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Land is a natural resource that humans have utilized for life and various activities. Land use/land cover change (LULCC) has been of great concern to many countries over the years. Some of the main reasons behind LULCC are rapid population growth, migration, and the conversion of rural to urban areas. LULC has a considerable impact on the land-atmosphere/climate interactions. Over the past two decades, numerous studies conducted in LULC have investigated various areas of the field of LULC. However, the assemblage of information is missing for some aspects. Therefore, to provide coherent guidance, a literature review to scrutinize and evaluate many studies in particular topical areas is employed. This research study collected approximately four hundred research articles and investigated five (5) areas of interest, including (1) LULC definitions; (2) classification systems used to classify LULC globally; (3) direct and indirect changes of meta-studies associated with LULC; (4) challenges associated with LULC; and (5) LULC knowledge gaps. The synthesis revealed that LULC definitions carried vital terms, and classification systems for LULC are at the national, regional, and global scales. Most meta-studies for LULC were in the categories of direct and indirect land changes. Additionally, the analysis showed significant areas of LULC challenges were data consistency and quality. The knowledge gaps highlighted a fall in the categories of ecosystem services, forestry, and data/image modeling in LULC. Core findings exhibit common patterns, discrepancies, and relationships from the multiple studies. While literature review as a tool showed similarities among various research studies, our results recommend researchers endeavor to perform further synthesis in the field of LULC to promote our overall understanding, since research investigations will continue in LULC.

This paper presents an in-pixel contrast enhancement circuit that performs image processing directly within the pixel circuit. The circuit leverages HyperFET, a hybrid device combining a MOSFET and a phase transition material (PTM), to enhance performance. It can be tuned for different modes of operation. In foreground enhancement mode, it suppresses low-intensity background pixels to nearly zero, isolating the foreground for better object visibility. In contrast enhancement mode, it improves overall image contrast. The contrast enhancement function is customizable both during the design phase and in real-time, allowing the circuit to adapt to specific applications and varying lighting conditions. A model of the designed pixel circuit is developed and applied to a full pixel array, demonstrating significant improvements in image quality. Simulations performed in HSPICE show a nearly 6x increase in Michelson Contrast Ratio (CR) in the foreground enhancement mode. Furthermore, process variation and Signal-to-Noise Ratio (SNR) analysis has been conducted to evaluate the robustness of the design under manufacturing variations. The simulation results indicate its potential for real-time, adaptive contrast enhancement across various imaging environments.

Estuarine organisms have varying tolerances and respond differently to salinity. Bottom-dwelling species such as oysters tolerate some change in salinity, but salinity outside an acceptable range will negatively affect their abundance as well as their survival within this sensitive ecosystem. Salinity in the Apalachicola Bay is heavily influenced by freshwater inflow discharged from the Apalachicola River. In this study, artificial neural network (ANN) was applied to correlate the monthly salinity variations at an oyster reef in Apalachicola Bay to the river inflow and wind. Parameters in the ANN were trained until the simulated salinity data correlated well with the observations from 2005 to 2007. Once the model is trained and optimized, the ANN structure is verified comparing the simulated data to the second dataset from 2008–2010. Four neural network training algorithms, including gradient decent, scaled conjugate gradient, quasi-Newton, and Levenberg–Marquardt, have been evaluated. The scaled conjugate gradient algorithm was selected for this study because it provides the best correlation with the value of 0.85. The verified ANN model was applied to investigate the potential impacts of freshwater reductions from upstream river on the salinity in the oyster reef. By comparing the resulting salinity from ANN model simulations to the optimal salinity range for oyster growth, the impacts of freshwater reduction scenarios on oyster growth can be examined.

