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Articles 31 - 60 of 2512
Full-Text Articles in Geography
Machine-Learning Landslide Susceptibility And Runout Modeling In The Nolichucky River Gorge After Hurricane Helene, Grace Braver
Machine-Learning Landslide Susceptibility And Runout Modeling In The Nolichucky River Gorge After Hurricane Helene, Grace Braver
Electronic Theses and Dissertations
Extreme rainfall from Hurricane Helene (September 2024) triggered widespread landslides across the southern Appalachian region, highlighting the need for rapid landslide susceptibility assessments that capture both landslide initiation and downstream runout. Traditional susceptibility models often focus solely on initiation zones, limiting their ability to identify which slopes will generate destructive landslides or where material will travel. This study addresses that gap by (1) integrating Geographic Information System (GIS)-based machine learning susceptibility modeling using ArcGIS Pro: Maximum Entropy (MaxEnt) and Random Forest-Based and Boosted Classification and Regression (FBBC) and (2) the U.S. Geological Survey (USGS) Grfin (Growth, Flow, and Inundation) runout …
Public Pool Usage As Adaptation Against Urban Heat, Stefan Borsky, Eric Fesselmeyer
Public Pool Usage As Adaptation Against Urban Heat, Stefan Borsky, Eric Fesselmeyer
Research Collection College of Integrative Studies
This paper examines the relationship between urban heat and outdoor public pool usage. Using attendance data from all 53 outdoor public pools in New York City, we analyze nonlinear effects of heat on pool usage across socioeconomic contexts. Pool attendance rises sharply with heat, especially in low-income neighborhoods where alternative coping options are likely limited. We also find that public pools reduce heat-related emergency medical service calls. Our findings highlight the need for equitable investment in blue infrastructure to enhance urban climate resilience and demonstrate how this type of adaptive infrastructure can play a critical role in managing urban heat.
Passive Microwave Remote Sensing Of Flash Drought Impacts On Vegetation, Quinton R. Deppert
Passive Microwave Remote Sensing Of Flash Drought Impacts On Vegetation, Quinton R. Deppert
School of Natural Resources: Dissertations, Theses, and Student Research
In 2002, Dr. Mark Svoboda characterized a new form of drought known as flash drought. Flash drought was defined as a rapid decline in vegetation health caused by severe heat and drought. In recent years, attempts to quantify the impacts of flash drought via precipitation, soil moisture, evapotranspiration, and temperature indicators have proliferated. What has rarely been quantified is what the rapid decline in vegetation health amid flash drought looks like through remote sensing. This is because vegetation health indices like the Normalized Difference Vegetation Index (NDVI) are derived from the visible and infrared regions of the electromagnetic spectrum and …
Sustainability, Culture, And Higher Education: An Autoethnographic Sustainability Comparison Of The Sustainability Initiatives At The University Of Salzburg And Bowling Green State University, Madison Alt
Honors Projects
Human activity is already triggering damaging environmental tipping points (Lenton, 2020), emphasizing the need for sustainability in all aspects of development. Institutes of Higher Education (IHEs) have the power and responsibility to contribute to a more sustainable world (Parr et al., 2022). Bowling Green State University (BGSU) in Ohio, United States, and the Paris Lodron University of Salzburg (PLUS) in Salzburg, Austria are two IHEs with multifaceted sustainability programs. While living and studying at BGSU and PLUS, I used autoethnography, a personal narrative approach, combined with public sustainability information to compare the sustainability initiatives at each university, and determine what …
Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert
Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models, Bilge Bingül, Emrah Pekkan, Resul Çömert
International Journal of Speleology
This study investigates the relationship between sinkhole occurrence and distance to drainage in the Sivrihisar region (Central Turkey) and evaluates the suitability of different regression approaches for modeling clustered count data in karst terrains. A comprehensive inventory of 104 sinkholes developed within the Neogene lacustrine limestones of the Akpınar Formation was compiled using official records, remote sensing analyses, and detailed field surveys. Sinkhole occurrences were analyzed relative to a drainage network derived from a high-resolution Digital Surface Model and grouped by proximity to drainage lines. Linear Regression (LM), Poisson Regression (PR), and Negative Binomial Regression (NBR) models were comparatively applied …
