Urban forest ecosystem analysis using fused airborne hyperspectral and lidar data

Urban trees are strategically important in a city's effort to mitigate their carbon footprint, heat island effects, air pollution, and stormwater runoff. Currently, the most common method for quantifying urban forest structure and ecosystem function is through field plot sampling. However, taking intensive structural measurements on private properties throughout a city is difficult, and the outputs from sample inventories are not spatially explicit. The overarching goal of this dissertation is to develop methods for mapping urban forest structure and function using fused hyperspectral imagery and waveform lidar data at the individual tree crown scale. Urban forest ecosystem services estimated using the USDA Forest Service’s i-Tree Eco (formerly UFORE) model are based largely on tree species and leaf area index (LAI). Accordingly, tree species were mapped in my Santa Barbara, California study area for 29 species comprising >80% of canopy. Crown-scale discriminant analysis methods were introduced for fusing Airborne Visible Infrared Imaging Spectrometry (AVIRIS) data with a suite of lidar structural metrics (e.g., tree height, crown porosity) to maximize classification accuracy in a complex environment. AVIRIS imagery was critical to achieving an overall species-level accuracy of 83.4% while lidar data was most useful for improving the discrimination of small and morphologically unique species. LAI was estimated at both the field-plot scale using laser penetration metrics and at the crown scale using allometry. Agreement of the former with photographic estimates of gap fraction and the latter with allometric estimates based on field measurements was examined. Results indicate that lidar may be used reasonably to measure LAI in an urban environment lacking in continuous canopy and characterized by high species diversity. Finally, urban ecosystem services such as carbon storage and building energy-use modification were analyzed through combination of aforementioned methods and the i-Tree Eco modeling framework. The remote sensing methods developed in this dissertation will allow researchers to more precisely constrain urban ecosystem spatial analyses and equip cities to better manage their urban forest resource

Student-Athlete Compensation: An Alternative Compensation Model for All Athletes Competing in NCAA Athletics

The Ed O’Bannon case (O’Bannon v. National Collegiate Athletic Association, 2015) has brought student-athlete compensation to the national spotlight. While the NCAA continues to defend its policy of amateurism, the time for college athlete compensation may soon become a reality (NCAA Division I Manual, 2019). Recent college athlete compensation models have explored revenue sharing models similar to that of professional sports leagues, although previous research failed to develop a compensation model for athletes in sports beyond basketball and football (Huma & Staurowsky, 2013). The current research argues for a more applied, market economy compensation model to offer fair compensation to collegiate athletes. This model takes into account the revenues generated by each university team, while also accounting for both the student-athlete and team’s performances on and off the field. Justifications for this model are explored, as this model will allow for a new way to compensate athletes via on and off-field metrics. This paper concludes with an example of the model’s utility through using publically accessible data for a major Division I college program

Combined inhibition of Bcl-2/Bcl-xL and Usp9X/Bag3 overcomes apoptotic resistance in glioblastoma in vitro and in vivo

Despite great efforts taken to advance therapeutic measures for patients with glioblastoma, the clinical prognosis remains grim. The antiapoptotic Bcl-2 family protein Mcl-1 is overexpressed in glioblastoma and represents an important resistance factor to the BH-3 mimetic ABT263. In this study, we show that combined treatment with ABT263 and GX15-070 overcomes apoptotic resistance in established glioblastoma cell lines, glioma stem-like cells and primary cultures. Moreover, this treatment regimen also proves to be advantageous in vivo. On the molecular level, GX15-070 enhanced apoptosis by posttranslational down-regulation of the deubiquitinase, Usp9X, and the chaperone Bag3, leading to a sustained depletion of Mcl-1 protein levels. Moreover, knock-down of Usp9X or Bag3 depleted endogenous Mcl-1 protein levels and in turn enhanced apoptosis induced through Bcl-2/Bcl-xL inhibition. In conclusion, combined treatment with ABT263 and GX15-070 results in a significantly enhanced anti-cancer activity in vitro as well as in vivo in the setting of glioblastoma. Both drugs, ABT263 and GX15-070 have been evaluated in clinical studies which facilitates the translational aspect of taking this combinatorial approach to the clinical setting. Furthermore we present a novel mechanism by which GX15-070 counteracts Mcl-1 expression which may lay a foundation for a novel target in cancer therapy

Urban forest ecosystem analysis using fused airborne hyperspectral and lidar data

Urban trees are strategically important in a city's effort to mitigate their carbon footprint, heat island effects, air pollution, and stormwater runoff. Currently, the most common method for quantifying urban forest structure and ecosystem function is through field plot sampling. However, taking intensive structural measurements on private properties throughout a city is difficult, and the outputs from sample inventories are not spatially explicit. The overarching goal of this dissertation is to develop methods for mapping urban forest structure and function using fused hyperspectral imagery and waveform lidar data at the individual tree crown scale. Urban forest ecosystem services estimated using the USDA Forest Service’s i-Tree Eco (formerly UFORE) model are based largely on tree species and leaf area index (LAI). Accordingly, tree species were mapped in my Santa Barbara, California study area for 29 species comprising >80% of canopy. Crown-scale discriminant analysis methods were introduced for fusing Airborne Visible Infrared Imaging Spectrometry (AVIRIS) data with a suite of lidar structural metrics (e.g., tree height, crown porosity) to maximize classification accuracy in a complex environment. AVIRIS imagery was critical to achieving an overall species-level accuracy of 83.4% while lidar data was most useful for improving the discrimination of small and morphologically unique species. LAI was estimated at both the field-plot scale using laser penetration metrics and at the crown scale using allometry. Agreement of the former with photographic estimates of gap fraction and the latter with allometric estimates based on field measurements was examined. Results indicate that lidar may be used reasonably to measure LAI in an urban environment lacking in continuous canopy and characterized by high species diversity. Finally, urban ecosystem services such as carbon storage and building energy-use modification were analyzed through combination of aforementioned methods and the i-Tree Eco modeling framework. The remote sensing methods developed in this dissertation will allow researchers to more precisely constrain urban ecosystem spatial analyses and equip cities to better manage their urban forest resource

The Dangers of Responsibilities Assigned to Concussed Athletes: Editor: Thomas H. Sawyer

©, Copyright SHAPE America. A high school freshman suffered post-concussive syndrome after receiving multiple head injuries stemming from assigned actions in the physical education classroom and extracurricular school-sponsored activities

The Dangers of Responsibilities Assigned to Concussed Athletes

High school freshman suffered post-concussive syndrome after receiving multiple head injuries stemming from assigned actions in the physical education classroom and extracurricular school-sponsored activities (Wellman v. Butler Area School District, 2017)

Using advanced airborne remote sensing as a sampling tool to support forest inventory in interior Alaska, USA

104323326

Downloaded from

Citations (this article cites 17 articles hosted on th