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Fluvial Channel Path Evolution – Documenting Decades Of Change Along The Little Wabash River, East Central Illinois, Usa, Diane M. Burns, David Viertel, Kwang Il Yoo Jul 2024

Fluvial Channel Path Evolution – Documenting Decades Of Change Along The Little Wabash River, East Central Illinois, Usa, Diane M. Burns, David Viertel, Kwang Il Yoo

The Compass: Earth Science Journal of Sigma Gamma Epsilon

As highly dynamic landforms, rivers etch their channels into the surrounding and underlying strata over time, continuously reshaping the landscapes they traverse. This study examines geomorphological changes of the Little Wabash River in East Central Illinois between 1938 and 2011. The Little Wabash River is a meandering river sourced in southwestern Coles County, Illinois, and flows southward approximately 390 km to its confluence with the Wabash River. The historical location of the Little Wabash River was delineated to establish a baseline survey using archival aerial photography acquired in 1938. To understand how the channel evolved, investigations were conducted in each …


A Target-Based And A Targetless Extrinsic Calibration Methods For Thermal Camera And 3d Lidar, Farhad Dalirani Jan 2024

A Target-Based And A Targetless Extrinsic Calibration Methods For Thermal Camera And 3d Lidar, Farhad Dalirani

Electronic Thesis and Dissertation Repository

This thesis introduces two novel methods for the extrinsic calibration of a thermal camera and a 3D LiDAR sensor, which are crucial for seamless data integration. The first method employs a distinctive calibration target, leveraging lines and plane equations correspondence in both modalities for a single pose, and incorporating more poses by matching the target's edges. It achieves reliable results, even with just one pose yielding 10.82% translation and 0.51-degree rotation errors. This outperforms alternative methods, which require eight pairs for similar results. The second method eliminates the need for a dedicated target. Instead, by collecting data during the sensor …


Lidar Monitoring Of Annual And Storm-Driven Episodic Erosion At Rainsford Island, Alan H. Bartels Aug 2023

Lidar Monitoring Of Annual And Storm-Driven Episodic Erosion At Rainsford Island, Alan H. Bartels

Graduate Masters Theses

Boston Harbor and its thirty-four islands are subject to erosion, driven by rain, winds, and waves. Climate change threatens to increase erosion over time as sea levels rise and the frequency and intensity of storms increase. Understanding the dynamics of coastal erosion is key to guiding the design of coastal shoreline protections, the research of which a goal of Stone Living Laboratory at the University of Massachusetts Boston. To better understand the impact of both annual weather and episodic severe storms, the high-resolution Riegl VZ400i LiDAR was deployed four times over 14 months from July 22, 2021 to October 19, …


Innovations In Geospatial Technologies For Water And Environmental Resource Protection, Madeleine Bolick Aug 2023

Innovations In Geospatial Technologies For Water And Environmental Resource Protection, Madeleine Bolick

All Dissertations

New technologies and applications of technologies are critical to protecting environmental and water resources. Students need to be aware of these new technologies so they can be prepared to utilize them in their future careers. One such technology is using Unmanned Aerial Vehicles (UAVs) because it can be applied to a wide variety of fields such as engineering, construction, wildlife biology, agriculture, and many more. Chapter two discusses the creation of an online teaching module to introduce students to using UAVs in natural resource research and evaluates how well students respond to the education module. Overall, student familiarity with UAVs …


Lidar Segmentation-Based Adversarial Attacks On Autonomous Vehicles, Blake Johnson Jun 2023

Lidar Segmentation-Based Adversarial Attacks On Autonomous Vehicles, Blake Johnson

Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal

Autonomous vehicles utilizing LiDAR-based 3D perception systems are susceptible to adversarial attacks. This paper focuses on a specific attack scenario that relies on the creation of adversarial point clusters with the intention of fooling the segmentation model utilized by LiDAR into misclassifying point cloud data. This can be translated into the real world with the placement of objects (such as road signs or cardboard) at these adversarial point cluster locations. These locations are generated through an optimization algorithm performed on said adversarial point clusters that are introduced by the attacker.