Complex Systems Mapping Of Fiscal Growth Dynamics At Strategic Maritime Chokepoints Using Time-Series Slopes, Rahul Balamurugan, Preethi Nanjundan, Avichal Sharma
Complex Systems Mapping Of Fiscal Growth Dynamics At Strategic Maritime Chokepoints Using Time-Series Slopes, Rahul Balamurugan, Preethi Nanjundan, Avichal Sharma
Northeast Journal of Complex Systems (NEJCS)
This study examines how maritime and trading states allocate public resources between defence, health, and economic growth around three strategic chokepoints the Strait of Malacca, the Strait of Hormuz, and the Suez Canal. The analysis extends the classic “guns versus butter” framing by treating defence and health spending as co-evolving components of an interconnected fiscal-growth system. Using World Development Indicators data (1999-2024), trend slopes are estimated for military spending (% of GDP), healthcare spending (% of GDP), and GDP growth (annual %). Two derived indicators are computed, a defence-to-health slope ratio (military slope/health slope) and a fiscal-balance proxy (health slope …
Monitoring Koyna Dam Displacements Using Persistent Scatterer Interferometry, Sara Zouriq, Gehan Hamdy, Amr Fawzy, Rejoice Thomas, Hesham El-Askary, Eehab Khalil, Mohamed Elsayad, Tarik El-Salawaky
Monitoring Koyna Dam Displacements Using Persistent Scatterer Interferometry, Sara Zouriq, Gehan Hamdy, Amr Fawzy, Rejoice Thomas, Hesham El-Askary, Eehab Khalil, Mohamed Elsayad, Tarik El-Salawaky
Mathematics, Physics, and Computer Science Faculty Articles and Research
Monitoring dam stability is critical to ensure structural safety and operational reliability. This study integrates Persistent Scatterer Interferometry (PSI) based on Sentinel-1 SAR imagery (2020–2023) with Finite Element Method (FEM) simulations to assess the behavior of the Koyna Dam in India. PSI detected crest displacements between −1.0 and −1.8 mm yr−1, while FEM simulations predicted a maximum vertical displacement of approximately −3.2 mm at the crest. Although these results represent different quantities (time-averaged displacement rates versus peak static displacement), both approaches indicate millimeter-scale deformation and a consistent pattern of settlement at the dam crest, supporting the interpretation of hydrologically driven …
High-Resolution Monitoring Of Intra-Seasonal Agricultural Drought Using Sentinel-2 And Machine Learning Across Bimodal Growing Seasons In Kenya, S. Mohammad Mirmazloumi, Harison Kipkulei, Rose Waswa, Tobias Landmann, Tom Dienya, Maximilian Schwarz, Fabrizio Ramoino, Clément Albergel, Gohar Ghazaryan
High-Resolution Monitoring Of Intra-Seasonal Agricultural Drought Using Sentinel-2 And Machine Learning Across Bimodal Growing Seasons In Kenya, S. Mohammad Mirmazloumi, Harison Kipkulei, Rose Waswa, Tobias Landmann, Tom Dienya, Maximilian Schwarz, Fabrizio Ramoino, Clément Albergel, Gohar Ghazaryan
All Peer-Reviewed Publications
Drought presents significant challenges to agriculture, threatening food security and livelihoods, across many regions. In Kenya, recurrent droughts across diverse agro-ecological zones emphasize the urgent need for reliable and scalable drought assessment methods. Although drought assessment with various datasets has been carried out for this region, many of them often use course or moderate resolution data. This study uses high-resolution Sentinel-2 observations and machine learning to monitor intra-seasonal crop conditions and assess drought impacts across bimodal growing seasons. Using pixel-based supervised random forest models trained with multiple vegetation indices as input, we classify croplands into drought-affected and unaffected areas. The …
Changes In Land, Ocean, Atmospheric Parameters Associated With The 2025 Myanmar (Mw 7.7) Earthquake, Feng Jing, Akshansa Chauhan, Ashwani Raju, Ramesh P. Singh
Changes In Land, Ocean, Atmospheric Parameters Associated With The 2025 Myanmar (Mw 7.7) Earthquake, Feng Jing, Akshansa Chauhan, Ashwani Raju, Ramesh P. Singh
Mathematics, Physics, and Computer Science Faculty Articles and Research
Multiple parameters associated with the land, atmosphere, and ocean were analyzed to study short-term and immediate pre-earthquake changes associated with the 28 March 2025 Myanmar earthquake (Mw 7.7). Anomalous clear-sky outgoing longwave radiation (ClrOLR) and trace gases (CH₄, CO, and O₃) were detected within two months prior to the mainshock. Vertical changes at different pressure levels suggest a possible underground source. High-temporal-resolution observations of the infrared brightness temperature and surface air pressure revealed short-lived fluctuations shortly before the earthquake, which may reflect localized stress adjustments and surface latent heat flux release during the final stage of earthquake preparation. In the …
