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G. Trudeau and Lowell, K., Detecting Coral Reef Presence Using ICESat-2 Data and Machine Learning Methods, Canadian Hydrographic Conference 2024. p. Saint John's, Newfoundland, Canada, 2024.PDF icon Trudeau_Lowell_CHC2024_Abstract.pdf (62.92 KB)
K. Lowell and Rzhanov, Y., Episodic Satellite-Derived Depth Change from a Single Model Based on “Stacking” Multi-temporal Images, Canadian Hydrographic Conference. p. Saint John's, Newfoundland, Canada, 2024.PDF icon Lowell_Rzhanov_CHC2024_Abstract.pdf (99.3 KB)
E. Adediran, Lowell, K., Kastrisios, C., Rice, G., and Zhang, Q., Exploring Ancillary Parameters for Quantifying Interpolation Uncertainty in Digital Bathymetric Models, Marine Geodesy. Taylor & Francis Group, 2024.
K. Lowell, Global and Local Magnitude and Spatial Pattern of Uncertainty from Geographically Adaptive Empirical and Machine Learning Satellite Derived Bathymetry Models, GIScience and Remote Sensing, vol. 61(1). p. 2297549, 2024.PDF icon Lowell_Rzhanov_2023_GlblAndLocalSpatialUncertPatternFromGeogAdaptiveSDBModels.pdf (8.27 MB)
A. Granger and Lowell, K., Optimizing the Accuracy of Bathymetric Maps Developed Using Automated and Manual Techniques to Extract Training Data from ICESat-2 Data, Canadian Hydrographic Conference 2024. p. Saint John's, Newfoundland, Canada, 2024.PDF icon Granger_Lowell_CHC2024_Abstract.pdf (10.95 KB)
K. Lowell, Automated Machine Learning-based Extraction of Shallow Water Bathymetry from LiDAR Point Clouds: Developing an Operational Workflow Via Accuracy Analysis, U.S. Hydro 2023. p. Mobile, AL, 2023.PDF icon Lowell_etal_USHydro_2023.pdf (599.77 KB)
K. Lowell, Improving Shallow Water Nautical Charts Via Operational Automated Machine Learning-based Bathymetry Extraction from Airborne LiDAR Point Clouds, JALBTCX (Joint Airborne LiDAR Bathymetry Technical Center of Expertise) . p. Kiln, Mississippi, 2023.PDF icon JALBTCX2023_Abstract_KLowell_UNH.pdf (67.49 KB)
K. Lowell and Miles, B., Improving Shallow Water Nautical Charts Via Operational Automated Machine Learning-Based Bathymetry Extraction from Airborne LiDAR Point Clouds, JALBTCX 2023 (Joint Airborne Lidar Bathymetry Technical Center of Expertise). p. Kiln, MI, 2023.PDF icon JALBTCX2023_Abstract_KLowell_UNH.pdf (67.49 KB)
E. Adediran, Lowell, K., Kastrisios, C., and Rice, G., A Machine Learning Approach to Characterizing Uncertainty in Interpolated Bathymetric Datasets, 2023 US Hydro Conference. p. Mobile, AL, 2023.
J. Miksis-Olds, Martin, B., Lowell, K., Verlinden, C., and Heaney, K., Minimal COVID-19 Quieting Measured in the Deep, Offshore Waters of the U.S. Outer Continental Shelf, Journal of the Acoustical Society of America Express Letters, vol. 2(9). p. 090801, 2022.
K. Lowell and Calder, B. R., Operational Performance of a Combined Density- and Clustering-based Approach to Extract Bathymetry Returns from LiDAR Point Clouds, International Journal of Applied Earth Observation and Geoinformation (Special Issue: Recent Advances in Geocomputation and GeoAI for Mapping), vol. 107. p. 102699, 2022.
