Switchgrass generates cellulosic ethanol, classified as an alternative fuel by federal definition. For switchgrass and other vegetation to become biofuel we have to look specifically at the cellulose microfibril and extract the glucose. This extraction leads to the fuel being produced. Switchgrass can deposit organic matter deep within the soil profile as the roots expand into the subsoil for nutrients and water. Not only is switchgrass a good biofuel product, but the carbon sequestration that comes along with planting this grass is highly beneficial. Due to the roots reaching deep into the soil, switchgrass is low maintenance while adding nutrients.
In this project, we will be researching possible farms in Saskatchewan, Canada preferably in close proximity to ethanol biorefinery plants for maximum switchgrass plantation, in order to seek possible expansion of biofuel production in Saskatchewan. We will be looking at farms, proximity of farms to biorefineries, and soil make up.

Switchgrass generates cellulosic ethanol, classified as an alternative fuel by federal definition. For switchgrass and other vegetation to become biofuel we have to look specifically at the cellulose microfibril and extract the glucose. This extraction leads to the fuel being produced. Switchgrass can deposit organic matter deep within the soil profile as the roots expand into the subsoil for nutrients and water. Not only is switchgrass a good biofuel product, but the carbon sequestration that comes along with planting this grass is highly beneficial. Due to the roots reaching deep into the soil, switchgrass is low maintenance while adding nutrients. In this project, we will be researching possible farms in Saskatchewan, Canada preferably in close proximity to ethanol biorefinery plants for maximum switchgrass plantation, in order to seek possible expansion of biofuel production in Saskatchewan. We will be looking at farms, proximity of farms to biorefineries, and soil make up.

Urbanization is an ever-growing problem that has led to habitat loss, habitat degradation, the spread of diseases, and so much more. Wildlife are slowly being pushed out of their historic home ranges, increasing human-wildlife conflicts. As a result, there has been a push to restore lost habitat and mitigate habitat destruction. However, this can be made tricky when managers are unaware of what makes a habitat suitable. Thus, there is an immediate need to determine ways of identifying environments favored by many species and implement conservation plans. Conducting present/absence surveys on animals and placing the sightings on a map is one way of determining where a species can be found. The purpose of this research will be to study the effects of urbanization on raccoons within parks in the Fort Worth area. Parks are valuable habitats for organisms in an urban environment as these parks have resources not found in highly human-disturbed areas such as neighborhoods or shopping districts. We will be comparing the raccoon sightings from iNatrualist, a citizen science platform, to different parks in the surrounding area to determine habitat suitability. We used GIS data from iNatrualist to compare raccoon sightings to habitat type. Habitat was divided into four categories: concrete, open field, water, and field with trees. Pictures of the study site were used to train Mulrispec, a multispectral image data analysis system, to identify areas that meet the habitat types. The distribution data was overlaid on top of the new map. Raccoon sightings were compared to habitat types to determine habitat preference. By identifying suitable habitats, we hope to learn how raccoons and other urban organisms are adapting to rising urbanization.

This project uses GIS to take a look at multiple layers of spatial data to identify possible relationships between COVID-19 and a variety of social and economic factors impacting social vulnerability in Tarrant County, Texas in the year 2020. The purpose of this research is to better understand trends of widespread public health events and factors that may contribute their severity. A variety of techniques are used to map COVID-19 rates for each city and to visualize differences in social vulnerability across the county. Furthermore, GIS is used to analyze social vulnerability and access to hospitals in order to identify areas underserved by medical care. From there, recommendations for new hospital locations are established.

For this project, we used GIS remote sensing technology to locate and identify potential locations for urban farming. The purpose of this project is to recognize and assist in the issue of food deserts in areas such as the DFW (Dallas Fort Worth) metroplex. A food desert refers to any area with limited or no access to affordable, nutritious food. This may include a lack of access to farmers’ markets, vegetable shops, or fresh produce. This project aims to recognize and assist in the issue of food deserts in urban areas with a particular focus on the East Fort Worth/Arlington area of Tarrant County. Several relevant datasets including high spatial resolution commercial remote sensing and other relevant spatial (such as property appraisal datasets, land temperature data) and non-spatial datasets. These will be combined in a GIS environment to identify empty plots of land that could be used for the purposes of urban agriculture while assessing their potential for food growth. Once these plots of land are identified, we will use ArcGIS to assess ecosystem services provided by these urban farms, such as the impact on climate and urban heat.