A Review Of Satellite-Derived Terrestrial Evapotranspiration: Theories, Methods And Products, Yunjun Yao, Jiquan Chen, Joshua B. Fisher, Changliang Shao, Yuanbo Liu
A Review Of Satellite-Derived Terrestrial Evapotranspiration: Theories, Methods And Products, Yunjun Yao, Jiquan Chen, Joshua B. Fisher, Changliang Shao, Yuanbo Liu
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Accurately estimating terrestrial evapotranspiration (ET), the second-largest hydrologic flux in the terrestrial water cycle, is vital for understanding global water and carbon exchanges. It is difficult to measure and estimate terrestrial ET at regional and global scales. Satellites have provided us an effective tool to estimate regional and global terrestrial ET in recent decades. In this article, we provide a comprehensive review of the basic theoretical foundations, methods and products of satellite-derived terrestrial ET. The basic theoretical foundations for estimating terrestrial ET are the Monin–Obukhov similarity theory (MOST) and other budding theories (e.g., Maximum entropy production theory, and generalized Hamilton …
Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus
Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus
Journal of Humanities and Social Sciences
This article critically explores how Bongo Fleva’s lyrics engage with environmental themes; and the interrelationship between nature and culture in the context of the Anthropocene. The data were purposively sampled from YouTube via content analysis, from which 50 Bongo Fleva songs were listened to, and only 10 environmentally-themed songs were analysed. Then, the selected songs were subjected to transcription (from oral to written form), translation (from Kiswahili into English), and close reading and textual analysis. The close reading of the selected songs focused on the employed aesthetic and rhetorical strategies, such as anthropomorphism, symbolism, antithesis, apocalyptic tones, solastalgia, rhetorical questions, …
Ecosystem-Based Flood Disaster Risk Reduction In The Little Ruaha River Basin, In The Southern Highlands Of Tanzania, Mawazo Ghambi, Tiemo Romward Haule
Ecosystem-Based Flood Disaster Risk Reduction In The Little Ruaha River Basin, In The Southern Highlands Of Tanzania, Mawazo Ghambi, Tiemo Romward Haule
Journal of Humanities and Social Sciences
Ecosystem-based approach that integrates floods and environmental risk management is believed to reduce flood disaster risk while providing socio-economic and environmental benefits to floodplain occupants. This study examined the socio-economic and environmental benefits of the ecosystem-based approach in managing flood disaster risk in the Little Ruaha River Basin in the southern highlands of Tanzania. The study involved 157 participants and employed the mixed research design to collect quantitative and qualitative data. Semi-structured interviews, in-depth interviews, direct field observation and Focus Group Discussions were used to collect primary data, whereas documentary review was used to collect secondary data. Findings revealed that …
Resilience Among Smallholder Irish Potato Farmers To The Impacts Of Climate Variability In Wanging’Ombe District, Tanzania, Timotheo Bilary Ngalaga, Digna Wolfram Mlengule, Jackson Raymond Sawe
Resilience Among Smallholder Irish Potato Farmers To The Impacts Of Climate Variability In Wanging’Ombe District, Tanzania, Timotheo Bilary Ngalaga, Digna Wolfram Mlengule, Jackson Raymond Sawe
Journal of Humanities and Social Sciences
This paper examines smallholder farmers’ adaptation strategies to climate variability, and their resilience in enhancing their capacity to adopt. The data was collected from 98 heads of households using both quantitative and qualitative approaches. The methods of data collection included household surveys, focus group discussions (FGDs), in-depth interviews, and document review. The quantitative data were analysed using the IBM SPSS (Version 23), while the qualitative data were analysed using thematic analysis. The findings indicate that 69.4% of respondents reported a decrease in rainfall, while 89.8% reported an increase and fluctuations in temperature over the past 29 years. Moreover, the findings …
Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya
Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya
