp.) Canopy Volume using Unmanned Aerial Systems. Rangeland Ecology & Management, 73(4), 531–537. Cite Download
Jones, C. W., III. (2021). Developing and Implementing a UAS-Based Reach-Scale Protocol to Understand and Test Indicators for Monitoring Beaver Dam Analog Effectiveness. ProQuest Dissertations Publishing. Cite
Hellman, I., Heinse, R., Karl, J. W., & Corrao, M. (2020). Detection of Terracettes in Semi-Arid Rangelands Using Fourier-Based Image Analysis of Very High-Resolution Satellite Imagery: Detection of Terracettes Using Fourier-Based Image Analysis. Earth Surface Processes and Landforms. Cite
Harrison, G. R., Shrestha, A., Strand, E. K., & Karl, J. W. (2024). A comparison and development of methods for estimating shrub volume using drone‐imagery‐derived point clouds. Ecosphere, 15(5), e4877. Cite
Gillan, J., Karl, J., Elaksher, A., & Duniway, M. (2017). Fine-Resolution Repeat Topographic Surveying of Dryland Landscapes Using UAS-Based Structure-from-Motion Photogrammetry: Assessing Accuracy and Precision against Traditional Ground-Based Erosion Measurements. Remote Sensing, 9(5), 437. Cite
Gillan, J. K., Karl, J. W., Barger, N. N., Elaksher, A., & Duniway, M. C. (2016). Spatially Explicit Rangeland Erosion Monitoring Using High-Resolution Digital Aerial Imagery. Rangeland Ecology & Management, 69(2), 95–107. Cite
Gillan, J. K., Karl, J. W., & van Leeuwen, W. J. D. (2020). Integrating drone imagery with existing rangeland monitoring programs. Environmental Monitoring and Assessment, 192(5), 269. Cite
Cunliffe, A. M., Anderson, K., Boschetti, F., Brazier, R. E., Graham, H. A., Myers‐Smith, I. H., Astor, T., Boer, M. M., Calvo, L. G., Clark, P. E., Cramer, M. D., Encinas‐Lara, M. S., Escarzaga, S. M., Fernández‐Guisuraga, J. M., Fisher, A. G., Gdulová, K., Gillespie, B. M., Griebel, A., Hanan, N. P., … Wojcikiewicz, R. (2021). Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems. Remote Sensing in Ecology and Conservation, rse2.228. Cite
Chen, G., Li, L., Shi, Z., & Shang, B. (2023). Aerial Nondestructive Testing and Evaluation (aNDT&E). Materials Evaluation, 81(1), 67–73. Cite
Cao, H., Gao, Y., Cai, W., Xu, Z., & Li, L. (2023). Segmentation Detection Method for Complex Road Cracks Collected by UAV Based on HC-Unet++. Drones, 7(3), 189. Cite Download