Saltwater Intrusion Along the Texas Gulf Coast: Tracking Wetlands Distribution, Adaptation, and Migration

Abstract

Climate change trends in recent decades have led to sea level rise (SLR) due to increased polar ice melting. As the sea level rises, saltwater concentrations increase inland, compelling wetland species to adapt or migrate. This added stress on wetland species hampers their ability to offer ecosystem services (ES). This study will investigate the impact of saltwater intrusion (SWI) on coastal wetland species along the Texas Gulf Coast. Supervised and unsupervised classification will be the primary methods used to accurately assess the loss, gain, or migration of different groups of wetland species over two decades. Additionally, the potential effect of wetland distribution and species changes on the ES will be investigated by analyzing the spatial extent of storm surge flooding resulting from land-falling hurricanes two decades ago versus the present.

This research assesses the relationship between income per capita and the amount of maintenance received for the major roads across the State of Texas. Relevant datasets and analysis techniques such as demographic (census data), population density (distribution), road network, maintenance records, etc. will be carried out using ArcGIS Pro software. A series of maps highlighting analysis results derived based on the various parameters will be produced to provide a comprehensive overview of the relationship between the variables, if any, that would be useful for future decision-making.

Sinkhole hazards pose a major threat to key infrastructure and human lives in Taylor and Jones counties in West Central Texas. These counties are underlain by soluble evaporite and carbonate rocks. In this study, a data fusion approach was adopted in which multi-source datasets and techniques were combined to detect and map the spatial distribution of sinkholes, quantify their displacement rates, and identify the processes and factors controlling their occurrence. Preliminary results indicate: (a) there is a spatial correspondence between depressions (area: 625 m2 - 2500 m2) identified using Light Detection and Ranging (LIDAR) datasets and previously- mapped sinkholes; (b) deformation rates over the mapped depressions derived using Persistent Scatterer Interferometry technique applied on 53 level-1 Sentinel-1 images (2016 – 2021) and calibrated using long-term (2006 – 2021) GNSS data indicate an average and peak subsidence rates of -6 mm/yr and +5 mm/yr, respectively; (c) clusters of high subsidence rates were noted over areas underlain by evaporites belonging to the Clear Fork Group; (d) efforts to validate the accuracy of the sinkhole detection techniques are currently underway using 2D Electrical Resistivity Tomography (ERT) surveys carried out on the identified subsiding depressions. In addition, groundwater level and discharge time series and other relevant datasets are being integrated to assess the processes and factors that induce the formation of these features. Results of this study could be used to develop an early warning system to implement mitigation strategies to curtail the impacts of the sinkhole hazards in Texas and other parts of the globe.

The Mendocino National Forest was affected by fire in August 2020. It devastated a substantial area of land over the period of three months, resulting in hundreds of millions of dollars in damage and the evacuation of thousands of people. Moreover, many of the local plantations were destroyed. To evaluate the severity of the impacted area for rehabilitation and restoration, severity data and maps are crucial. This study will combine several geospatial data including multitemporal remote sensing data to identify changes in forest structure and moisture content affected by the fires through burn severity maps. This study will use the Normalized Burn Ratio (NBR) technique to identify burned areas and provide a measure of burn severity. The NBR is calculated as a ratio between the NIR and SWIR values bands 5 and 7 obtain from pre-fire and post-fire Landsat 8 imageries. This will be followed by generating the Differenced Normalized Burn Ratio (ΔNBR) for pre and after-imageries to map the fire severity. The result of the NBR analysis will be integrated with the Normalized Difference Vegetation Index (NDVI) to map vegetation greenness over the study area that will be helpful to validate the accuracy of the NBR analysis. Moreover, elevation dataset (Digital Elevation Model (DEM)) will be used to assess factors that exacerbate emerging wildfires such as topography and slope.

The objective of this research is to conduct wind farm suitability analysis (for energy generation) with a focus on areas that either heavily rely non-renewable sources of energy (parts of Australia) or areas that have limited access to energy. The study will combine several spatial datasets (road networks, population distribution, high mean windspeed, etc.) and analysis products (proximity to roads, national grids, etc.) to determine, through the suitability analysis, whether the wind energy is ideal and economical source of energy for the investigated areas.

