The upper Campanian Castlegate Sandstone in the Book Cliffs of Utah is a highly amalgamated fluvial sandstone well known as a reservoir analog for oil and gas. It comprises the lower Castlegate, the formation capping Bluecastle Tongue, and the floodplain-rich middle Castlegate deposits. The Castlegate is among the most studied fluvial deposits in the world. Despite this, there has yet to be a fluvial architecture analysis completed for these deposits which consider the longitudinal variance within the Castlegate fluvial system. This project assesses the average channel depth and discharge for the lower Castlegate, allowing analysis of the relationship between channel depth and discharge and their effect on facies distribution, depositional style and fluvial architecture in the outcrops. The lower Castlegate Sandstone is a tributary fluvial system with paleocurrents oriented primarily W-NW to E-SE comprised of stacked braided fluvial sands updip, and large, higher flow straight-meandering trunk channels downdip. Distal outcrops show three distinct depositional styles with the first representing a period of highstand during which carbonaceous floodplain and small channels of 0.5-1 m in depth and maximum 4 m in width were deposited; the second represents a localized tectonic uplift with large channels of ~15 m in width and depth and lateral accretion sets scaled accordingly, and finally the capping units of small amalgamated sands composed of classic braided style channels which represent a period of lowstand.

This study characterizes the sediment transport dynamics of the fluvial portion of the DeGrey River delta, a dryland tide/wave-dominated delta along the Pilbara coast of northwestern Australia. The primary focus lies in the discernment of discrete deposits resulting from annual flood events in this ephemeral river, primarily driven by cyclones and tropical depressions during the austral summer.

Methodology combines water discharge data, digital elevation models (DEM), and Sentinel-2 change detection to model flow depth and flooding extent during storm events, linking it to riverbed shear stress and the formation of discrete flood deposits. A time series of DEM datasets, consisting of a 1-m aerial survey (2021) and drone photogrammetry surveys (2022 and 2023) were used to generate differential DEMs to accurately detect yearly morphological changes within the river channel. Field surveys of selected sites indicating presence of flood deposits enabled characterization of grain size, water flow, and structural elements.

Cyclone floods in the region cause propagation of preexisting dunes, unit bars, and compound bars. These events predominantly shape lower-flow-regime structures within medium-grained sand. Unit bars exhibit down-climbing cross-stratified sets, with variations in thickness contingent on their location within the channel ranging from 0.4-1.6 meters. Lower-flow-regime bar and bedform morphology persists and propagates between flows, despite the occurrence of intense flash floods, often generating discharges in excess of 100,000 ML/day. This challenges conventional expectations of channel excavation and the preservation of upper-flow-regime bedforms in the wake of such extreme events.

Surface water plays a critical role in meeting Texas’s water demands, particularly for municipal use. In the State of Texas, there are 188 major water reservoirs, 15 major river basins, and 8 coastal basins. These water sources serve as the lifeline of Texas’ urban and agricultural populations. In our study, we will be examining how proximity to these sources affects development, particularly focusing on population density to determine the type of population (urban or agricultural). Our findings have the potential to provide insights that can inform city water departments near major water resources with high population density and aid with water demand and scarcity management.

This study investigates the intricate relationship between population growth and energy demand, aiming to identify trends and patterns that inform future energy planning. Through comprehensive analysis, utilizing data spanning geographical regions of the US and the period 2000-2021, the study assesses the impact of population growth on energy consumption. Data from the US Energy Information Administration will be utilized for electricity and energy data, while data from the US Census will be used for population data. The analysis will focus on examining how population changes affect energy demand, and conversely, how changes in energy demand influence the sources from which energy is produced. This analysis aims to provide insights into predicting future energy usage, production sources, and demand patterns as the population continues to grow. The findings underscore the pressing need for sustainable energy solutions as the population continues to increase, providing valuable insights for policymakers and stakeholders to navigate the complexities of energy planning and management.

Global climate change, due to increases in greenhouse gas emissions, is a prevailing issue that is projected to continue with heightened impacts on extreme weather events, desertification, and human health. Our project draws connections between resilience to climate change and the molecular composition of organic molecules found in soil.

Through assessments of the carbon (C), hydrogen (H), and oxygen (O) content and composition of organic molecules in soils can be determined. Specifically, through assessments of C-number (Cn), H/C and O/C ratios of organic molecules, we can determine how well different soils and soil types can sequester carbon and ultimately support climate resiliency. Higher Cn in organic molecules indicate more carbon storage capacity while lower O/C and H/C ratios in organic molecules indicate more stable carbon that is resistant to release as CO2 to the atmosphere. Our research will compare Cn, O/C and H/C data of organic molecules in soils from across the United States to identify possible trends in carbon sequestration potential across regions of the conterminous US.

The data to be used is raw Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data from the “One thousand soils for molecular understanding of belowground carbon cycling” project (Bowman et al.). We first plotted the soil samples on Van Krevelen diagrams, which visualize each molecule as a point with O.C and H.C ratios, and we made frequency distributions to understand the largest organic molecular formula for each sample. We then plotted the maximum organic formula from each soil onto a new Van Krevelen diagram, where we compared the different samples to see which ones had higher overall carbon content. We hope to find a connection between soil composition and U.S. regions from which we will then make predictions on potential for carbon sequestration and, ultimately, the ability of these regions to remain resilient and sequester carbon during climate change.