Journal of Humanities and Social Sciences
This article examines the perceived effect of climate change on cereal crop production and the responses of various stakeholders aimed at enhancing the resilience of smallholder farmers in semi-arid areas of central Tanzania. A total of 366 household heads, 28 participants in focus group discussions (FGDs), and 8 key informants from Bahi and Kongwa districts in Dodoma, Tanzania, were involved in this study. Both quantitative and qualitative data were gathered through a structured interview schedule, FGDs, in-depth interviews, and documentary reviews. Descriptive statistics and content analysis were used to analyse quantitative and qualitative data, respectively. The findings indicate that smallholder …
Long-Term Variability Of Air Quality And Greenhouse Gas Emissions From Rice Crop Burning In Punjab During 2012–2020, Harsimranjit Kaur Romana, Dericks Praise Shukla, Ramesh P. Singh
Long-Term Variability Of Air Quality And Greenhouse Gas Emissions From Rice Crop Burning In Punjab During 2012–2020, Harsimranjit Kaur Romana, Dericks Praise Shukla, Ramesh P. Singh
Mathematics, Physics, and Computer Science Faculty Articles and Research
Punjab, India's primary rice and wheat production hub, has witnessed rapid expansion of paddy cultivation over the past two decades, driven by minimum support price incentives, changes in government policies, alignment of sowing with the monsoon season and the adoption of high-yielding varieties. This transition has intensified groundwater extraction and shortened the fallow period between rabi and kharif crop seasons, reducing the window between rice harvesting and wheat sowing, leading to widespread open-field burning of rice residue and recurrent post-monsoon air-quality deterioration across the Indo-Gangetic Plain. Despite numerous short-term or single-pollutant assessments, a spatially resolved, multi-pollutant and multi-decadal evaluation linking …
Super-Resolution Remote Sensing Datasets For Application To Caral–Supe Archeological Sites Employing Sar And Dems, Jungrack Kim, Ramesh P. Singh
Super-Resolution Remote Sensing Datasets For Application To Caral–Supe Archeological Sites Employing Sar And Dems, Jungrack Kim, Ramesh P. Singh
Mathematics, Physics, and Computer Science Faculty Articles and Research
Publicly accessible spaceborne remote sensing datasets often lack the spatial resolution required to reliably distinguish archeological features from their surrounding geomorphological contexts. In this study, we assess the potential of super-resolution (SR) products derived from multiple public-domain remote sensing datasets for a systematic archeological survey in the Caral–Supe region. We focus on Synthetic Aperture Radar (SAR) and topographic datasets—including Sentinel-1, Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR), and Digital Elevation Models (DEMs)—because of their capacity to detect subtle surface expressions and shallow subsurface structures obscured by vegetation or sediment cover. Using state-of-the-art deep learning algorithms, …
Automated Machine Learning For High-Resolution Daily And Hourly Methane Emission Mapping For Rice Paddies Over South Korea: Integrating Modis, Era5-Land, And Soil Data, Jiah Jang, Seung Hee Kim, Menas Kafatos, Jaeil Cho, Gayoung Yoo, Sujong Jeong, Yangwon Lee
Automated Machine Learning For High-Resolution Daily And Hourly Methane Emission Mapping For Rice Paddies Over South Korea: Integrating Modis, Era5-Land, And Soil Data, Jiah Jang, Seung Hee Kim, Menas Kafatos, Jaeil Cho, Gayoung Yoo, Sujong Jeong, Yangwon Lee
Institute for ECHO Articles and Research
Agriculture is a major global source of methane (CH4), and accurate emission estimates are essential for refining national greenhouse gas inventories and supporting climate-resilient policies. This study develops a high-resolution estimation framework for CH4 emissions from Korean rice paddies by integrating multi-source datasets, including Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis Version 5 (ERA5)-Land meteorological variables, and Harmonized World Soil Database (HWSD) soil properties. Using CH4 flux observations from four global rice ecosystems (Italy, Japan, South Korea, and USA), we constructed parallel daily and hourly machine learning models using an automated machine …
College Of Natural Sciences 2025 Year-End Publication, College Of Natural Sciences
College Of Natural Sciences 2025 Year-End Publication, College Of Natural Sciences
College of Natural Sciences Newsletters and Reports
Page 2 Dean's Message
Page 3 Department Highlights
Page 4 One Day for State
Page 5 Ice cores reveal volcanic eruptions in 13th century