As we move further into the 21st century, Earth's functional processes are experiencing a steady shift, particularly in terms of climate and sea levels. Anthropogenic warming has accelerated the rise of sea levels and increased the frequency, intensity, and rainfall of cyclones and hurricanes. To investigate the impact of rising sea levels on storm surges in vulnerable areas, we utilized remote sensing and GIS technology to come up with an understanding of the influence land cover type has on flood intensity and assess the vulnerability of the Houston area based on storm surges from 2015 - 2022. Our findings underscore the critical need for urgent adaptation and mitigation measures to mitigate the risks associated with changing weather patterns and rising sea levels.

The purpose of this project was to identify the best market demographic in the South Florida area (Miami-Dade, and Broward County) for Fizgig. Fizgig a newly developed pet sitting app, is launching their app soon and we need to analyze market demographics to help aid with a successful app launch. Fizgig aims to connect certified pet sitters to pet owners with ease and affordability. Fizgig is not restricted to just cats and dogs, but all pets. Fizgig provides opportunities for those who are certified in pet sitting and want to grow there career in such disciplines. Furthermore, to analyze the capability of a successful launch we used Esri and Google Maps data of median household income, average annual pet spending, and pet sitting association data to pinpoint specific areas (hotspots) in South Florida to focus on the app launch. We concluded that Southeast Miami-Dade, Northwest Broward, and West Broward hotspots had the highest potential for pet sitting employment and app use due to highest pet expenditure in correlation to median income in there respective counties in addition to a high number of pet sitting associations within a close radius of these hotspots.

For our research project, we plan to use GIS remote sensing technology to locate and identify potential land plots for urban farming. The purpose of this project is to recognize and assist in the issue of food deserts in urban areas such as the DFW (Dallas Fort Worth) metroplex, NYC, and Los Angeles. A food desert refers to any area with limited or no access to affordable, nutritious food. This could include a lack of access to farmers’ markets, vegetable shops, or fresh produce. This project aims to recognize and assist in the issue of food deserts in urban areas with a particular focus on the East Fort Worth/Arlington areas in Tarrant County. Several relevant datasets including high spatial resolution commercial remote sensing and other relevant spatial (such as property appraisal datasets, soil data) and non-spatial datasets, and data analysis products (such as the proximity of the areas to fresh produce/major grocery stores) will be combined in a GIS environment to identify empty plots of lands that could be used for the purposes of urban agriculture and assess their potential for food growth.

The greater East Texas Basin represents the portion of the Cretaceous Texas Shelf north of the San Marcos Arch, proximal to the Woodbine siliciclastics sourced from the Ouachita and Sabine uplifts. During the Early to Middle Cenomanian the basin underwent a time-transgressive transition from an oxygenated carbonate platform to an anoxic shelf. The Cenomanian-Turonian aged Woodbine and Eagle Ford Groups have been studied since the late 1800’s; a confusing nomenclature system has been developed for them due to outdated biostratigraphic studies and inaccurate age interpretations, obscuring the age relationships of the various lithostratigraphic units. To study this time-transgressive transition and better understand and define the Woodbine-Eagle Ford contact in north Texas, stratigraphic and X-ray Fluorescence (XRF) geochemical data will be collected from USGS near-surface cores drilled in Dallas and Grayson counties, and paired with X-ray diffraction (XRD), inductively coupled plasma-mass spectrometry (ICP-MS), and core spectral gamma ray data provided by the USGS, and biostratigraphic data provided by Denne. Field work will also be conducted on several outcrop locations in the Dallas-Fort Worth (DFW) Metroplex for detailed descriptions and measured sections to be made as well as sample collection for thin section, detrital zircon, and further XRF analysis. The data collected for this study will be used to lithostratigraphically and geochemically define the Woodbine-Eagle Ford transition zone in north Texas with the intent of determining the paleoceanographic conditions during deposition, and determine if this transition is time-transgressive across the DFW Metroplex and North Texas region.

