A5011362394- Meteorological Phenomena and Simulations
- Flood Risk Assessment and Management
- Earthquake Detection and Analysis
- Energy Load and Power Forecasting
- Tropical and Extratropical Cyclones Research
- Geographic Information Systems Studies
- Atmospheric and Environmental Gas Dynamics
- Climate variability and models
- Seismology and Earthquake Studies
- earthquake and tectonic studies
- Solar Radiation and Photovoltaics
- Remote-Sensing Image Classification
- Data Management and Algorithms
- Air Quality Monitoring and Forecasting
- Radioactive contamination and transfer
- Urban Heat Island Mitigation
- Hydrological Forecasting Using AI
- Wind and Air Flow Studies
- Neural Networks and Applications
- Human Mobility and Location-Based Analysis
- Cryospheric studies and observations
- Remote Sensing in Agriculture
- Evolutionary Algorithms and Applications
- Calibration and Measurement Techniques
- Seismic Waves and Analysis
Pennsylvania State University
2015-2024
Pacific States University
2023
NSF National Center for Atmospheric Research
2014-2022
Research Applications (United States)
2019
Walker (United States)
2013-2018
Institute of Geography of the Slovak Academy of Sciences
2009-2017
Lamont-Doherty Earth Observatory
2017
Columbia University
2017
George Mason University
2004-2013
A new methodology is introduced that leverages data harvested from social media for tasking the collection of remote-sensing imagery during disasters or emergencies. The images are then fused with multiple sources contributed damage assessment transportation infrastructure. capability valuable in situations where environmental hazards such as hurricanes severe weather affect very large areas. During these types it paramount to 'cue' assess impact fast-moving and potentially life-threatening...
Asphalt roads are the basic component of a land transportation system, and quality asphalt will decrease during use stage because aging deterioration road surface. In end, some pavement distresses may appear on surface, such as most common potholes cracks. order to improve efficiency inspection, currently new forms remote sensing data without destructive effect widely used detect distresses, digital images, light detection ranging, radar. Multispectral imagery presenting spatial spectral...
Evaluating the condition of transportation infrastructure is an expensive, labor intensive, and time consuming process. Many traditional road evaluation methods utilize measurements taken in situ along with visual examinations interpretations. The measurement damage deterioration often qualitative limited to point observations. Remote sensing techniques offer nondestructive for assessment large spatial coverage. These tools provide opportunity frequent, comprehensive, quantitative surveys...
Abstract. A new methodology for the generation of flood hazard maps is presented fusing remote sensing and volunteered geographical data. Water pixels are identified utilizing a machine learning classification two Landsat scenes, acquired before during flooding event as well digital elevation model paired with river gage statistical computes probability flooded areas function number adjacent classified water. Volunteered data obtained through Google news, videos photos added to modify...
Abstract. This research proposes a methodology that leverages non-authoritative data to augment flood extent mapping and the evaluation of transportation infrastructure. The novelty this approach is application freely available, its integration with established methods. Crowdsourced photos volunteered geographic are fused together using geostatistical interpolation create an estimation damage in New York City following Hurricane Sandy. assessment utilized authoritative storm surge map as...
The first goal of this study is to quantify the magnitude and spatial variability air quality changes in USA during COVID-19 pandemic. We focus on two pollutants that are federally regulated, nitrogen dioxide (NO
Abstract. The paper examines the possible relationship of anomalous variations different atmospheric and ionospheric parameters observed around time a strong earthquake (Mw 7.8) which occurred in Mexico (state Colima) on 21 January 2003. These are interpreted within framework developed model Lithosphere-Atmosphere-Ionosphere coupling. main attention is focused processes near ground layer atmosphere involving ionization air by radon, water molecules' attachment to formed ions, corresponding...
Abstract. Natural gas infrastructure releases methane (CH4), a potent greenhouse gas, into the atmosphere. The estimated emission rate associated with production and transportation of natural is uncertain, hindering our understanding its footprint. This study presents new application inverse methodology for estimating regional rates from gathering facilities in north-eastern Pennsylvania. An inventory CH4 emissions was compiled major sources served as input data Weather Research Forecasting...
Every year, flood disasters are responsible for widespread destruction and loss of human life. Remote sensing data capable providing valuable, synoptic coverage events but not always available because satellite revisit limitations, obstructions from cloud cover or vegetation canopy, expense. In addition, knowledge road accessibility is imperative during all phases a event. June 2013, the City Calgary experienced sudden extensive flooding lacked comprehensive remote coverage. Using this event...
Unlike deterministic forecasts, probabilistic predictions provide estimates of uncertainty, which is an additional value for decision-making. Previous studies have proposed the analog ensemble (AnEn), a technique to generate uncertainty information from purely forecast. The objective this study improve AnEn performance wind power forecasts by developing static and dynamic weighting strategies, optimize predictor combination with brute-force continuous ranked probability score (CRPS)...
Remote-sensing satellite data are routinely used during disasters for damage assessment and to coordinate relief operations. Although there is a plethora of sensors able provide actionable about an event, their temporal resolution limited by revisit time, presence clouds, errors in the reception data. These limitations do not allow uninterrupted monitoring, which crucial emergencies. This research presents approach that leverages increased crowdsourced partially overcome The proposed focuses...
Many scientific problems require multiple distinct computational tasks to be executed in order achieve a desired solution. We introduce the Ensemble Toolkit (EnTK) address challenges of scale, diversity and reliability they pose. describe design implementation EnTK, characterize its performance integrate it with two exemplar use cases: seismic inversion adaptive analog ensembles. perform nine experiments, characterizing EnTK overheads, strong weak scalability, case imple-mentations, at scale...
Hurricane Ian in 2022 was a destructive category 4 Atlantic hurricane striking the state of Florida, which caused hundreds deaths and injuries, catastrophic property damage, an economic loss more than $112 billion. Before landfall government issued evacuation orders high-risk zones to reduce casualties injuries. However, there is limited data available monitor actual patterns compliance with at large geographic scale. This study utilizes human mobility (i.e. SafeGraph Weekly Pattern) analyse...
Data heterogeneity can pose a great challenge to process and systematically fuse low-level data from different modalities with no recourse heuristics manual adjustments refinements. In this paper, new methodology is introduced for the fusion of measured detecting predicting weather-driven natural hazards. The proposed research introduces robust theoretical algorithmic framework heterogeneous in near real time. We establish flexible information-based target optimality criterion choice, which...
Abstract Interferometric Synthetic Aperture Radar (InSAR) provides subcentimetric measurements of surface displacements, which are key for characterizing and monitoring magmatic processes in volcanic regions. The abundant displacements multitemporal InSAR data routinely acquired by SAR satellites can facilitate near real‐time volcano on a global basis. However, the presence atmospheric signals interferograms complicates interpretation those measurements, even lead to misinterpretation...
The rising temperature is one of the key indicators a warming climate, capable causing extensive stress to biological systems as well built structures.Ambient collected at ground level can have higher variability than regional weather forecasts, which fail capture local dynamics. There remains clear need for accurate air prediction suburban scale high temporal and spatial resolutions. This research proposed framework based on long short-term memory (LSTM) deep learning network generate...