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Browsing by Author "Vogeler, Jody, committee member"

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    Evaluation of UAS flight parameters for rapid monitoring of forest characteristics
    (Colorado State University. Libraries, 2020) Swayze, Neal, author; Tinkham, Wade T., advisor; Vogeler, Jody, committee member; Hudak, Andrew, committee member
    Forest managers are increasingly turning to finer spatial and temporal resolution data for monitoring forest structure in a rapidly changing world. Traditionally utilized networks of field plots for inventorying forest resources require significant time and financial investments; in response to this, remote sensing techniques have been investigated for providing inventory data across large extents. These methods, including light detection and ranging (LiDAR), require significant financial investment that limits the frequency of repeated surveys. Unmanned Aerial Systems (UAS) have emerged as potential alternatives for generating fine spatial and temporal resolution 2D and 3D data for modeling forest structure. The use of Structure from Motion (SfM) photogrammetry has made it possible to use UAS to collect aerial images and generate point clouds that can be used to model vertical forest structure information in a cost-effective way. Recent research has indicated that UAS-derived SfM point clouds are comparable to LiDAR point clouds for forest structure characterization through both area-based and individual tree observations. However, substantial knowledge gaps exist regarding the influence of UAS flight parameters on SfM-derived forest attributes. This thesis presents two studies to address these knowledge gaps. Specifically, Chapter 1 investigates the influence of UAS altitude and flight speed on modeling aboveground forest biomass through an area-based approach and Chapter 2 evaluates the influence of UAS altitude, camera angle, and flight pattern on extracted tree level and summarized plot and stand level attributes. Results show a strong positive relationship between flight altitude and plot-based aboveground biomass modeling, with UAS predictions increasingly outperforming (2-24% increased variance explained) contemporary LiDAR strategies as acquisition altitude increased from 80-120 m. When monitored at the individual tree level, UAS acquisitions conducted using a combination of crosshatch flight paths and off-nadir camera angles (20-30°) maximized tree detection rates (F-score of 0.77), correlations between stem mapped and extracted tree heights and DBHs (0.995 and 0.910, respectively), and estimates of stand and plot level basal area per hectare and TPH. These results indicate that UAS can be utilized to accurately summarize tree, plot, and stand level forest structure to assist in monitoring and planning of management prescriptions.
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    Partnering Indigenous and Western knowledge systems: a case study of Maasai perspectives on problematic plants in northern Tanzania's drylands
    (Colorado State University. Libraries, 2024) McCarty, Connor, author; Lynn, Stacy, advisor; Vogeler, Jody, committee member; Smith, Melinda, committee member
    Maasai are an Indigenous group native to the East African drylands who traditionally practice pastoralism, but their livelihoods are undergoing drastic changes as they become increasingly dependent on cultivation, adapt to climate change, and endure socio-political pressures, including for wildlife conservation. We wanted to understand Maasai communities' views on this landscape-level change using their Indigenous knowledge of plants as an indicator. In the first part of this research project, we asked members of five Maasai villages located in Tanzania's Simanjiro Plains about their experiences with problematic plants to identify and rank which plant species and plant characteristics they found to be most problematic from their perspective without influence from our team's biases. In the second part of the project, we introduced a participatory science tool, CitSci, into the community to collect geospatial data on these plants to created habitat suitability models for the three most problematic plants – Oltelemet (Ipomoea hildebrandtii), Alairahirah (Crotalaria polysperma), and Gugu caroti (Parthenium hysterophorus). Using quantitative and qualitative analyses, we evaluated participatory science's challenges and benefits in the community as a source of continuous engagement, collaboration, and local utility. This speaks to our greater goal: to embed two-eyed seeing in participatory social-ecological research. By utilizing both Indigenous knowledge and scientific tools from the Western scientific world, there is potential to improve academic research and help Indigenous researchers carry out locally focused and community-led projects without the oversight, influence, or harm from external forces common with Western-focused approaches. Using this project as an exploratory case study, our conceptual framework shows great promise.