Page 5 How do our cells interpret stress
Page 6-7 Faculty Excellence
Page 8 New chemical biology consortium will accelerate cancer research
Page 9 SDSU to combat crop disease, biofilms in new NSF-back project
Page 9 Science as Art Competition
Page 10-11 Student Excellence
Page 12 SDSU researcher developing natural alternative to synthetic dyes
Page 12 Browning Retired
Page 13 Quantum technologies through NSF-backed project
Page 13 NASA Funds CNS Development of Model
Page 14 GGS …
A Probabilistic Deep Learning Framework For Retrieving Chlorophyll-A From Hyperspectral Imagery: Integrating Channel Attention And Mixture Density Networks, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Junde Chen, Hesham Morgan, Michael J. Garay, Olga V. Kalashnikova, Shahryar Fazli, Charles Ichoku, Hesham El-Askary
A Probabilistic Deep Learning Framework For Retrieving Chlorophyll-A From Hyperspectral Imagery: Integrating Channel Attention And Mixture Density Networks, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Junde Chen, Hesham Morgan, Michael J. Garay, Olga V. Kalashnikova, Shahryar Fazli, Charles Ichoku, Hesham El-Askary
Mathematics, Physics, and Computer Science Faculty Articles and Research
Accurate monitoring of Chlorophyll-a (Chla) is critical for assessing aquatic ecosystem health, yet ecological complexity often leads to ambiguous spectral signatures in satellite data. Traditional deterministic models assume a one-to-one mapping between spectra and pigments, often failing to capture these high-dimensional analytical challenges. In this study, we propose a novel deep learning architecture, the Channel Attention-Mixture Density Network (CA-MDN), to retrieve Chla from the National Aeronautics and Space Administration (NASA) Earth Surface Mineral Dust Source Investigation (EMIT) hyperspectral mission. The CA-MDN integrates an attention mechanism to dynamically select ecologically relevant spectral bands and employs a probabilistic output layer to quantify …
Satellites, Urban Heat, And Environmental Justice: Community As The Bridge Between Analysis And Action, Joshua B. Fisher, Ambar Rivera, Ava Cison, Ashley Agatep, Kainani Tacazon, Sophia Spiegleman, Alison Mckenery, Rio E. Fisher, Reginald Archer, Jason A. Douglas
Satellites, Urban Heat, And Environmental Justice: Community As The Bridge Between Analysis And Action, Joshua B. Fisher, Ambar Rivera, Ava Cison, Ashley Agatep, Kainani Tacazon, Sophia Spiegleman, Alison Mckenery, Rio E. Fisher, Reginald Archer, Jason A. Douglas
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Heat waves are increasing in frequency, intensity, magnitude, and duration, causing a disproportionate impact on marginalized communities exposed to urban heat islands. Newly emerging spaceborne thermal sensing instruments, such as ECOSTRESS and Hydrosat, now have the capabilities to measure urban surface temperatures accurately at the block level (< 100 m) and with enough frequency to capture transient heat waves (daily to subweekly). Such data are critical for monitoring and informing policy and mitigation efforts, such as resurfacing, green space, cooling stations, and medical mobilization. These serve to advance environmental justice and reduce health risks—and deaths—among the most vulnerable: minority, low-income, elderly, those with physical- and mental-health preconditions, unhoused, children, and outdoor workers. While scientists have increasingly used satellite data to quantify urban heat islands and risks to communities, there remains a significant gap in action resulting from such analyses—a figurative and literal “valley of death.” Reviewing over 500 scientific publications, we identify a critical lack of engagement with the communities being analyzed (10.9%; n = 58); yet, community engagement is key to bridging such analysis with subsequent action. Here, we demonstrate how participatory community engagement directly with data and analysis leads to increased policy changes and mitigation efforts. Our framework has immediate implications for how scientists may augment their work and thought processes to achieve …
The World's Largest Saddle Dam At Risk: Multisensor Geohazard Analysis And Downstream Impacts, Hesham El-Askary, Hesham Morgan, Surendra Maharjan, Ali Elgendy, Wenzhao Li, Rejoice Thomas, Austin Madson, Cyril Rakovski
The World's Largest Saddle Dam At Risk: Multisensor Geohazard Analysis And Downstream Impacts, Hesham El-Askary, Hesham Morgan, Surendra Maharjan, Ali Elgendy, Wenzhao Li, Rejoice Thomas, Austin Madson, Cyril Rakovski
Mathematics, Physics, and Computer Science Faculty Articles and Research