Current in-situ assessments of water quality in lakes can be significantly improved by leveraging recent advances in remote sensing and algorithm development for a faster and more cost-effective approach. This study leveraged satellite- (Landsat 7/8 and Sentinel-2) and UAV-based remote sensing datasets to detect and monitor changes in key water quality parameters (Chlorophyll-a (Chl-a) and turbidity) within the epilimnion of Lake Arlington (Texas) during the past 20 years. In addition, remote sensing algorithms were developed to capture the spatial variability of the water quality parameters across the entire extent of the water body. The investigation period was divided into two segments: before and after the EPA-established Watershed Protection Plan program (WPP) in 2012 to mitigate the lake's water quality deterioration. A regression model, using satellite-based and historical in-situ observations (2002 – 2020), was developed to predict the targeted water quality parameters across the extent of the lake. Our preliminary results indicate: (1) Chl-a levels at the lake's inlet decreased significantly after 2012 (before: 32.1ug/L; after: 9.2ug/l); also turbidity (via Secchi Disk Depth) across the lake decreased after 2012 (before: 0.6 m; after: 0.5 m); and the spring season had the highest levels of Chl-a followed by the summer season for both before and after 2012 while high turbidity values also coincided with high Chl-a values in the summer, (2) regression analysis revealed a high correlation between the in-situ Chl-a and Landsat (before 2012: spring R2 = 0.62, summer R2=0.66; p-value < 0.01; after 2012: spring R2 = 0.54, summer R2=0.73; p-value < 0.01) and Sentinel-2 bands (2015-2020: spring R2 = 0.99, summer R2=0.82; p-value >0.05). Similarly, the regression analysis revealed a high correlation (2015-2020: spring R2 = 0.98, summer R2=0.57; p-value >0.05) between reflectance from Sentinel-2 bands and in-situ turbidity levels; (3) The optimum spectral band to detect Chl-a was found to be between 590-880nm for Landsat and 665-940 nm for Sentinel-2 while for turbidity it was between 450-670nm for Landsat and 560-705nm for Sentinel-2. Therefore, Sentinel-2 bandwidth was better at detecting Chl-a and turbidity levels in the lake because of its wider bandwidth; (4) Water quality controlling factors in lake Arlington include landcover change, precipitation rates, and the EPA WPP measures. Landcover change between 2001 and 2019 shows an overall 25% increase in urban areas, a 9.5% increase in wetlands, and a 10.7% decrease in grassland which may have contributed to the decline in Chl-a and turbidity values. Finally, efforts to calibrate and improve the accuracy of the satellite-based observations are underway with UAV-acquired multispectral imagery obtained at the time of the Sentinel-2 overpass over the lake.

Given the drastic rise in renewable energy investment across the US and globally, along with global sustainable development goals, it is important to develop techniques for renewable resource assessment. The study aims to identify the most suitable areas for renewable energy development in Texas by analyzing various geospatial factors that influence renewable energy production, such as terrain and land use. Resource-specific data such as surface direct normal irradiance (DNI) and wind speed and power density were used to ensure resource availability. Proximity to important infrastructure was also considered, access to infrastructure is an important economic consideration for utility-scale installation. Products generated use an integration of remote sensing data, geospatial analysis, and machine learning algorithms to develop a spatially-explicit multi-criteria decision analysis (MCDA) for solar and wind resources in Texas.

This study will develop (livable) suitability index for areas within Fort Worth with respect to the availability of various amenities (walkability, parks, etc.), public transport, proximity to fresh produce and entertainment (restaurants, etc.), and other relevant services. This is important as the City of Fort Worth has some of the lowest transit scores compared to major cities across the US especially with those having similar population as Fort Worth. Several spatial analysis techniques including proximity and overlay analysis will be undertaken using tools in ArcGIS Pro and ArcGIS Online to attain the objectives of the study.

As the nature and quantity of new/novel nanomaterials continue to expand to meet industrial, medical, and domestic demands, their accidental or intentional release becomes inevitable. To this end, an evolving understanding of the interaction dynamics between nanomaterials and naturally occurring geomaterials is central to supporting continued sustainable development and use of nanomaterials. The current study explores the chemodynamics of the organic nanomaterial, polyamidoamine (PAMAM) dendrimers, binding to (and debinding from) ferrihydrite. Specific focus is placed on how PAMAM size and pH affects the reaction between three carboxyl-terminated PAMAMs (Gx.5-COOH) sorbing/desorbing to/from the variably-charged ferrihydrite (FFH). Since both ferrihydrite and PAMAM exhibit pH-dependent variation of speciation, it is expected that binding/debinding dynamics of differing sizes of PAMAM will vary. Investigating the quantity, rate, and dynamics of these reactions provides insight into the type of bonding occurring (physiosorption, electrostatic bonding, or hydrogen bonding) and the location of bonding (surface versus micropore spaces). The information gained from this study will help to develop a more holistic picture of the environmental fate of synthetic nanomaterials.

