Remote Sensing Commons^™

Comparison Of Airborne Lidar-Derived Elevation Data In Fayetteville, Arkansas, Usa, Angelica M. Otting

Graduate Theses and Dissertations

Light detection and ranging (lidar) laser scanners are prominent remote sensing tools to produce high resolution three-dimensional (3D) imagery of the Earth’s surface. These laser scanners combined with global navigation satellite systems (GNSS) and real-time kinematic (RTK) reference stations can generate some of the most accurate ground surface imagery and elevation data for terrain mapping and related applications. Lidar aerial survey is an important tool in industries such as architecture, civil engineering, forestry, geology, geography, and agriculture where digital terrain models (DTMs) can be used to examine the geographical landscape and urban industry. Currently, there are three different common laser …

Forest Above-Ground Biomass Estimation Using Nasa Gedi Lidar Waveforms And Global Tree Allometry, Ian Grant

Theses and Dissertations

Above-ground forest biomass plays a crucial role in global carbon cycles, yet accurately estimating biomass at global scales remains challenging. This thesis addresses two key challenges in processing NASA’s Global Ecosystem Dynamics Investigation (GEDI) space-borne lidar data to estimate above-ground biomass density (AGBD): accounting for global variation in forest structure and developing robust physical interpretations of lidar returns. The first component of the thesis analyzes global patterns of tree allometry using the Tallo tree allometry dataset, examining relationships between tree dimensions across biomes, continents, and plant functional types. This analysis reveals consistent allometry across continents for some biomes (e.g., tropical …

Modeling Snow Surface Properties From Lidar And Imaging Spectroscopy, Brenton A. Wilder

Boise State University Theses and Dissertations

Seasonal snow surface plays an important role in altering terrestrial hydrology and global climate patterns. Snow reflects a majority of incoming shortwave radiation thereby reducing the net shortwave radiation received into snowpack throughout the season. This property is commonly referred to as snow albedo and impacts water cycles and air temperatures by modulating the timing and magnitude of melt. This reflectivity of snow is difficult to measure accurately in mountain environments and at a large enough scale to be meaningful for water resource managers and climate scientists. The work presented herein aims to improve methodologies to measure snow reflectivity from …

Redefining Approaches For Measuring Landscape Subsidence And Permafrost Degradation In Arctic Tundra Environments, Tabatha Lynn Fuson

Open Access Theses & Dissertations

As climate change accelerates in the Arctic, the degradation of permafrost is leading to significant landscape transformation in tundra landscapes. This dissertation investigates the multifaceted responses of permafrost systems to warming, focusing on the dynamics of surface elevation changes and active layer thickness (ALT) across the North Slope of Alaska. In this study, I explore the capacity of repeat Terrestrial Laser Scanning (TLS) technology for modeling tundra features and detecting surface subsidence, specifically how different climate and landscape conditions during scanning impact TLS model precision. We also compare TLS model precision estimates to TLS model accuracy by comparing elevation values …

Using Terrestrial Laser Scanning To Estimate Canopy Structure In Peatland Conifers Under A Climate Manipulation, Angela D. Seibert

Boise State University Theses and Dissertations

Northern peatlands are major terrestrial carbon sinks, storing 415 ± 150 Gt of carbon. The composition of peatland vegetation affects this carbon storage capacity, and thus quantifying the vegetation helps to constrain uncertainty in peatland carbon storage estimates. Ground layer vegetation, such as Sphagnum sp. moss contributes greatly to carbon storage capacity. In forested peatlands, the tree canopy structure directly influences peatland solar insolation, soil temperature, and water table levels. Each of these factors impacts the ground layer vegetation. Currently, there is uncertainty about how the peatland tree canopy structure is influenced by elevated levels of carbon dioxide (CO_{2 …}