The Grand Ethiopian Renaissance Dam (GERD) Saddle Dam, which holds approximately 89% of the main reservoir's live storage, is one of the largest and most critical auxiliary dams globally; its construction on Ethiopia's Blue Nile has consequently raised significant regional and international concerns regarding potential environmental impacts and geohazard risks. This study presents a comprehensive risk assessment of the GERD Saddle Dam by integrating high-resolution satellite data (GRACE, Sentinel-1, Sentinel-2, WorldView-3), hydrological modeling (SWAT), Persistent Scatterer Interferometry (PSI), geospatial analysis, and advanced statistical techniques. The results highlight critical structural vulnerabilities, including groundwater infiltration estimated at approximately 41 ± 6.2 billion …
Deep Learning Style Transfer For Enhanced Smoke Plume Visibility: A Standardized False Color Composite (Sfcc) In Gems Satellite Imagery, Yemin Jeong, Seung Hee Kim, Menas Kafatos, Jeong-Ah Yu, Kyoung-Hee Sung, Seung-Yeon Kim, Goo Kim, Jae-Jin Kim, Yangwon Lee
Deep Learning Style Transfer For Enhanced Smoke Plume Visibility: A Standardized False Color Composite (Sfcc) In Gems Satellite Imagery, Yemin Jeong, Seung Hee Kim, Menas Kafatos, Jeong-Ah Yu, Kyoung-Hee Sung, Seung-Yeon Kim, Goo Kim, Jae-Jin Kim, Yangwon Lee
Institute for ECHO Articles and Research
Wildfire smoke visualization using geostationary satellite imagery is essential for real-time monitoring and atmospheric analysis; however, inconsistencies in color tone across Geostationary Environment Monitoring Spectrometer (GEMS) images hinder reliable interpretation and model training. This study proposes a Standardized False Color Composite (SFCC) framework based on deep learning style transfer to enhance the visual consistency and interpretability of wildfire smoke scenes. Four tone-standardization methods were compared: the statistical Empirical Cumulative Distribution Function (ECDF) correction and three neural approaches—ReHistoGAN, StyTr2, and Style Injection Diffusion Model (SI-DM). Each model was evaluated visually and quantitatively using six metrics (SSIM, LPIPS, FID, histogram similarity, ArtFID, …
Typeface: Machine-Viewing Gentrification On Storefront Imagery In Bedford-Stuyvesant, Brooklyn, Alexander Mcquilkin
Typeface: Machine-Viewing Gentrification On Storefront Imagery In Bedford-Stuyvesant, Brooklyn, Alexander Mcquilkin
Dissertations, Theses, and Capstone Projects
Gentrification—broadly, the replacement of a less powerful group by a more powerful one in an urban context—is oft-discussed in the popular press, but its definition is much-debated in the urban planning literature. Furthermore, academic treatments of displacement understandably focus on measurable yet fairly abstract indicators like changes in rent or income, whereas neighborhood change is often registered by residents on the ground using visual, but difficult-to-quantify markers like retail turnover. This project uses image recognition technology on a set of storefront photos to index the visual streetscape of a neighborhood, as well as to track changes to that portrait over …
Land Use And Sovereignty Along The Catawba River, Thomas C. Brugh, Lucile C. Rencher
Land Use And Sovereignty Along The Catawba River, Thomas C. Brugh, Lucile C. Rencher
Student Scholarship
This document-based case study explains how land-use change along the Catawba River Corridor (Lancaster and York Counties, South Carolina) has been produced through the interaction of property rights (dominium) and rule-setting authority (imperium), showing why sovereignty continues to shape development even after land disputes appear “settled.” Through analyzing legal records (Treaty of Nation Ford, the 1959 Catawba Division of Assets Act, the 1986 Supreme Court timing decision, and the 1993 Settlement Act), planning documents, parcel records, and field observations, we trace how shifting jurisdiction and title certainty structured what kinds of land uses were possible and when. We argue that …
A Robust Deep Learning Ensemble Framework For Waterbody Detection Using High-Resolution X-Band Sar Under Data-Constrained Conditions, Soyeon Choi, Seung Hee Kim, Son V. Nghiem, Menas Kafatos, Minha Choi, Jinsoo Kim, Yangwon Lee
A Robust Deep Learning Ensemble Framework For Waterbody Detection Using High-Resolution X-Band Sar Under Data-Constrained Conditions, Soyeon Choi, Seung Hee Kim, Son V. Nghiem, Menas Kafatos, Minha Choi, Jinsoo Kim, Yangwon Lee
Institute for ECHO Articles and Research