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    The impact of wildfire on avian communities: exploring habitat associations two decades after fire
    (Colorado State University. Libraries, 2023) Vicini, Maria, author; Stevens-Rumann, Camille, advisor; Vogeler, Jody, committee member; Fornwalt, Paula, committee member
    Large high-severity wildfires have been affecting ponderosa pine dominated systems for decades, yet minimal long-term research has been conducted to address how avian species are responding to vegetation recovery and wildfire-driven conversion multiple decades after wildfire in ponderosa pine ecosystems of the southwestern United States. Understanding how community dynamics differ between low- and high-severity portions of burned footprints, and how vegetation structure relates to species presence is crucial for species conservation efforts, especially as wildfires in the western U.S. continue to have larger proportions of high-severity fire compared to historical fires. To address this in the Southwest, our study sought to quantify vegetation recovery, avian community dynamics across low- and high-severity sites, and quantify species-specific relationships with current vegetation structure in two post-fire footprints two decades after fire. This study focused on the Ponil Complex Fire in northern New Mexico and the Hayman Fire in southern Colorado, both of which burned in 2002. We found continued divergence between vegetation recovery at low- and high-severity sites, though this divergence was more pronounced at the Hayman Fire. We found also significant dissimilarities in avian community composition between low- and high-severity sites, and significantly lower species richness at high-severity sites across both wildfires. Forest-associated bird species presence was associated with more canopy cover and lower severity. Alternatively, lower canopy cover and higher severity were associated with the presence of a variety of grassland-, shrubland-, and desert-associated species. Our findings point to the importance of preserving pyrodiversity on the landscape to maximize suitable habitat for the greatest number of species, especially as it pertains to preserving adequate proportions of low-severity patches for forest-associated species who require intact canopy cover. However, large high-severity patches as the dominant component of the landscape will not support the most diverse array of bird communities 20+ years post fire.
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    Unmanned aerial systems for forest structure mapping: assessments of area-based and individual tree monitoring
    (Colorado State University. Libraries, 2020) Creasy, Matthew, author; Tinkham, Wade T., advisor; Vogeler, Jody, committee member; Hoffman, Chad, committee member
    Characterization of forest structure is important for management-related decision making, especially in the wake of disturbance. Increasingly, observations of forest structure are needed at both finer resolution and across greater extents in order to support managers in meeting spatially explicit objectives. Current methods of acquiring forest measurements can be limited by a combination of time, expense, and either extent or temporal resolution. Drone or UAS-based photogrammetry provides an airborne method of forest structure data acquisition at a significantly lower cost and time commitment when compared to existing methods of such as airborne laser scanning (LiDAR). A growing body of literature confirms UAS-based photogrammetry models can be as detailed as conventional LiDAR models. However, there exists a knowledge gap in best practice for data acquisition parameters and assessment of accurate characterization within forest photogrammetry. The following two chapters utilize large stem mapped sites to fill that knowledge gap by 1) systematically testing the effects of UAS flight speed and altitude on plot-based aboveground biomass modeling through photogrammetry and 2) evaluating several algorithms for detecting individual tree locations and characterizing crown areas. Results show a strong positive relationship between flight altitude and aboveground biomass modeling, with all UAS flights evaluated above 80 m altitude, providing better results (2-24% more variance explained) than contemporary LiDAR modeling strategies. Additionally, results demonstrate that the probability of detecting individual trees decays moving from the dominant overstory to suppressed trees, corresponding to >97% at the top of the canopy and decreasing to 67% for trees in the understory. Our results indicate the potential for UAS photogrammetry to produce highly detailed maps of forest biomass, as well as capture variation of forest structure through the detection of trees and tree groups. Such high-resolution data has the potential to become a much-needed tool for monitoring forest structures to inform spatially explicit management objectives. Additionally, these studies reinforced how UAS photogrammetry can provide low-cost repeat monitoring of forest conditions.