Post Wildfire Vegetation Response To The Wildland-Urban Interface: A Case Study Of The Station Fire, Angelo C. De Guzman, Raju Bista, Parveen K. Chhetri May 2023

Post Wildfire Vegetation Response To The Wildland-Urban Interface: A Case Study Of The Station Fire, Angelo C. De Guzman, Raju Bista, Parveen K. Chhetri

CSU Journal of Sustainability and Climate Change

In the past, wildfires served as a method for mother nature to promote biodiversity and to help maintain a functioning ecosystem. However, climate change alters the fire regime, significantly impacting vegetation recovery. Human disturbances and increased land use and land cover heighten vegetation disruption and abundance after a fire. Wildland-urban interface (WUI) – the region where the vegetation intermingles with the roads, houses, and human-made structures – threatens vegetation and the human population. Overall vegetation recovery after the Station Fire of 2009 spread through the San Gabriel Mountains, Los Angeles County was observed using Digital Elevation Model (DEM), Normalized Difference …


Liloc: Enabling Precise 3d Localization In Dynamic Indoor Environments Using Lidars, Darshana Rathnayake, Meera Radhakrishnan, Inseok Hwang, Archan Misra May 2023

Liloc: Enabling Precise 3d Localization In Dynamic Indoor Environments Using Lidars, Darshana Rathnayake, Meera Radhakrishnan, Inseok Hwang, Archan Misra

Research Collection School Of Computing and Information Systems

We present LiLoc, a system for precise 3D localization and tracking of mobile IoT devices (e.g., robots) in indoor environments using multi-perspective LiDAR sensing. The key differentiators in our work are: (a) First, unlike traditional localization approaches, our approach is robust to dynamically changing environmental conditions (e.g., varying crowd levels, object placement/layout changes); (b) Second, unlike prior work on visual and 3D SLAM, LiLoc is not dependent on a pre-built static map of the environment and instead works by utilizing dynamically updated point clouds captured from both infrastructural-mounted LiDARs and LiDARs equipped on individual mobile IoT devices. To achieve fine-grained, …


Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis Apr 2023

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …


Digital Archaeology: Detection Of Archaeological Structures Using Convolutional Neural Networks On Aerial Lidar Data, Katie Larue Jan 2023

Digital Archaeology: Detection Of Archaeological Structures Using Convolutional Neural Networks On Aerial Lidar Data, Katie Larue

WWU Honors College Senior Projects

Archaeology is a field that is mostly done by hand. Archaeologists explore remote and unknown areas of the world to find undiscovered civilizations that will give us any idea about how people lived in the past. To speed up this process, Airborne light detection and ranging or LiDAR systems have been used to great effect to speed up this processing. However, we still require domain experts to annotate this information to confirm structures. Deep learning has the potential to speed up this process and the following presentation is a basic overview of machine learning, popular types of deep learning models, …


Oh The Places Snow Blows: Observations And Impacts Of Snow Redistribution On Arctic Sea Ice, David Clemens-Sewall Jan 2023

Oh The Places Snow Blows: Observations And Impacts Of Snow Redistribution On Arctic Sea Ice, David Clemens-Sewall

Dartmouth College Ph.D Dissertations

Arctic sea ice has declined dramatically due to climate change. This decline impacts Arctic communities, ecosystems, international trade, and the world's climate. However, due to uncertain physical processes, climate models generally do not capture the severity of the observed decline---adding uncertainty to projections of future climate change. A major uncertainty in the Arctic sea ice component of climate models is how much heat passes through the snow on top of the ice in the winter. This heat flux controls how much ice grows each winter, impacting how much ice survives the summer melt. Snow is an excellent thermal insulator (about …


Integrating Lidar, Aeromagnetic, And Geological Field Data To Identify Structural-Lithologic Elements Within The Archean Carney Lake Gneiss Complex, Ian M. Gannon Jan 2023

Integrating Lidar, Aeromagnetic, And Geological Field Data To Identify Structural-Lithologic Elements Within The Archean Carney Lake Gneiss Complex, Ian M. Gannon

Dissertations, Master's Theses and Master's Reports

The Archean Carney Lake Gneiss Complex (CLGC) is a suite of rocks on the southern margin of the Superior Province and within the Minnesota River Valley subprovince. It is one of many gneissic domes in Michigan, Wisconsin, and Minnesota whose complex geology is poorly understood due to a previous lack of economic interest in gneissic terranes and significant challenges to their investigation. As a consequence, the CLGC and other gneissic domes in the region are represented on geologic maps as undifferentiated masses surrounded by better defined and understood Paleoproterozoic supracrustal rocks and igneous intrusions. Within the last ten years, however, …


