@article{starek_chu_mitasova_harmon_2020, title={Viewshed simulation and optimization for digital terrain modelling with terrestrial laser scanning}, volume={41}, ISSN={["1366-5901"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85087281550&partnerID=MN8TOARS}, DOI={10.1080/01431161.2020.1752952}, abstractNote={The main objective of this study is the development of a simulation and optimization method for wide-area terrain mapping with terrestrial laser scanning (TLS). The problem can be stated as follows...}, number={16}, journal={INTERNATIONAL JOURNAL OF REMOTE SENSING}, author={Starek, Michael J. and Chu, Tianxing and Mitasova, Helena and Harmon, Russell S.}, year={2020}, month={Aug}, pages={6409–6426} }
 @article{starek_mitasova_wegmann_lyons_2013, title={Space-Time Cube Representation of Stream Bank Evolution Mapped by Terrestrial Laser Scanning}, volume={10}, ISSN={["1558-0571"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84886592528&partnerID=MN8TOARS}, DOI={10.1109/lgrs.2013.2241730}, abstractNote={Terrestrial laser scanning (TLS) is utilized to monitor bank erosion along a stream that has incised through historic millpond (legacy) sediment. A processing workflow is developed to generate digital terrain models (DTMs) of the bank's surface from the TLS point cloud data. Differencing of the DTMs reveals that the majority of sediment loss stems from the legacy sediment layer. The DTM time series is stacked into a voxel model to form a space-time cube (STC). The STC provides a compact representation of the bank's spatiotemporal evolution captured by the TLS scans. The continuous STC extends this approach by generating a voxel model with equal temporal resolution directly from the point cloud data. Novel visualizations are extracted from the STCs to explore patterns in surface evolution. Results show that erosion is highly variable in space and time, with large-scale erosion being episodic due to bank failure within legacy sediment.}, number={6}, journal={IEEE GEOSCIENCE AND REMOTE SENSING LETTERS}, author={Starek, M. J. and Mitasova, H. and Wegmann, K. W. and Lyons, N.}, year={2013}, month={Nov}, pages={1369–1373} }
 @article{starek_vemula_slatton_2012, title={Probabilistic detection of morphologic indicators for beach segmentation with multitemporal LiDAR measurements}, volume={50}, number={11}, journal={IEEE Transactions on Geoscience and Remote Sensing}, author={Starek, M. J. and Vemula, R. and Slatton, K. C.}, year={2012}, pages={4759–4770} }
 @article{starek_mitasova_hardin_weaver_overton_harmon_2011, title={Modeling and analysis of landscape evolution using airborne, terrestrial, and laboratory laser scanning}, volume={7}, ISSN={["1553-040X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84858779393&partnerID=MN8TOARS}, DOI={10.1130/ges00699.1}, abstractNote={Current laser scanning (Lidar, light detection and ranging) technologies span a wide range of survey extent and resolutions, from regional airborne Lidar mapping and terrestrial Lidar field surveys to laboratory systems utilizing indoor three-dimensional (3D) laser scanners. Proliferation in Lidar technology and data collection enables new approaches for monitoring and analysis of landscape evolution. For example, repeat Lidar surveys that generate a time series of point cloud data provide an opportunity to transition from traditional, static representations of topography to terrain abstraction as a 3D dynamic layer. Three case studies are presented to illustrate novel techniques for landscape evolution analysis based on time series of Lidar data: (1) application of multiyear airborne Lidar surveys to a study of a dynamic coastal region, where the change is driven by eolian sediment transport, wave-induced beach erosion, and human intervention; (2) monitoring of vegetation growth and the impact of landscape structure on overland flow in an agricultural field using terrestrial laser scanning; and (3) investigation of landscape design impacts on overland water flow and other physical processes using a tangible geospatial modeling system. The presented studies demonstrate new insights into landscape evolution in different environments that can be gained from Lidar scanning spanning 1.0–0.001 m resolutions with geographic information system analysis capabilities.}, number={6}, journal={GEOSPHERE}, author={Starek, Michael J. and Mitasova, Helena and Hardin, Eric and Weaver, Katherine and Overton, Margery and Harmon, Russell S.}, year={2011}, month={Dec}, pages={1340–1356} }