This thesis explores the intersection of trauma theory, social identity theory and dialogical approaches in the context of interfaith dialogue among Nigerian Christian and Muslim groups in Nigeria and the UK. Through ethnographic case studies focusing particularly on the Redeemed Christian Church of God (RCCG) and the Nasrul-lahi-li-Fathi Society of Nigeria (NASFAT), this thesis critically examines how historical conflicts and social identities influence interfaith dialogue among the Nigerian Christian and Muslim groups in Nigeria and the Nigerian UK diaspora.The study reveals that the memories of violent conflicts persist and actively shape contemporary interfaith dynamics. This approach provides deeper understanding and facilitates reconciliation by using the dialogical model, which emphasises individual narratives and lived experiences. Unlike traditional dialogues that often emphasise procedural methods and theoretical frameworks, this model acknowledges the profound psychological impact of past trauma and fosters mutual respect and empathy among conflicting parties. This integration of personal narratives with structured dialogue not only enhances interfaith interactions but also contributes significantly to the healing and reconciliation efforts.This thesis contributes to the broader discourse on interfaith dialogue by highlighting the need to integrate personal experiences and trauma-informed approaches into dialogue processes. It argues for a methodological shift recognising the complex interplay between individual trauma and social identities. It proposes practical and theoretical ways to improve interfaith dialogue and promote sustainable peace in migrant communities.

Urban tree cover can provide several ecological and public health benefits. Secondary datasets for Tampa, FL, including sociodemographic variables (e.g., race/ethnicity), health data, and interpolated values for features of tree cover (e.g., percent canopy and leaf area index) were analyzed using correlation and regression. Percent canopy cover and leaf area index were inversely correlated to respiratory and cardiovascular outcomes, yet only leaf area index displayed a significant association with respiratory conditions in the logistic regression model. Percent racial/ethnic minority residents at the block group level was significantly negatively correlated with median income and tree density. Leaf area index was also significantly lower in block groups with more African-American residents. The percentage of African Americans (p = 0.101) and Hispanics (p < 0.001) were positively associated with respiratory outcomes while population density (p < 0.001), percent canopy (p < 0.01), and leaf area index (p < 0.01) were negatively associated. In multivariate models, higher tree density, leaf area index, and median income were significantly negatively associated with respiratory cases. Block groups with a higher proportion of African Americans had a higher odds of displaying respiratory admissions above the median rate. Tree density and median income were also negatively associated with cardiovascular cases. Home ownership and tree condition were significantly positively associated with cardiovascular cases.

Spatial thinking has been well-described and characterized for many STEM fields, and there have been numerous studies that emphasize the importance of incorporating spatial opportunities early and often throughout curricula. However, there is still a gap in the research in implementing deliberate spatial training in curricula as well as the transfer of spatial thinking skills from academic to workforce settings. The goals of this dissertation are three-fold. Firstly, develop a survey to understand adults’ spatial reasoning, experience with spatial tasks, and confidence in spatial reasoning to determine how these metrics along with college major and career fields are related. Secondly, employ a spatially-rich geological activity to determine how the delivery method of pedagogical aides (e.g., physically vs virtually) affect performance on a topographical and geological activity and a geoscience spatial thinking instrument. Lastly, describe and characterize the challenges to and strategies for solving the spatial visualization items on this spatial instrument using eye-tracking data and retrospective interviews. This research highlights the value of instruction and collaboration in STEM and the geosciences.

Chlorophyll-a (chl-a) is considered as a primary indicator for water quality and foods for oyster growth in Apalachicola estuarine ecosystem. Assessment of chl-a concentration variation in response to river inflow is important for estuarine environmental research and management. In this study, remote sensing analysis has been conducted to evaluate the effects of river inflow on chlorophyll concentrations in Apalachicola Bay of Florida in the northeast Gulf of Mexico. A remote sensing model for chl-a was improved and applied to map spatial distributions of chl-a by using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m resolution imageries in high-flow and low-flow seasons in 2001 and 2008. Chl-a values approximately ranged from the minimum 6 μg/l to the maximum 29 μg/l in the study period. Maximum chl-a concentration in high-flow season was almost twice above that in low-flow season. The averaged mean and minimum chl-a level in the high-flow season were approximately 42 and 28 % higher than those in low-flow season, respectively. The remote sensing mapping of chl-a was able to show spatial variations of chl-a in the entire bay under different flow conditions, which indicated its advantage over the traditional field data sampling for monitoring water quality over a large area of estuary. The MODIS 250-m remote sensing regression model presented from this study can be used to support monitoring and assessment of the spatial chl-a distribution in the bay for environmental research and management in Apalachicola Bay.