Uncertainty Of Icesat-2 Atl06- And Atl08-Derived Snow Depths For Glacierized And Vegetated Mountain Regions, Ellyn M. Enderlin, Colten M. Elkin, Madeline Gendreau, H.P. Marshall, Shad O'Neel, Christopher Mcneil, Caitlyn Florentine, Louis Sass Dec 2022

Uncertainty Of Icesat-2 Atl06- And Atl08-Derived Snow Depths For Glacierized And Vegetated Mountain Regions, Ellyn M. Enderlin, Colten M. Elkin, Madeline Gendreau, H.P. Marshall, Shad O'Neel, Christopher Mcneil, Caitlyn Florentine, Louis Sass

Geosciences Faculty Publications and Presentations

Seasonal snow melt dominates the hydrologic budget across a large portion of the globe. Snow accumulation and melt vary over a broad range of spatial scales, preventing accurate extrapolation of sparse in situ observations to watershed scales. The lidar onboard the Ice, Cloud, and land Elevation, Satellite (ICESat-2) was designed for precise mapping of ice sheets and sea ice, and here we assess the feasibility of snow depth-mapping using ICESat-2 data in more complex and rugged mountain landscapes. We explore the utility of ATL08 Land and Vegetation Height and ATL06 Land Ice Height differencing from reference elevation datasets in two …


Advancements In Measuring And Modeling The Mechanical And Hydrological Properties Of Snow And Firn: Multi-Sensor Analysis, Integration, And Algorithm Development, Tate G. Meehan Aug 2022

Advancements In Measuring And Modeling The Mechanical And Hydrological Properties Of Snow And Firn: Multi-Sensor Analysis, Integration, And Algorithm Development, Tate G. Meehan

Boise State University Theses and Dissertations

Estimating snow mechanical properties – such as elastic modulus, stiffness, and strength – is important for understanding how effectively a vehicle can travel over snow-covered terrain. Vehicle instrumentation data and observations of the snowpack are valuable for improving the estimates of winter vehicle performance. Combining in-situ and remotely-sensed snow observations, driver input, and vehicle performance sensors requires several techniques of data integration. I explored correlations between measurements spanning from millimeter to meter scales, beginning with the SnowMicroPenetrometer (SMP) and instruments applied to snow that were designed for measuring the load bearing capacity and the compressive and shear strengths of roads …


Temporal Lidar Scanning In Quantifying Cumulative Rockfall Volume And Hazard Assessment: A Case Study At Southwestern Saudi Arabia, Abdullah A. Alotaibi, Norbert H. Maerz, Kenneth J. Boyko, Ahmed M. Youssef, Biswajeet Pradhan Aug 2022

Temporal Lidar Scanning In Quantifying Cumulative Rockfall Volume And Hazard Assessment: A Case Study At Southwestern Saudi Arabia, Abdullah A. Alotaibi, Norbert H. Maerz, Kenneth J. Boyko, Ahmed M. Youssef, Biswajeet Pradhan

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Rockfalls and unstable slopes pose a serious threat to people and property along roads/highways in the southwestern mountainous regions of Saudi Arabia. In this study, the application of terrestrial light detection and ranging (LiDAR) technology was applied aiming to propose a strategy to analyze and accurately depict the detection of rockfall changes, calculation of rockfall volume, and evaluate rockfall hazards along the Habs Road, Jazan Region, Saudi Arabia. A series of temporal LiDAR scans were acquired at three selected sites. Our results show that these three sites have different degrees of hazard due to their geological differences. The mean volume …


Differentiating Fissure-Fed Lava Flow Types And Facies Using Radar And Lidar: An Example From The 2014–2015 Holuhraun Lava Flow-Field, Gavin Douglas Tolometti, Catherine D. Neish, Christopher W. Hamilton, Gordon R. Osinski, Antero Kukko, Joana R.C. Voigt Jun 2022

Differentiating Fissure-Fed Lava Flow Types And Facies Using Radar And Lidar: An Example From The 2014–2015 Holuhraun Lava Flow-Field, Gavin Douglas Tolometti, Catherine D. Neish, Christopher W. Hamilton, Gordon R. Osinski, Antero Kukko, Joana R.C. Voigt