Mapping Forest Structure In Mississippi Using Lidar Remote Sensing, Nitant Rai

Theses and Dissertations

This study aimed at evaluating the agreement of spaceborne Light Detection and Ranging (lidar) ICESat-2 canopy height with Airborne Laser Scanning (ALS) derived canopy height to inform about the performance of ICESat-2 canopy height metrics and understand its uncertainties and utilities. The agreement was assessed for different forest types, physiographic regions, a range of percent canopy cover, and diverse disturbance histories. Results of this study suggest that best agreements are found using strong beam data collected at night for canopy height retrieval using ICESat-2. The ICESat-2 showed great potential for estimating canopy heights, particularly in evergreen forests with high canopy …

Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …

Shipboard Lidar As A Tool For Remotely Measuring The Distribution And Bulk Characteristics Of Marine Particles, Brian Leigh Collister

OES Theses and Dissertations

Light detection and ranging (lidar) can provide remote estimates of the vertical distribution of optical properties in the ocean, potentially revolutionizing our ability to characterize the spatial structure of upper ocean ecosystems. However, challenges associated with quantifying the relationship between lidar measurements and biogeochemical properties of interest have prevented its adoption for routinely mapping the vertical structure of marine ecosystems. To address this, we developed a shipboard oceanographic lidar that measures attenuation (α) and linear depolarization (δ) at scales identical to those of in-water optical and biogeochemical measurements. The instrument’s ability to resolve the distribution of optical and biogeochemical properties …

Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Mohammed Alqawba, Norou Diawara, Kwasi G. Afrifa, Mohamed I. Elbakary, Mecit Cetin, Khan Iftekharuddin

Mathematics & Statistics Faculty Publications

In this article, we present a new study for the analysis and classification of atmospheric aerosols in remote sensing LIDAR data. Information on particle size and associated properties are extracted from these remote sensing atmospheric data which are collected by a ground-based LIDAR system. This study first considers optical LIDAR parameter-based classification methods for clustering and classification of different types of harmful aerosol particles in the atmosphere. Since accurate methods for aerosol prediction behaviors are based upon observed data, computational approaches must overcome design limitations, and consider appropriate calibration and estimation accuracy. Consequently, two statistical methods based on generalized linear …

Characterizing The Impacts Of The Invasive Hemlock Woolly Adelgid On The Forest Structure Of New England, Peter Brehm Boucher

Graduate Doctoral Dissertations

Climate change is raising winter temperatures in the Northeastern United States, both expanding the range of an invasive pest, the hemlock woolly adelgid (HWA; Adelges tsugae), and threatening the survival of its host species, eastern hemlock (Tsuga canadensis). As a foundation species, hemlock trees underlie a distinct network of ecological, biogeochemical, and structural systems that will likely disappear as the HWA infestation spreads northward. Remote sensing can offer new perspectives on this regional transition, recording the progressive loss of an ecological foundation species and the transition of evergreen hemlock forest to mixed deciduous forest over the course of the infestation. …

The Importance Of Landscape Position Information And Elevation Uncertainty For Barrier Island Habitat Mapping And Modeling, Nicholas Matthew Enwright

LSU Doctoral Dissertations

Barrier islands provide important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. As a result, natural resource managers are concerned with monitoring changes to these islands and modeling future states of these environments. Landscape position, such as elevation and distance from shore, influences habitat coverage on barrier islands by regulating exposure to abiotic factors, including waves, tides, and salt spray. Geographers commonly use aerial topographic lidar data for extracting landscape position information. However, researchers rarely consider lidar elevation uncertainty when using automated processes for extracting elevation-dependent habitats from lidar data. …

Unmanned Aerial-Vehicle-Based Measurement Of Urban Forests, Earle W. Isibue

Graduate Research Theses & Dissertations

Human and natural forces continually act on urban forests to producing changes that leading to trees being removed or replanted. Therefore, to manage the urban forest effectively, periodic inventories are needed to ensure that information about the urban forest is current and comprehensive. This task has traditionally been accomplished by manual ground-based field surveys, or more recently by lidar; however, these methods are expensive, either in terms of time, labor, or cost. This project proposes a novel method of using Unmanned Aerial Vehicles (UAVs) to more accurately measure urban tree height and trunk diameter than is currently possible using conventional …