In Tarrant County, Texas, food deserts affect approximately 275,000 residents. Chronic health conditions affect households living in food-insecure communities, leading the government to spend billions of dollars treating preventable diseases. Implementing sustainable urban agriculture in areas of high need to produce food using geospatial technology to aid in soil management can play an important role in helping farmers. The objective is to create an urban soil analysis map from the data collected on the soil properties, distribution, and variability of how these properties affect landscapes.

The aim for this project is centered around understanding carbon sequestration and the potential for carbon capture, utilization, and storage (CCUS) in the United States of America. An in depth look at the CO2 emissions for given areas of the U.S. will be looked at to gain an idea of where localized hotspots for emissions are located and how the impact of these emissions can be reduced using CCUS. By coupling emission data with existing infrastructure data (such as active and abandoned wells, pipelines, storage facilities, etc.) an outlook on the possibility of CCUS and reduction of emissions can be achieved. Geologic formations also play a specific role in how CCUS works. Understanding the various rock formations below and how the injected CO2 will be sealed away deep in the ground is a vital piece for any CCUS project. Combining the geological data with the emissions and infrastructure data will piece together a variety of information to better understand the possibility of reducing carbon emissions in various areas around the United States.

The Middle Cenomanian Woodbine sandstones act as a major reservoir system for many large oil fields throughout East Texas. Although numerous studies have been completed on Woodbine outcrops within DFW Metroplex, none have used modern techniques or tools, or utilized facies model concepts to study their reservoir characteristics or environment of deposition. Prior studies interpreted these outcrops as a shelf-strandplain coastal setting or a fluvial-dominated delta plain. However, this study of Woodbine outcrops along Lake Grapevine identified evidence of significant tidal influence.
The focus of this project was to determine the depositional environment and obtain a better understanding of the reservoir characteristics of the upper Woodbine (Lewisville) sandstones found in outcrop along the southeastern shores of Lake Grapevine in Tarrant County, TX. A detailed study of the lithofacies, ichnofacies, and biofacies, along with handheld spectral gamma ray and permeameter analyses, from 8 measured sections were conducted to identify representative lithofacies. Oversized thin-sections were made to estimate porosity ranges for each lithofacies, and to identify the types and extent of cement in the sandstones. Photomosaics were utilized to delineate sand body geometries by tracing out the lateral extent of the units and identifying significant surfaces and potential fluid barriers or baffles.
Seven lithofacies were distinguished in the outcrops of the study area: Bioclastic, massive bioturbated sandstone, mudstone, heterolithic sandstone and mudstone, crossbedded sandstone, flaser-bedded sandstone, and cemented sandstone. Two of the most common and laterally continuous lithofacies, the massive bioturbated and crossbedded sandstones, also had the best reservoir characteristics, with average porosities of 26% and 27%, and average measured permeabilities of 6,300 mD and 10,700 mD, respectively. The lower permeabilities in the massive bioturbated sandstone are related to clay-rimmed burrows. The bioclastic, mudstone, and cemented sandstone lithofacies are potential barriers to fluid flow, as they all have low porosities (less than 2%) and permeabilities (less than 200 mD).
The data acquired during this study were all consistent with an interpretation of a tidally-influenced estuarine to shallow marine depositional environment for the upper Woodbine in the study area, which differs from previous studies. The high abundance of trace fossils that are commonly found in tidally-influenced depositional systems, including Conichnus/Bergaueria, Cylindrichnus, Planolites, Palaeophycus, Rosselia, Rusophycus, Skolithos, and Thalassinoides, coupled with the presence of heterolithic deposits and common oyster shells led to this interpretation.
This study is the first to analyze outcrops of the Lewisville (upper Woodbine) sandstones in their type area specifically for their reservoir characteristics, and to document tidal influences during deposition. Considering the considerable volumes of hydrocarbons that have been produced from the Woodbine in the adjacent East Texas Basin, this study could provide valuable data for building reservoir models of upper Woodbine sandstones for both hydrocarbon production and potential CO2 sequestration.