Accurate delineation of inland waterbodies is critical for applications such as hydrological monitoring, disaster response preparedness and response, and environmental management. While optical satellite imagery is hindered by cloud cover or low-light conditions, Synthetic Aperture Radar (SAR) provides consistent surface observations regardless of weather or illumination. This study introduces a deep learning-based ensemble framework for precise inland waterbody detection using high-resolution X-band Capella SAR imagery. To improve the discrimination of water from spectrally similar non-water surfaces (e.g., roads and urban structures), an 8-channel input configuration was developed by incorporating auxiliary geospatial features such as height above nearest drainage (HAND), slope, …
High Spatiotemporal Resolution Monitoring Of Crop Water Stress Across The Contiguous United States Using Harmonized Landsat And Sentinel-2 Data, Na Chen, Yanlei Feng, Na Wang, Jevan Yu, Mohammad Reza Alizadeh, Yifeng Cui, Ning Ye, Wenzhe Jiao, Joshua B. Fisher, César Terrer
High Spatiotemporal Resolution Monitoring Of Crop Water Stress Across The Contiguous United States Using Harmonized Landsat And Sentinel-2 Data, Na Chen, Yanlei Feng, Na Wang, Jevan Yu, Mohammad Reza Alizadeh, Yifeng Cui, Ning Ye, Wenzhe Jiao, Joshua B. Fisher, César Terrer
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Accurate and timely monitoring of crop water stress is essential for efficient agricultural water management, ultimately maintaining and improving crop productivity. While Landsat has been used for this purpose, its temporal resolution hampers timely detection of crop water stress. The recently released Harmonized Landsat and Sentinel-2 Version 2.0 dataset, which enables a higher-frequency time series of satellite observations (2–3 days, 30 m), offers a promising solution to this challenge. However, its potential for crop stress monitoring remained unexplored. In this study, we utilized 923 HLS satellite tiles to assess crop water stress across the contiguous United States (CONUS). Crop water …
A Visualization-Supported, Hierarchical, Action-Learning Model For Driving Behavior In A V2x Environment, Xuantong Wang, Jing Li, Jecca Bowen
A Visualization-Supported, Hierarchical, Action-Learning Model For Driving Behavior In A V2x Environment, Xuantong Wang, Jing Li, Jecca Bowen
Geography and the Environment: Faculty Scholarship
Understanding human driving decisions is crucial for intelligent transportation research. Most existing studies focus on individual vehicles in limited contexts, which restricts broader applicability of results. Leveraging Vehicle-to-Everything (V2X) infrastructure, this study introduces a machine learning framework to model driving actions and detect outliers across diverse environments. This approach features a semantically enabled clustering method that groups similar driving behaviors based on speed and actions. It also adds a time-series learning model to identify typical driving behaviors across various contexts, thereby enabling detection of abnormal driving actions. A suite of visual tools has been developed to help interpret driving patterns, …
Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei
Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei
Mechanical & Aerospace Engineering Faculty Publications
In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …
Below The Rows, Beyond The Roots: An Art Exhibition Depicting Agriculture Across The Globe, Maggie Enoch
Below The Rows, Beyond The Roots: An Art Exhibition Depicting Agriculture Across The Globe, Maggie Enoch
Honors Theses and Capstones
In Below the Rows, Beyond the Roots, artist Maggie Enoch creates multimedia works inspired by her exposure to diverse agricultural systems and perspectives while studying geography and sustainable agriculture/food systems around the world. By integrating complex histories with the contemporary realities of farming, Maggie paints vivid pictures of the power of food in this five-piece exhibition.
Submesoscale Dynamics Of Phytoplankton And Carbon Export Revealed By High-Resolution Airborne And Satellite Remote Sensing Of Currents And Ocean Color, Sarah E. Lang
Open Access Dissertations
Satellites and airborne sensors reveal submesoscale (1 - 10 km) variability in ocean color in the form of filaments, eddies, and patches. The variability in ocean color is closely tied to the physical dynamics that restructure phytoplankton distributions and drive active biological responses like changes in primary productivity and community structure. As the base of the marine food web and a key component of the biological carbon pump, phytoplankton are crucial to the overall health of marine ecosystems and to the ocean's role in climate. This dissertation focuses on the use of airborne and satellite remote sensing to study the …