DePaul University
Western Michigan University
Minnesota State University, Mankato
Indonesian Agency for Meteorology Climatology and Geophysics, Jakarta
University of Arkansas, Fayetteville
Contrasting Coastal Dune Environments In Chile,
2026
Embry-Riddle Aeronautical University
Contrasting Coastal Dune Environments In Chile, Aurora Christianson
Discovery Day - Daytona Beach
Emerging coastalization and urbanization threats to the prehistoric Concón Dunes and Humedal de Mantagua coastal area of Chile is being investigated by researchers via uncrewed aircraft systems (UAS) in "Contrasting Coastal Dune Environments in Chile." Four UAS were utilized: Anzu Raptor T, DJI Mavic 3E, DJI Mavic 3M, and DJI Air 3 to collect various images of the coastal dunes. Multispectral and RGB cameras gather images by photogrammetry to create orthomosaics and monitor vegetation indexes in Pix4Dmapper. Thermal cameras provided images in rainbow, white hot infrared, and black hot infrared schemes to monitor wildlife and vegetation. The normalized difference vegetation …
Automated Classification, Measurement, And Semantic Segmentation Of Open-Web Joists From Point Cloud Data,
2026
Rowan University
Automated Classification, Measurement, And Semantic Segmentation Of Open-Web Joists From Point Cloud Data, Justin Raymond Dworacek
Theses and Dissertations
This thesis presents a BIM-oriented methodology for the automated classification, measurement, and segmentation of structural trusses from point cloud data. A real truss point cloud and a complementary synthetic dataset derived from CADBIM Revit families were used to develop and evaluate the workflow. Classification was performed using a rule-based Python algorithm based on principal component analysis, side-view feature extraction, and family-specific geometric decision logic, while a separate family-aware script was used to extract key truss dimensions. Semantic segmentation was evaluated using a PointTransformerV3 model to separate truss and non-truss points in mixed point cloud scenes. The results demonstrated strong performance …
Cramer’S V-Based Driver Screening For Land-Use Change Prediction In A Flood-Prone Coastal Lowland Of Demak Regency, Indonesia (2002-2035),
2026
Universitas Gadjah Mada, Indonesia
Cramer’S V-Based Driver Screening For Land-Use Change Prediction In A Flood-Prone Coastal Lowland Of Demak Regency, Indonesia (2002-2035), Mellinia Regina Heni Prastiwi, Sigit Heru Murti Budi Santosa, Sudaryatno Sudaryatno, Daud Richard Malusu
Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi
Land use in the floodplain of Demak Regency has changed rapidly under pressure from urbanization and economic activity, and this change is hypothesized to contribute to increased flood risk, a concern reinforced by the extreme flood disaster of February-March 2024, although establishing a direct causal link between the observed land-use trajectory and the magnitude of that specific flood event would require dedicated hydrological modeling beyond the scope of this study. This study proposes examining the spatio-temporal dynamics of land use from 2002 to 2024 and forecast the conditions in 2035 utilizing a Land Change Model (LCM) framework combining Markov chains …
Global Performance Of Remote Sensing-Based And Reanalysis-Driven Models To Estimate Open Water Evaporation,
2026
Federal University of Rio Grande do Sul
Global Performance Of Remote Sensing-Based And Reanalysis-Driven Models To Estimate Open Water Evaporation, Júlia Brusso Rossi, Ayan Santos Fleischmann, Leonardo Laipelt, Bruno Comini De Andrade, Joshua B. Fisher, Justin L. Huntington, Christopher Pearson, R. Iestyn Woolway, Roseilson Vale, Júlio Tota, Gabriel B. Senay, Huilin Gao, Anderson Ruhoff
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Evaporation plays an essential role in the water cycle, influencing local and regional climates while directly impacting water availability in lakes. However, directly measuring evaporation over water bodies remains challenging due to the high costs of installing and maintaining the required in situ instrumentation. Although several remote sensing algorithms have been providing evaporation estimates, the lack of a global validation hinders our understanding of their relative uncertainties and performances across different regions. Here, we analyze the performance of a suite of models that leverage satellite data and meteorological reanalysis to estimate evaporation over lakes worldwide. We compare 3 remote sensing‐based …
Coastal Vulnerability Index Mapping Using Remote Sensing And Gis Techniques: A Comparative Study Of Oaxaca (Mexico) And Bali (Indonesia),
2026
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, Indonesia
Coastal Vulnerability Index Mapping Using Remote Sensing And Gis Techniques: A Comparative Study Of Oaxaca (Mexico) And Bali (Indonesia), Siti Aisyah, Mangapul Parlindungan Tambunan
Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)
This study aims to conduct a comparative analysis of two journal articles that assess coastal vulnerability using the Coastal Vulnerability Index (CVI), focusing on the State of Oaxaca in Mexico and the Province of Bali in Indonesia. The comparison covers the research context, data inputs, methodological frameworks, findings, and conclusions, while also highlighting the respective strengths and limitations of each study. Both regions applied CVI methodologies to evaluate areas at risk from sea-level rise, utilizing remote sensing data and Geographic Information System (GIS) tools at a regional scale. The outcomes of this research emphasize key parameters that significantly affect coastal …
Crustal Structure Of The Vøring Plateau And Vøring Spur From Joint Refraction And Reflection Travel-Time Tomography,
2026
University of Nebraska-Lincoln