K. Lowell and Calder, B. R., Assessing Marginal Shallow-Water Bathymetric Information Content of Lidar Sounding Attribute Data and Derived Seafloor Geomorphometry, Remote Sensing, vol. 13(9), 1604. MDPI, 2021.PDF icon lowell-calder-2021-remotesensing-13-01604.pdf (3.71 MB)
J. Pierce, Butler, M. J., Rzhanov, Y., Lowell, K., and Dijkstra, J. A., Classifying 3-D Models of Coral Reefs Using Structure-from-Motion and Multi-View Semantic Segmentation, Frontiers in Marine Science, vol. 8:706674. 2021.
K. Lowell and Calder, B. R., Extracting Shallow-water Bathymetry from Lidar Point Clouds Using Pulse Attribute Data: Merging Density-based and Machine Learning Approaches, Marine Geodesy, vol. 44(4) (DOI: https://doi.org/10.1080/01490419.2021.1925790). Taylor and Francis, pp. 259-286, 2021.
H. Kates Varghese, Lowell, K., and Miksis-Olds, J., Global-Local-Comparison Method: Understanding Marine Mammal Spatial Behavior by Applying Spatial Statistics and Hypothesis Testing to Passive Acoustic Data, Frontiers in Marine Science, vol. 8:625322. 2021.
K. Lowell, Calder, B. R., and Lyons, A. P., Measuring Shallow-water Bathymetric Signal Strength in Lidar Point Attribute Data Using Machine Learning, International Journal of Geographical Information Science, vol. 35(8) (DOI:10.1080/13658816.2020.1925790). Taylor and Francis, pp. 1592-1610, 2021.
D. C. Wilford, Miksis-Olds, J., Martin, S. B., Howard, D. R., Lowell, K., Lyons, A. P., and Smith, M., Quantitative Soundscape Analysis to Understand Multidimensional Features, Frontiers in Marine Science, vol. 8:672336. 2021.
H. Kates Varghese, Lowell, K., Miksis-Olds, J., DiMarzio, N., Moretti, D., and Mayer, L. A., Spatial Analysis of Beaked Whale Foraging During Two 12 kHz Multibeam Echosounder Surveys, Frontiers in Marine Science, vol. 8:654184. 2021.
K. Lowell, Calder, B. R., and Lyons, A. P., Developing Machine Learning Models for Quality Assurance and Continuous Improvement of Bathymetry Extraction from Lidar Point Clouds, Canadian Hydrographic Conference. Quebec City, Quebec, Canada, 2020.PDF icon Lowell_Calder_CHC2020_Final.pdf (638.59 KB)
H. Kates Varghese, Miksis-Olds, J., DiMarzio, N., Lowell, K., Linder, E., Mayer, L. A., and Moretti, D., The Effect of Two 12 kHz Multibeam Mapping Surveys on the Foraging Behavior of Cuvier’s Beaked Whales Off of Southern California, Journal of the Acoustical Society of America, vol. 147(6). Acoustical Society of America, pp. 3849-3858, 2020.
J. Pierce, Rzhanov, Y., Lowell, K., and Dijkstra, J. A., Reducing Annotation Times: Semantic Segmentation of Coral Reef Survey Images, Global Oceans 2020. IEEE, U.S. Gulf Coast, Biloxi, MS, USA, pp. 1-9, 2020.
K. Lowell and Calder, B. R., Improving Extraction of Bathymetry from Lidar Using Machine Learning, 20th Annual Coastal Mapping & Charting Workshop of the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). p. Notre Dame, IN, 2019.
K. Lowell and Calder, B. R., Machine Learning Strategies for Enhancing Bathymetry Extraction from Imbalanced Lidar Point Clouds, Oceans 2019. IEEE, Seattle, WA, 2019.PDF icon Oceans2019_KLowell_BCalder_190523-005.pdf (741.12 KB)
K. Lowell and Calder, B. R., Machine Learning Strategies for Enhancing Bathymetry Extraction from Imbalanced Lidar Point Clouds, Oceans '19. IEEE, Seattle, WA, 2019.