Earth Sciences Publications

Distinguishing between lava types and facies using remote sensing data is important for interpreting the emplacement history of lava flow-fields on Earth and other planetary bodies. Lava facies typically include a mixture of lava types and record the collective emplacement history of material preserved at a particular location. We seek to determine if lava facies in the 2014–2015 Holuhraun lava flow-field are discernible using radar roughness analysis. Furthermore, we also seek to distinguish between lava types using high resolution Light Detection and Ranging (LiDAR) data. We extracted circular polarization ratios (CPR) from the Uninhabited Aerial Vehicle Synthetic Aperture Radar and …


Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder May 2022

Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder

2022 Symposium

EWU contains a variety of deciduous and evergreen trees across its campus, providing several benefits. However, no comprehensive record exists of the total number, location, species, or ages of these trees. This knowledge can inform facilities of proper care for individual trees and can be used to estimate carbon sequestration on campus. Traditional on-the-ground methods for assessing trees require tree cores or clinometers, making trees susceptible to pests or disease and leading to inaccurate results. Remote sensing using lidar data is a noninvasive, more precise method to measure tree height and subsequently assess tree age. This poster explores using point …


Challenges In Approaching The Detection Limits For Hillslope Erosion Using Terrestrial Laser Scanning, Gene Nathan Bailey Iii May 2022

Challenges In Approaching The Detection Limits For Hillslope Erosion Using Terrestrial Laser Scanning, Gene Nathan Bailey Iii

Masters Theses

Accurately quantifying soil loss due to water erosion is a critical step in managing soils. Terrestrial LiDAR (Light Detection and Ranging) presents a potential alternative to traditional soil loss measurement by estimating soil erosion and deposition through detecting surface changes. Terrestrial LiDAR can also provide spatial distribution information without disturbing the observed surface. While erosion estimation through terrestrial LiDAR detects large magnitude erosion well, the finer temporal/spatial scale erosion experienced on the hillslope in sheet and rill erosion has remained a challenge to detect. This research addresses two of the challenges in using terrestrial LiDAR on fine scales in two …


Multi-Trophic Biodiversity Increases With Increasing Structural Complexity Of Forest Canopy, Ayanna St. Rose May 2022

Multi-Trophic Biodiversity Increases With Increasing Structural Complexity Of Forest Canopy, Ayanna St. Rose

Graduate Theses and Dissertations

Understanding the effects of forest canopy structural complexity on multi-trophic diversity is critical for conserving biodiversity and managing land sustainably. But multi-trophic diversity is often ignored when making decisions about land management due to lack of cost- and time-effective methods to evaluate it. Here, we explored a new method based on widely available remote sensing data to quantify canopy structural complexity and its relationships with multi-trophic biodiversity at landscape scale using 32 forested sites of the National Ecological Observatory Network. We investigated the influence of vertical and horizontal structural complexity of forest canopy on multi-trophic (primary producers, herbivores (beetles), omnivores …


Automatic Segmentation Of Sinkholes Using A Convolutional Neural Network, Muhammad Usman Rafique, Junfeng Zhu, Nathan Jacobs Feb 2022

Automatic Segmentation Of Sinkholes Using A Convolutional Neural Network, Muhammad Usman Rafique, Junfeng Zhu, Nathan Jacobs

Faculty, Staff, and Affiliated Publications--KGS

Sinkholes are the most abundant surface features in karst areas worldwide. Understanding sinkhole occurrences and characteristics is critical for studying karst aquifers and mitigating sinkhole-related hazards. Most sinkholes appear on the land surface as depressions or cover collapses and are commonly mapped from elevation data, such as digital elevation models (DEMs). Existing methods for identifying sinkholes from DEMs often require two steps: locating surface depressions and separating sinkholes from non-sinkhole depressions. In this study, we explored deep learning to directly identify sinkholes from DEM data and aerial imagery. A key contribution of our study is an evaluation of various ways …


Automatic Segmentation Of Sinkholes Using A Convolutional Neural Network, Muhammad Usman Rafique, Junfeng Zhu, Nathan Jacobs Feb 2022

Automatic Segmentation Of Sinkholes Using A Convolutional Neural Network, Muhammad Usman Rafique, Junfeng Zhu, Nathan Jacobs

