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Articles 1 - 11 of 11
Full-Text Articles in Other Forestry and Forest Sciences
Tree Crown Economics Of Broadleaf Deciduous Forests, Yiting Fan
Tree Crown Economics Of Broadleaf Deciduous Forests, Yiting Fan
Graduate Theses, Dissertations, and Problem Reports (ETD)
Tree crown architecture, a critical determinant of forest ecosystem processes such as photosynthesis, evapotranspiration, and spectral reflectance, is shaped by adaptive trade-offs in resource use and environmental responses. However, significant gaps remain in our understanding of how these traits vary across species, environmental gradients, and temporal scales. This dissertation addresses these gaps by employing remote sensing data across three interconnected studies. Together, these studies advance tree crown economic theory, highlighting how crown traits mediate trade-offs between light capture and water-use efficiency and how these traits influence forest responses to global change. Collectively, this dissertation offer insights for improving models that …
Characterizing Prescribed Fire With Terrestrial Lidar In The New Jersey Pine Barrens, Samuel Rhule Stockton
Characterizing Prescribed Fire With Terrestrial Lidar In The New Jersey Pine Barrens, Samuel Rhule Stockton
Graduate Theses, Dissertations, and Problem Reports (ETD)
Prescribed burning has become a commonly used tool in the mitigation of wildfire, though monitoring the way it changes ecosystems has historically been a time-intensive process. Rapid change across ecosystems has necessitated advancements in remote sensing technologies to quantify the changes taking place. Single-scan terrestrial LiDAR scanning is one such method of monitoring these changes through the quantification of ecosystem structural characteristics. Acute disturbance events such as fire can transform the structure of an ecosystem, and by extension, change the way that ecosystem functions. The purpose of this study is to analyze the changes in vegetation density and distribution following …
Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder
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 …
Multi-Trophic Biodiversity Increases With Increasing Structural Complexity Of Forest Canopy, Ayanna St. Rose
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 …
Lidar-Landsat Covariance For Predicting Canopy Fuels, Margaret D. Epstein
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 …
Urban Aerobiological Risk Mapping Of Ornamental Trees Using A New Index Based On Lidar And Kriging: A Case Study Of Plane Trees, Raúl Pecero-Casimiro, Santiago Fernández-Rodríguez, Rafael Tormo-Molina, Alejandro Monroy-Colín, Inmaculada Silva-Palacios, Juan Pedro Cortés-Pérez, Ángela Gonzalo-Garijo, J. M. Maya-Manzano
Urban Aerobiological Risk Mapping Of Ornamental Trees Using A New Index Based On Lidar And Kriging: A Case Study Of Plane Trees, Raúl Pecero-Casimiro, Santiago Fernández-Rodríguez, Rafael Tormo-Molina, Alejandro Monroy-Colín, Inmaculada Silva-Palacios, Juan Pedro Cortés-Pérez, Ángela Gonzalo-Garijo, J. M. Maya-Manzano
Articles
Ornamental trees bring benefits for human health, including reducing urban pollution. However, some species, such as plane trees (Platanus sp.), produce allergenic pollen. Consequently, urban maps are a valuable tool for allergic patients and allergists, but they often fail to include variables that contribute to the “building downwash effect”, such as the width and shape of streets and the height of buildings. Other factors that directly influence pollen dispersion (slopes and other geographical features) also have not traditionally been discussed. The LiDAR (Laser Imaging Detection and Ranging) technique enables one to consider these variables with high accuracy. This work proposes …
Estimation Of Dbh Using Tree Variables Derived From Aerial Lidar For Ford Forest, Baraga, Michigan, Tugay Demiraslan
Estimation Of Dbh Using Tree Variables Derived From Aerial Lidar For Ford Forest, Baraga, Michigan, Tugay Demiraslan
Dissertations, Master's Theses and Master's Reports
This study implemented LiDAR (Light Detection and Ranging) remote sensing technology and applied ITD (Individual Tree Detection) methods as an approach to estimate some essential tree variables, such as DBH (Diameter at Breast Height), height, volume, and biomass for Ford Forest Research Center in Upper Peninsula, Michigan. There were 34 deciduous (1 bigtooth aspen, 9 red oaks, 20 sugar maples, 2 white birches, and 2 yellow birches) and 17 coniferous (2 eastern hemlocks, 11 red pines, and 4 white pines) subject tree species. There were two different available LiDAR datasets from the same area that were collected in 2011 and …
Models Of Forest Inventory For Istanbul Forest Using Airborne Lidar And Spaceborne Imagery, Mustafa Kagan Ozkal
Models Of Forest Inventory For Istanbul Forest Using Airborne Lidar And Spaceborne Imagery, Mustafa Kagan Ozkal
Dissertations, Master's Theses and Master's Reports
Active remote sensing technology (LiDAR) and passive remote sensing technology (Pleiades and Göktürk-2 satellites) were used to find a meaningful relationship between ground data and remote sensing instruments for Istanbul Forest, Turkey. Two dominant species in the field, oak (deciduous trees) and maritime pine (coniferous trees), were researched. There were 86 plots total, 41 for maritime pine and 45 for oak. Three diameter at breast height (DBH) thresholds were studied. Trees of any DBH (DBH≥0.1 cm), trees ≥8 cm DBH thresholds and, trees ≥10 cm DBH thresholds. Both satellite image metrics were derived from Grey Level Co-occurrence Measures (GLCM). All …
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs
Theses and Dissertations
NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.
A Comparison Of Lidar Generated Channel Features With Ground-Surveyed Channel Features In The Little Creek Watershed, Ryan M. Hilburn
A Comparison Of Lidar Generated Channel Features With Ground-Surveyed Channel Features In The Little Creek Watershed, Ryan M. Hilburn
Master's Theses
Detecting change in stream channel features over time is important in understanding channel morphology and the effects of both natural and anthropogenic influences. Channel features historically, and now currently, are being measured using a variety of ground survey techniques. These surveys require substantial time commitments and funding to complete. Light Detection and Ranging (LiDAR) is an airborne laser mapping technology that holds promise to provide an alternative to ground-based survey methods. For this study, ground surveys were used to verify the accuracy of data collected using airborne LiDAR. Fifty nine cross-sectional profiles were surveyed in the Little Creek watershed at …
Assessment Of Canopy Fuel Loading Across A Heterogeneous Landscape Using Lidar, Kenneth L. Clark, Nicholas Skowronski, Michael Gallagher, Nicholas Carlo, Michael Farrell, Melanie R. Maghirang
Assessment Of Canopy Fuel Loading Across A Heterogeneous Landscape Using Lidar, Kenneth L. Clark, Nicholas Skowronski, Michael Gallagher, Nicholas Carlo, Michael Farrell, Melanie R. Maghirang
Joint Fire Science Program Research Project Reports
Our research used light detection and ranging (LiDAR) systems coupled with sequential harvesting of Pitch pine (Pinus rigida Mill.) to quantify canopy fuels in three dimensions across a large, heterogeneous landscape impacted by multiple wildfires, prescribed burns and insect defoliation events. We used a three-tiered approach; 1) calibration of upward sensing profiling LiDAR data with sequential harvesting of 20 x 20 meter plots to quantify the mass of foliage, branches and stems in Pitch pine canopies in 1-meter height layers, 2) scaling results to the landscape scale using previously-published relationships between upward sensing and downward sensing scanning LiDAR systems in …