Hong, X.; Huang, W.; Johnson, E.; Lou, S., and Wan, W., 2014. Effects of sea level rise on salinity intrusion in St. Marks River estuary, Florida, U.S.A.. Effects of sea level rise on salinity intrusion in St. Mark River estuary has been investigated by the application of a 3D hydrodynamic model. The estuary receives freshwater inputs from two upstream tributaries, Wakular River and St. Mark River. The model has been calibrated by using the observed data measured in the estuary. Under the sea level rise of 0.85m, numerical modeling under the flow for the 4-month period in 2000 indicate that, the sea level rise can cause substantial increase of salinity near the lower Wakulla River, with the increase of 9.2 ppt for surface salinity and 12.7 ppt for bottom salinity. At mid estuary, surface salinity increases by 5.6 ppt, and bottom salinity increases by 3.8 ppt. Because the existence of freshwater and brackish marshes through much of the Wakulla River, the substantial increase of salinity by sea level rise of 0.85 m may have significant impact on the ecosystem in Wakala River tributary.

The effects of sea level rise on salinity intrusion in St. Mark River estuary has been investigated by the application of a 3D hydrodynamic model. The estuary receives freshwater inputs from two upstream tributaries, Wakular River and St. Mark River. The model has been calibrated, by using the observed data measured in the estuary. Under the sea level rise of 0.85m, numerical modeling under the flow for the 4-month period in 2000 indicate that, the sea level rise can cause substantial increase of salinity near the lower Wakulla River, with the increase of 9.2 ppt for surface salinity and 12.7 ppt for bottom salinity. At mid estuary, surface salinity increases by 5.6 ppt, and bottom salinity increases by 3.8 ppt. Because the existence of freshwater and brackish marshes through much of the Wakulla River, the substantial increase of salinity by sea level rise of 0.85 m may have significant impact on the ecosystem in Wakala River tributary.

Spatial reasoning ability is a necessary skill for success in any of the science, technology, engineering, and mathematics (STEM) domains. Research suggests that spatial thinking ability and exposure to opportunities aimed at developing spatial reasoning skills through educational training could impact a student’s decision to select a STEM or non-STEM course of study or impact their decision to remain in STEM career path (Wai et al., 2009, Kell & Lubinski, 2013). Geology is one such field that may be impacted by spatial thinking skills. Students that have less spatial thinking ability could have a more difficult time learning geological concepts (Ishakawa & Kastens, 2005). However, spatial ability is malleable and can improve with intervention and training (Uttal et al., 2013). The heavy reliance on spatial ability to understand many geological concepts, like cartography and topography (Woods et al., 2016; Giorgis et al., 2017), makes researching innovative methods and technologies to train spatial skills a necessity in the geosciences.Several recent publications have utilized the augmented reality (AR) sandbox in the undergraduate classroom (Woods et al., 2017; Giorgis et al., 2017), and there has been some research suggesting that a student’s spatial thinking ability impacts their performance on topographic map assessments after exposure to AR sandbox (McNeal et al., 2019), but there has been no evidence to determine whether the AR sandbox can improve students’ spatial reasoning ability. This study aimed to determine the effectiveness of the AR sandbox for improving the spatial thinking of low scoring students. We also explored how students’ experiences with the spatial training activities impacted their self-reflections of their overall spatial thinking skills. Furthermore, we aimed to understand which activities they perceived to best support their spatial skill development to create an effective pedagogical intervention for undergraduate geoscience classrooms.