Computer Science Faculty Publications

Sinkholes are the most abundant surface features in karst areas worldwide. Understanding sinkhole occurrences and characteristics is critical for studying karst aquifers and mitigating sinkhole-related hazards. Most sinkholes appear on the land surface as depressions or cover collapses and are commonly mapped from elevation data, such as digital elevation models (DEMs). Existing methods for identifying sinkholes from DEMs often require two steps: locating surface depressions and separating sinkholes from non-sinkhole depressions. In this study, we explored deep learning to directly identify sinkholes from DEM data and aerial imagery. A key contribution of our study is an evaluation of various ways …


The Burning Bush: Linking Lidar-Derived Shrub Architecture To Flammability, Michelle S. Bester Jan 2022

The Burning Bush: Linking Lidar-Derived Shrub Architecture To Flammability, Michelle S. Bester

Graduate Theses, Dissertations, and Problem Reports

Light detection and ranging (LiDAR) and terrestrial laser scanning (TLS) sensors are powerful tools for characterizing vegetation structure and for constructing three-dimensional (3D) models of trees, also known as quantitative structural models (QSM). 3D models and structural traits derived from them provide valuable information for biodiversity conservation, forest management, and fire behavior modeling. However, vegetation studies and 3D modeling methodologies often only focus on the forest canopy, with little attention given to understory vegetation. In particular, 3D structural information of shrubs is limited or not included in fire behavior models. Yet, understory vegetation is an important component of forested ecosystems, …


Multi-Scale Assessment Of Gully Erosion At Road Drainage Outlets, Emma Louise Estabrook Jan 2022

Multi-Scale Assessment Of Gully Erosion At Road Drainage Outlets, Emma Louise Estabrook

Graduate College Dissertations and Theses

Gully erosion and sediment deposition from roads are underrated sources of sediments entering receiving waterways. While gully erosion has been studied throughout the world, the monitoring of the temporal and spatial erosional processes related to culverts and road drainage is rare. The objectives of this study are to quantify rates of gully erosion from Vermont’s transportation drainage networks at multiple temporal scales and report on insights gained from a multi-scale approach to monitoring gully erosion. To quantify event to seasonal timescales of gully erosion, high resolution terrestrial LiDAR surveys were conducted at 13 field sites. Field sites were monitored at …


Lidar-Landsat Covariance For Predicting Canopy Fuels, Margaret D. Epstein Jan 2022

Lidar-Landsat Covariance For Predicting Canopy Fuels, Margaret D. Epstein

Graduate Student Theses, Dissertations, & Professional Papers

Managing wildfires in the western United States is becoming increasingly complex. Visualizing and quantifying canopy structures allows fire managers to both plan for fire and track recovery. Light detecting and ranging, or LiDAR can measure forests in three dimensions, but has limited spatial and temporal coverage. LiDAR-Landsat covariance uses machine learning to fill in the spatial and temporal gaps of LiDAR coverage with supplemental Landsat imagery. However, in order to capture real forest dynamics, a model needs to be stable enough to detect long term trends, sensitive to episodic disturbance, and general enough to work on multiple landcovers. The purpose …


Historical Changes Of Channel Width In A Headwater Stream System, Mark Twain National Forest, Missouri, Sierra N. Casagrand Aug 2021

Historical Changes Of Channel Width In A Headwater Stream System, Mark Twain National Forest, Missouri, Sierra N. Casagrand

MSU Graduate Theses

It is well known that watershed disturbances due to land clearing and agricultural settlement during the early 1800s changed the hydrology and geomorphology of stream systems in the Midwestern USA. However, little is known about the impacts of historical logging on stream systems in forested watersheds. This study evaluates channel width measurements from 38 General Land Office (GLO) surveys completed in 1821, aerial photographs from the 1930’s to present, and LiDAR imagery from 2016/17 to evaluate changes in channel morphology in Big Barren Creek in Mark Twain National Forest in the Ozarks Highlands of southeast Missouri. The area was heavily …


Just-In-Time Biomass Yield Estimation With Multi-Modal Data And Variable Patch Training Size, Patricia O'Byrne, Patrick Jackman Dr., Damon Dr. Berry Dr., Thomas Lee, Michael French, Robert J. Ross Jan 2021

Just-In-Time Biomass Yield Estimation With Multi-Modal Data And Variable Patch Training Size, Patricia O'Byrne, Patrick Jackman Dr., Damon Dr. Berry Dr., Thomas Lee, Michael French, Robert J. Ross

