Dr. Stephen Medeiros and his PhD student Milad Hooshyar were selected to participate in the Fall 2015 Cohort of the National Science Foundation’s Innovation Corps. Their team has an idea for bringing higher resolution wind and weather data to the aviation and consumer markets by using a simple, durable sensor with no moving parts. Together with their business mentor, Mr. Terry Pierce, they hope to discover more about the needs of their target customers and develop a viable business model for their future company, WindSwarm. To learn more about the I-Corps program at UCF, go to https://icorps.cie.ucf.edu/
A few weeks ago, I was using LAStools for a test on a small data set. LAStools are free to use on small lidar datasets; if you exceed the point limits a small amount of noise is injected into your output. This has always made me a little uncomfortable so I sent out the following tweet:
@rapidlasso is vital to lidar ecosystem but I disagree w/ injection of noise into data from unlicensed copies of lastools. point limits r ok— Stephen Medeiros (@scmphdpe) June 3, 2015
First, I noticed that Martin favorited the tweet. I anticipated that this was because he was preparing to respond. I was right.
However, his response was not what I expected (a tweet). He resent me an email exchange that we had in 2013 regarding this same issue. In that email, he concisely made the case for licensing his software for commercial use and supporting its development.
I sincerely appreciated his response in both cases, however I am still wary of the "injecting noise" method of license control, even if the amount of noise is very small. My fear is that those corrupt data could propagate from one to many naive users.
That being said, Rapid Lasso and LAStools have made numerous contributions to the lidar community, including an app to release data from the proprietary zlas format. The company also provides many avenues for academic and non-profit users to use LAStools at low to no cost. For details, go to the company's main website. Martin personally responds to comments posted in the forum so feel free to do that as well.
Anti-Disclaimer: As of this writing, I have no business relationship with Martin Isenburg or Rapid Lasso. I am simply reporting on an interaction I had with a person who I consider to be the worldwide ambassador for lidar. In the future, I do hope to become a licensed user of LAStools when my meager academic budgets allow.
I had the opportunity to appear on television as a guest on Metro Center Outlook, a production of WUCF. It was an interesting experience that was way outside of my comfort zone. It also involved wearing makeup.
Medeiros, S.C., S.C. Hagen, et al. (2015), “Adjusting lidar-derived digital terrain models in coastal marshes based on estimated above ground biomass density,” Remote Sensing – Special Issue: Towards Remote Long-Term Monitoring of Wetland Landscapes, 7(4), 3507-3525; doi:10.3390/rs70403507.
Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three- class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer to true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.
Passeri, D.L., S.C. Hagen, M.V. Bilskie, S.C. Medeiros (2015), “On the significance of incorporating shoreline changes for evaluating coastal hydrodynamics under sea level rise scenarios”, Natural Hazards, 75(2) pp. 1599-1617, doi:10.1007/s11069-014-1386-y.
The influence of including the dynamic effects of future shoreline changes associated with sea level rise into hydrodynamic modeling is evaluated for the coast of the Northern Gulf of Mexico from Mobile Bay, AL to St. Andrew Bay, FL. A two-dimensional, depth-integrated hydrodynamic model forced by astronomic tides and hurricane winds and pressures representative of Hurricanes Ivan (2004), Dennis (2005) and Katrina (2005) is used to simulate present conditions, 2050 projected sea level (0.46 m rise) with present-day shorelines, and 2050 sea level with projected 2050 shorelines. The 2050 shoreline and nearshore morphology are projected using Coastal Vulnerability Index shoreline change rates to determine the position of the new Gulf and bay shorelines, while the active beach profile is shifted horizontally according to the amount of erosion or accretion, and vertically to keep pace with rising seas. Hydrodynamic model results show that taking a dynamic approach to modeling sea level rise (as opposed to a static, or “bathtub” approach) increases tidal ranges and tidal prisms within the bay systems. Incorporating the projected shoreline changes does not alter tidal ranges, but some bays experience changes in tidal prisms depending on whether the planform area of the bay increases or decreases with the projected erosion or accretion. Barrier islands with projected erosion are vulnerable to increased overtopping from storm surge inundation, which impels more water into the back-bays and increases the inland inundation extent and magnitude. Inundation along barrier islands with projected accretion remains relatively the same as inundation under present-day shorelines, which prevents additional overtopping and limits more water from entering back-bays. Results demonstrate that although modeling sea level rise as a dynamic process is necessary, the incorporation of shoreline changes has variable impacts when evaluating future hydrodynamics and the response of the coastal system to sea level rise.
Bilskie, M. V., S. C. Hagen, S. C. Medeiros, and D. L. Passeri (2014), Dynamics of sea level rise and coastal flooding on a changing landscape, Geophys. Res. Lett., 41, doi:10.1002/2013GL058759.
Standard approaches to determining the impacts of sea level rise (SLR) on storm surge flooding employ numerical models reflecting present conditions with modified sea states for a given SLR scenario. In this study, we advance this paradigm by adjusting the model framework so that it reflects not only a change in sea state but also variations to the landscape (morphologic changes and urbanization of coastal cities). We utilize a numerical model of the Mississippi and Alabama coast to simulate the response of hurricane storm surge to changes in sea level, land use/land cover, and land surface elevation for past (1960), present (2005), and future (2050) conditions. The results show that the storm surge response to SLR is dynamic and sensitive to changes in the landscape. We introduce a new modeling framework that includes modification of the landscape when producing storm surge models for future conditions.
Atkinson, J., H. Roberts, S.C. Hagen, S. Zhou, P. Bacopoulos, S. Medeiros, J. Weishampel and Z. Cobell (2011), “Deriving Frictional Parameters and Performing Historical Validation for an ADCIRC storm surge model of the Florida gulf coast,” Florida Watershed Journal, Vol. 4. No. 2, Spring 2011, pp. 22–27.
Updates are in process for FEMA’s Digital Flood Insurance Rate Map (DFIRM) for three Florida coastal counties - Wakulla, Jefferson, and Franklin - that are subject to flooding from hurricane-driven storm surge. To assess the statistical frequency of inundation for the coastal counties, a finite element computer model, Advanced Circulation Model (ADCIRC), is used to simulate storm surge flooding for a large number of hurricane scenarios. This article is a companion to other articles in this issue that discuss aspects of the modeling developed for FEMA in the study region. One of the important components of modeling flood inundation from hurricane storm surge is to correctly model the surface roughness characteristics in the region of interest. The following provides details on the development of the frictional inputs for the ADCIRC model and an example from the surface model validation.