This research will examine the change in size of local aquifers in Texas to determine how drought affects crop yield in Texas, for the aquifers scattered about Texas are the major source of irrigation for farmers in the state. This will be demonstrated by assessing conditions in the San Antonio area (as a case study) due to the severe drought that has affected the area for the past couple of months. Several spatial datasets including remote sensing datasets and results derived using different analysis tools in GIS will be utilized to demonstrate the change in aquifer size and volume during the investigated period.

More meteorites are found in North-West Africa every year than in any other location on the earth’s surface. These meteorites are sold and will either enter a scientific collection, or that of a private collector. In the latter case, a meteorite may never be officially classified, which means that it is not recognized by the scientific community as a new meteorite find.. The meteorite classification process is led by the Meteoritical Society, who nominate meteorite researchers to serve on the Meteorite Nomenclature Committee. This committee is responsible for the peer review of all meteorite classification submissions, and to ensure the donation of a scientific repository sample. After this, an official name is assigned and the meteorite is entered into the Meteoritical Bulletin Database (MetBull). MetBull is an archive of all meteorites recognized by the Meteoritical Society and contains basic information about each meteorite; for example, its classification, the location it was found, and a brief description of the sample studied.

The Monnig Meteorite Collection at TCU contains a number of unclassified meteorite samples. In this study, we will examine three unknown meteorites and determine the meteorite type in terms of: (1) the type of body they come from, (2) the minerals and textures they contain, (3) their mineral compositions and, (4) their thermal history. This data will then be submitted to the Meteorite Nomenclature Committee for official classification.

Excessive greenhouse gas emissions that result from unregulated energy exploitation contribute to climate change and air pollution. One way to restore the carbon balance within the earth’s systems is to increase carbon inputs by capturing atmospheric carbon and storing it in stable reservoirs, also known as Carbon Sequestration. Using the process of photosynthesis, plants absorb carbon dioxide from the atmosphere and convert it to organic carbon that is relatively more stable than gaseous carbon. The ability to sequester carbon varies across different vegetation species and the environments in which they grow. Using ArcGIS tools and free-access remote sensing data, this study will survey the spatial distribution of plant biomass and their effective carbon storage capacity in a case study located in Africa. The results from this study will i) identify facilities with the most effective carbon sequestration potential ii) help conservation programs in making landscaping decisions for future urban developments.

The 1.2 Ga Barby Formation located in SW Namibia is comprised of basaltic andesites and shoshonites from oblique subduction in a volcanic arc setting. Recent mapping and whole-rock geochemistry within the Barby Formation has been completed by previous TCU graduate students. Clinopyroxenes (CPX) from samples collected during these studies were analyzed using an Electron Microprobe (EMP) at Fayetteville State University, North Carolina. Data collected from CPX phenocrysts corresponds with previous findings that the samples can be divided into two groups. Group 1 samples show an enrichment in rare earth elements (REE) and light rare earth elements (LREE) Th, Zr, La/Yb, Nb, with a smaller Ti anomaly as compared to Group 2 (Lehman, 2019; Orhmundt, 2020). CPX phenocrysts within Group 1 have higher TiO2 wt% concentrations. Differences between the two groups are attributed to different source rock compositions and partial melting (Lehman, 2019; Orhmundt, 2020). Mineral compositions and cation ratios from EPMA data were also used to determine geothermobarometric conditions of the formation’s magma plumbing system. Single-clinopyroxene thermometry and barometry equations from Wang et al. (2021) and Purtika (2008) were utilized in this study. Wang et al. (2021) calculations resulted with average pressures between 1-3 ± 1.5 kbar and average temperatures between 1100-1200 °C. Purtika (2008) calculations resulted with overall higher pressures averaging at 3-5 kbar and slightly hotter temperatures at 1200 ± 50°C. Overall temperatures are higher than what would be expected in the basaltic andesitic system and variations could be due to the low-grade metamorphism the area has experienced that has affected the geochemistry.