Comparing Unmanned Aerial Systems (Uas) Structure-From-Motion Digital Surface Modeling To Laser Imaging Detection And Ranging (Lidar), Joshua D. Schane

Geography Masters Research Papers

UAS (unmanned-aerial systems) mapping is an emerging technology in spatial science. UAS, more informally referred to as “drones,” are small, radio-controlled or autonomous aerial platforms outfitted with camera sensor systems that can be deployed to fly missions for mapping terrain and structures. With the use of a photogrammetry technique called structure-from-motion, overlapping aerial images can be developed into high-resolution spatial data (< 5-cm). These data are georeferenced by GPS location information assigned to aerial targets which act as ground-control points (GCPs). This research explores the accuracy of the UAS-derived digital surface model (DSM) as it relates to a LIDAR DSM of the same study area in St. Helens, Oregon.

The site that was chosen to be mapped was a large wastewater treatment plant, with surrounding natural areas, residential, and industrial properties. The site was mapped using a small quadcopter-style UAS which was programmed autonomously; the overlapping aerial …

Lidar And Machine Learning Estimation Of Hardwood Forest Biomass In Mountainous And Bottomland Environments, Bowei Xue

Graduate Theses and Dissertations

Light detection and ranging (lidar) has been applied in various forest applications, such as to retrieve forest structural information, to build statistical models for identification of tree species, and to monitor forest growth. However, despite significant progress in these areas, the choice of regression approach and parameter tuning remains an ongoing critical question. This study focused on choosing the right spatial generalization level to transform lidar point clouds to 2D images which can be further processed by mature image processing and pattern recognition approaches. It also compared the prediction ability of popular machine learning algorithms applied to aboveground forest biomass …

Mapping Forest Canopy Structure With On-Demand Fusion Of Remotely Sensed Data, Gordon M. Green

Dissertations, Theses, and Capstone Projects

Current methods of mapping forest canopy structure often result in data products that are limited in resolution, coverage, or ease of access. On-demand processing introduces several new ways in which existing data products can be combined and re-purposed, mitigating some of these limitations. In this research, we investigate several methods of extending the spatial and temporal resolution, coverage, and accessibility of existing forest canopy datasets by processing them on demand. These methods include downscaling coarse-resolution canopy height data dynamically to estimate height at 30 m and 1 m resolution for any location within the contiguous United States. A related method …

Slope Stability Monitoring Using Remote Sensing Techniques, Omar Alberto Conte Robles

Graduate Theses and Dissertations

During the past six years the Arkansas State Highway and Transportation Department (AHTD) has spent over nine million dollars repairing slope failures that have occurred in the state of Arkansas. Specifically, higher than average precipitation in 2004 and 2008 led to large quantities of slides, all of which were repaired. Two highways, within the state of Arkansas, with known historical movements along or across the highways are being monitored using traditional surveying techniques and advanced remote sensing techniques. These slides, both of which are located in fill slopes. One a 500-foot long slide located north of Chester, Arkansas, within the …

Accuracy Assessment Of Land Cover Maps Derived From Multiple Data Sources, Daniel Unger, Hillary Tribby, Hans Michael Williams, I-Kuai Hung

Faculty Publications

Maximum Likelihood (ML) and Artificial Neural Network (ANN) supervised classification methods were used to demarcate land cover types within IKONOS and Landsat ETM+ imagery. Three additional data sources were integrated into the classification process: Canopy Height Model (CHM), Digital Terrain Model (DTM) and Thermal data. Both the CHM and DTM were derived from multiple return small footprint LIDAR. Forty maps were created and assessed for overall map accuracy, user's accuracy, producer's accuracy, kappa statistic and Z statistic using classification schemes from U.S.G.S. 1976 levels 1 and 2 and T.G.l.C. 1999 levels 2 and 4. Results for overall accuracy of land …