Crustal Structure Of The Vøring Plateau And Vøring Spur From Joint Refraction And Reflection Travel-Time Tomography, Anika Nawar Mayeesha
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
Crustal architecture of the Vøring Plateau and Vøring Spur in the mid-Norwegian continental margin remains debated because the geophysical data in the area do not uniquely constrain whether the crust is continental, oceanic, or transitional. This study reanalyzes wide-angle ocean-bottom seismometer data from Profile 11-03 across the Vøring passive continental margin using joint travel-time tomography of crustal refractions and Moho reflections. A total of 6,760 first-arrival picks and 542 PmP picks from sixteen instruments were inverted for P-wave velocity and reflector depth. Three starting models were inverted independently to test sensitivity to the initial crustal configuration. The first two used …
Evapotranspiration Everywhere, All The Time: Towards A Unified View From Earth Observation,
2026
Chapman University
Evapotranspiration Everywhere, All The Time: Towards A Unified View From Earth Observation, Joshua B. Fisher, Martha C. Anderson, Diego G. Miralles, Kanishka Mallick, Paul C. Stoy, Youngryel Ryu, Wim G. M. Bastiaanssen
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
Scientists want to know everything, everywhere, and all the time. This is particularly true in Earth science, where we seek to understand processes that span from the molecular to the planetary scale in how the world works, how it affects us, and how we impact it—especially the water cycle. Evapotranspiration (ET) was the last component to be measured in closing the water cycle: for decades, closing the water budget meant adding up all the measurable components, then inferring ET as the residual. Early measurements relied on water loss from pans and weighing lysimeters, followed by sensors inserted into plants to …
Machine-Learning Landslide Susceptibility And Runout Modeling In The Nolichucky River Gorge After Hurricane Helene,
2026
East Tennessee State University
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 …
Increasing Accuracy Of Mapping Local Climatic Zones Using Building Height And Spectral Unmixing,
2026
Western Michigan University
Increasing Accuracy Of Mapping Local Climatic Zones Using Building Height And Spectral Unmixing, Ian Douglas Stauffer
Masters Theses
Local climatic zone (LCZ) classifications are traditionally done using reflectance, population data, and often climatic data. The goal of this research is to utilize Google’s new “Open Buildings Temporal v1” building data set as well as “spectral unmixing”. With the objective of testing, assessing, and implementing this data set into the workflow of LCZ mapping. After testing the quality of the data against a validated LiDAR data set from the same year as a given “Open Buildings Temporal v1” band, I implemented it into the Random Forest machine learning process. Secondly, I justified the use of spectral unmixing as a …
Passive Microwave Remote Sensing Of Flash Drought Impacts On Vegetation,
2026
University of Nebraska-Lincoln
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 …
Applications Of Suas Thermal Imaging And Lidar At Letort Spring Garden Preserve: An Independent Study,
2026
Harrisburg University of Science and Technology
Applications Of Suas Thermal Imaging And Lidar At Letort Spring Garden Preserve: An Independent Study, Kelsey Wardell
Harrisburg University Other Works
No abstract provided.
Drainage Proximity And Sinkhole Occurrence In Sivrihisar (Central Turkey): A Comparative Analysis Of Linear, Poisson, And Negative Binomial Regression Models,
2026
Eskişehir Technical University, Department of Remote Sensing and Geographical Information Systems, Eskişehir, Türkiye
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 …
Monitoring Koyna Dam Displacements Using Persistent Scatterer Interferometry,
2026
Benha University
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 …
Changes In Land, Ocean, Atmospheric Parameters Associated With The 2025 Myanmar (Mw 7.7) Earthquake,
2026
China Earthquake Administration
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,
2026
Beijing Normal University
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 …
A Distributed Model For Undergraduate Education In Environmental Remote Sensing: Increased Student Interest In Science And Sense Of Science Identity And Belonging,
2026
Chapman University
A Distributed Model For Undergraduate Education In Environmental Remote Sensing: Increased Student Interest In Science And Sense Of Science Identity And Belonging, Gregory R. Goldsmith, Monae Verbeke, Jeremy Forsythe, Joshua B. Fisher
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
"We present results from a new open-access course in satellite remote sensing of the environment that uses evidence-based, active learning pedagogy to train the next generation of interdisciplinary scientists The course, called Observing Earth from Above, teaches students how to access, visualize, and communicate satellite remote sensing data from NASA’s ECOSTRESS instrument to address a variety of environmental challenges. The resources focus on follow-along tutorials for students and also include recorded lectures and interviews with remote sensing scientists."
Long-Term Variability Of Air Quality And Greenhouse Gas Emissions From Rice Crop Burning In Punjab During 2012–2020,
2026
Indian Institute of Technology (IIT) Mandi
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,
2026
Future Vision Inc.
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,
2026
Pukyong National University
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 …
A Probabilistic Deep Learning Framework For Retrieving Chlorophyll-A From Hyperspectral Imagery: Integrating Channel Attention And Mixture Density Networks,
2026
Chapman University
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 …
