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). https://doi.org/10/gnkd2p Cite

Yoon, J., & Ryu, J. H. (2024). STEM Talk: Cultivating students’ STEM affinity and careers. Contemporary Mathematics and Science Education, 5(1), ep24006. https://doi.org/10.30935/conmaths/14473 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. https://doi.org/10.1002/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. https://doi.org/10.1002/ecs2.4465 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. https://doi.org/10.3390/rs16081365 Cite

Ryu, J. H., Clements, J., & Neufeld, J. (2022). Low-Cost Live Insect Scouting Drone: iDrone Bee. Journal of Insect Science, 22(4), 5. https://doi.org/10.1093/jisesa/ieac036 Cite

Ryu, J. H. (2022). UAS-based real-time water quality monitoring, sampling, and visualization platform (UASWQP). HardwareX, 11, e00277. https://doi.org/10.1016/j.ohx.2022.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. https://doi.org/10.1016/j.ohx.2022.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. https://doi.org/10.3390/rs15245703 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. https://doi.org/10.1038/s43705-022-00089-5 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. https://doi.org/10.1021/acs.est.3c05142 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. https://doi.org/10.1016/j.ecolind.2014.05.017 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. https://doi.org/10.1016/j.rama.2020.03.001 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. https://doi.org/10.1002/esp.4971 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. https://doi.org/10.1002/ecs2.4877 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. https://doi.org/10.3390/rs9050437 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. https://doi.org/10.1016/j.rama.2015.10.012 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. https://doi.org/10.1007/s10661-020-8216-3 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. https://doi.org/10.1002/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. https://doi.org/10.32548/2023.me-04300 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. https://doi.org/10.3390/drones7030189 Cite Download