Conference papers

The just-in-time estimation of farmland traits such as biomass yield can aid considerably in the optimisation of agricultural processes. Data in domains such as precision farming is however notoriously expensive to collect and deep learning driven modelling approaches need to maximise performance but also acknowledge this reality. In this paper we present a study in which a platform was deployed to collect data from a heterogeneous collection of sensor types including visual, NIR, and LiDAR sources to estimate key pastureland traits. In addition to introducing the study itself we address two key research questions. The first of these was the …


Bicknell's Thrush Habitat Use On Commercial Forests In Maine, Usa, Kaitlyn Wilson Aug 2020

Bicknell's Thrush Habitat Use On Commercial Forests In Maine, Usa, Kaitlyn Wilson

Electronic Theses and Dissertations

Forest reliant species may be significantly impacted by forest management practices. Understanding these impacts, and whether they are positive or negative, requires a species- specific understanding of habitat use. Bicknell’s thrush (Catharus bicknelli) is a range-restricted habitat specialist occurring in balsam fir (Abies balsamea) dominated montane forests that have been recently disturbed and are undergoing successional growth. While research investigating this species’ habitat use has been conducted throughout much of its breeding range, knowledge of Bicknell’s thrush habitat use in Maine is lacking. Greater understanding of habitat use in Maine would improve the ability of forest managers to promote conservation …


Resolution Of Lava Tubes With Ground Penetrating Radar: The Tubex Project, Sanaz Esmaeili, Sarah Kruse, Sajad Jazayeri, P. Whelley, E. Bell, J. Richardson, W. B. Garry, K. Young May 2020

Resolution Of Lava Tubes With Ground Penetrating Radar: The Tubex Project, Sanaz Esmaeili, Sarah Kruse, Sajad Jazayeri, P. Whelley, E. Bell, J. Richardson, W. B. Garry, K. Young

School of Geosciences Faculty and Staff Publications

Remote sensing surveys of the Moon and Mars show evidence of lava tubes, which are potential safe havens for human crews and their equipment. Ground penetrating radar (GPR) can be used to map tubes because the void/rock interface at tube ceilings and floors strongly reflects radar pulses. We have tested the capacity of GPR to sense lava tube geometry at Lava Beds National Monument in California, USA. GPR and detailed light detection and ranging (LiDAR) data are presented for two tubes: Skull Cave, with a few meters of overburden, diameter ~10–20 m, and a rubbly floor; and Valentine Cave, with …


Truck Trailer Classification Using Side-Fire Light Detection And Ranging (Lidar) Data, Olcay Sahin Apr 2020

Truck Trailer Classification Using Side-Fire Light Detection And Ranging (Lidar) Data, Olcay Sahin

Civil & Environmental Engineering Theses & Dissertations

Classification of vehicles into distinct groups is critical for many applications, including freight and commodity flow modeling, pavement management and design, tolling, air quality monitoring, and intelligent transportation systems. The Federal Highway Administration (FHWA) developed a standardized 13-category vehicle classification ruleset, which meets the needs of many traffic data user applications. However, some applications need high-resolution data for modeling and analysis. For example, the type of commodity being carried must be known in the freight modeling framework. Unfortunately, this information is not available at the state or metropolitan level, or it is expensive to obtain from current resources.

Nevertheless, using …


Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl Mar 2020

Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl

Theses and Dissertations

The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …


Mapping Surficial Geology In The New River Gorge National River And Bluestone National Scenic River, West Virginia, Using Lidar-Derived Digital Elevation Data, Marla K. Denicola Jan 2020

Mapping Surficial Geology In The New River Gorge National River And Bluestone National Scenic River, West Virginia, Using Lidar-Derived Digital Elevation Data, Marla K. Denicola

Graduate Theses, Dissertations, and Problem Reports

The purpose of this thesis was to determine if the surficial geology of Bluestone National Scenic River (BLUE) and New River Gorge National River (NERI), two areas of similar geology, can be mapped using visual interpretation methods applied to digital elevation models (DEMs) derived from light detection and ranging (LiDAR) data. Surficial geology in BLUE was field mapped using GPS, following definitions and characterizations for surficial geology units established with the guidance of Dr. J. Steven Kite. A 2m x 2m LiDAR-derived DEM was used for BLUE and most of NERI using US Army Corps of Engineers (USCOE) LiDAR data, …