The regional geological framework of the area I am studying involves a possible major northwest-trending Cambrian to Ordovician rift zone with abundant igneous rocks in parts of Colorado. These igneous rocks may be related to large volumes of Cambrian igneous rocks located along the same trend in southern Oklahoma. My project focuses on plutonic igneous intrusions located in the Wet Mountains in the southern part of the Front Range and in the Powderhorn District farther west. The goal of this project is to discover whether the rocks in Colorado formed during the same major magmatic event as those in Oklahoma. I will be studying thin sections of rock samples from Colorado utilizing a petrographic microscope. I will describe and identify the main igneous minerals from the samples, some of which are rare. I will also study the igneous textures and alteration products in the samples. Geochemical studies in progress will build on these results and will allow detailed comparison with the southern Oklahoma igneous rocks.

The Eagle Ford Shale (EFS) is an unconventional Cretaceous play producing crude oil and gas extending from northeast Leon County to the Mexico-American border in Southwest Texas. This Cenomanian -Turonian formation records the drowning of the Texas carbonate shelf and transgression of the Western Interior Seaway (WIS) into North America. Regional depositional patterns were affected by a series of changes in tectonic activity and eustatic sea level. The formation recorded a distinct change in oceanography during the Oceanic Anoxic Event 2 (OAE2) between the lower and upper EFS sections. The Boquillas Formation, age equivalent to the EFS, is found west of the producing region in Big Bend State and National Park. Outcrops of the EFS can be found along the Ouachita orogen and in the Big Bend region due to tilting during the Laramide orogeny and intrusive igneous activity. The largest known EFS equivalent outcrops have been found within the state park, however, no data had been collected in these locations. Evaluation of the geochemical properties and redox indicators of the depositional environment is essential to understanding the potential for hydrocarbons. The main method to acquire this data has been through the X-Ray Fluorescence Spectrometer (XRF). For this study I have utilized two handheld analyzers, the XRF along with the Laser Induced Breakdown Spectrometer (LIBS) for outcrop and core samples. Using both methods produces a more complete element suite including light elements not offered by XRF alone. Additionally, comparing LIBS data to the widely used XRF analyzer allows me to determine the practical usage of LIBS in petroleum geology.

It is well documented that the major sorbents in soils are organic matter, silicate clays, and metal-oxyhydroxides. In particular, interactions between organic matter and fine-grained minerals, such as aluminum oxides, have been cited as important stabilizers of the humic matter in soils, which has large implications for the storage of anthropogenic carbon and pollutants (i.e., hydrophobic organic acids) in the environment (Keil and Mayer 2014). Utilizing simple organic acids containing functional groups present in humic compounds enhances understanding of metal-hydroxide and organic acid interactions at the mineral-water interface. The energetics of these interactions largely depend on the sorbate, the physico-chemical characteristics of the sorbent, and solution conditions (e.g. pH).
Ongoing work in our lab, using flow-adsorption microcalorimetry (FAMC) to directly and systematically measure energy dynamics of sorption at the oxide-water interface indicated that structural water in the lattices of boehmite and boehmite-bayerite mixed-phased samples increased binding energetics of acetate, propionate and butyrate at pH 5. The presentation will cover energy dynamics data collected for these mono-carboxylates and their respective di-carboxylate counterparts (oxalate, malonate, and succinate) binding onto a series of synthesized boehmites and bayerites. Focus will be placed on resolving effects of carboxylate carbon chain length, the number and acidity of carboxylates, and aluminum oxide surface properties on binding dynamics.

A major Cambrian rift zone containing abundant igneous rocks is present in southern Oklahoma and trends northwest from the ancient continental margin. Previous geologists have mapped numerous igneous intrusions in Colorado that follow the same trend, ranging from Cambrian to Ordovician in age, and have speculated that these intrusions may be a part of the same rift. These intrusions include abundant igneous dikes of various compositions that originated from deeper magmatic bodies, filling fracture systems in older igneous rocks and Precambrian gneisses. This study involves the microscopic analysis of samples we collected from different dike types, including diabase, trachyte, and lamprophyre. Diabase is a common intrusive basaltic rock that develops coarser grains due to slower cooling and represents partial melt from the mantle that fills fractures in the upper crust. For our samples, trachyte refers to igneous dikes containing large crystals of K-feldspar within a distinctive red-colored, fine-grained matrix. Magmas of this composition are typically associated with intraplate rift zones. Lamprophyre is a rare intrusive igneous rock that has large crystals of biotite and amphibole in a finer matrix of feldspar and mafic minerals. While rare, this rock is also associated with intraplate rift zones. We also sampled one significantly younger basalt dike that intrudes Cenozoic volcanic rock to compare with the much older diabase dike samples.
Nine of our samples come from the Wet Mountains in the southern part of the Front Range in Colorado, and we also have an additional five samples of diabase dikes along the Front Range ~100 km to the north. Analysis of thin sections of these samples under the petrographic microscope will provide insight into their exact mineralogical compositions as well as their igneous textures. This work will provide a framework for geochemical analyses of the dikes, which is currently underway. The results will help determine whether the Colorado intrusions are directly related to the southern Oklahoma rift.

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.