Remote Sensing Commons^™

Ensemble Machine Learning Approaches For Bathymetry Estimation In Multi-Spectral Images, Kazi A. Islam, Omar Abdul-Hassan, Hongfang Zhang, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

OES Faculty Publications

Traditional bathymetry measures require a large number of human hours, and many bathymetry records are obsolete or missing. Automated measures of bathymetry would reduce costs and increase accessibility for research and applications. In this paper, we optimized a recent machine learning model, named CatBoostOpt, to estimate bathymetry based on high-resolution WorldView-2 (WV-2) multi-spectral optical satellite images. CatBoostOpt was demonstrated across the Florida Big Bend coastline, where the model learned correlations between in situ sound Navigation and Ranging (Sonar) bathymetry measurements and the corresponding multi-spectral reflectance values in WV-2 images to map bathymetry. We evaluated three different feature transformations as inputs …

Shifting Waters: A 41-Year Time-Series Analysis Of Surface Water Change In The Prairie Pothole Region, Madison Dejarlais

Electronic Theses and Dissertations

The Prairie Pothole Region (PRR) is a landscape defined by a dynamic surface water system, with wetlands, lakes, and rivers playing critical roles in supporting biodiversity, regulating floods, and maintaining hydrological balance. This study conducts a time-series analysis of surface water change in the PPR from 1984 to 2024, using remote sensing tools including Google Earth Engine, ArcGIS Pro, and ENVI. 41 annual surface water presence rasters were compiled into a cumulative dataset, allowing for both year-to-year comparisons and broader trend analysis. Results indicate that the presence of surface water in the PPR has not followed a simple linear trend. …

Performance Of Acoustic Telemetry And Space Use Of Pallid Sturgeon In The Lower Platte River, Nebraska, Christopher F. Pullano

School of Natural Resources: Dissertations, Theses, and Student Research

Pallid Sturgeon (Scaphirhynchus albus) are centenarian, potamodromous, rheophiles that historically occupied the Missouri River and Mississippi River basins. Listed on the U.S. Endangered Species Act in 1990, population declines are attributed to habitat fragmentation and degradation, as well as overharvest, and hybridization. A knowledge gap exists regarding the extent to which tributaries facilitate key life stages for Pallid Sturgeon. This study evaluated the capacity of acoustic telemetry to monitor the movements of Pallid Sturgeon in a shallow, braided tributary to the Missouri River. The specific objectives were to (1) evaluate the environmental variables influencing the performance of acoustic …

Time Series Decomposition Of Land Surface Temperature For Long-Term Trend Forecasting And Impact On Nesting Sea Turtle Habitats In The Arabian Gulf, Sachi Perera, Rommel H. Maneja, Mohamed Allali, Cyril Rakovski, Erik Linstead, Daniele Struppa, Ali Qasem, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Improving land surface temperature (LST) modeling is vital for mitigating climate change effects on various ecosystems and marine habitats such as important sea turtle habitats. Over the past decade, extreme temperatures have likely significantly affected nesting sea turtle habitats in the Arabian Gulf, with predominantly female hatchlings creating an imbalance in the sex ratio. Such shifts have profound implications for these habitats’ long-term survival and conservation management. This study leverages statistical machine learning models to measure ongoing temporal variations in LST. We break down the LST time series into trend, seasonal, and noise components using classical decomposition methods like X11, …

Multi-Temporal Analysis Of Urbanization-Driven Slope And Ecological Impact Using Machine-Learning And Remote Sensing Techniques, Zhang Hao, Muhammad Haseeb, Zheng Xiangtian, Zainab Tahir, Syed Amer Mahmood, Aqil Tariq, Rana Waqar Aslam, M. Abdullah-Al-Wadud, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Rapid urbanization in Lahore, Pakistan, has led to significant ecological and thermal challenges, particularly the intensification of Urban Heat Island (UHI) effects and increased thermal stress as measured by the Urban Thermal Field Variance Index (UTFVI). This study employs a multi-temporal evaluation of Landsat satellite imagery and GIS-based analysis to investigate the Spatio-temporal trends in land-use and land-cover (LULC) changes from 1994 to 2024. We detected substantial changes in urban growth, vegetation cover, and barren areas using supervised classification (Random Forest) methods and remote sensing indices such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), NDBI (Normalized …

Spatial Gap-Filling Of Himawari-8 Hourly Aod Products Using Machine Learning With Model-Based Aod And Meteorological Data: A Focus On The Korean Peninsula, Youjeong Youn, Seoyeon Kim, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, …

Climatological Trends And Effects Of Aerosols And Clouds On Large Solar Parks: Application Examples In Benban (Egypt) And Al Dhafrah (Uae), Harshal Dhake, Panagiotis Kosmopoulos, Antonis Mantakas, Yashwant Kashyap, Hesham El-Askary, Omar Elbadawy

Mathematics, Physics, and Computer Science Faculty Articles and Research

Solar energy production is vastly affected by climatological factors. This study examines the impact of two primary climatological factors, aerosols and clouds, on solar energy production at two of the world’s largest solar parks, Benban and Al Dhafrah Solar Parks, by using Earth observation data. Cloud microphysics were obtained from EUMETSAT, and aerosol data were obtained from the CAMS and assimilated with MODIS data for higher accuracy. The impact of both factors was analysed by computing their trends over the past 20 years. These climatological trends indicated the variations in the change in each of the factors and their resulting …

Coupling Between Evapotranspiration, Water Use Efficiency, And Evaporative Stress Index Strengthens After Wildfires In New Mexico, Usa, Ryan C. Joshi, Annalise Jensen, Madeleine Pascolini-Campbell, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

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Challenges And Future Directions In Quantifying Terrestrial Evapotranspiration, Koong Yi, Gabriel B. Senay, Joshua B. Fisher, Lixin Wang, Kosana Suvočarev, Housen Chu, Georgianne W. Moore, Kimberly A. Novick, Mallory L. Barnes, Trevor F. Keenan, Kanishka Mallick, Xiangzhong Luo, Justine E. C. Missik, Kyle B. Delwiche, Jacob A. Nelson, Stephen P. Good, Xiangming Xiao, Steven A. Kannenberg, Arman Ahmadi, Tianxin Wang, Gil Bohrer, Marcy E. Litvak, David E. Reed, A. Christopher Oishi, Margaret S. Torn, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Terrestrial evapotranspiration is the second-largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross-disciplinary group of ET scientists to overcome the …

Conducting Structure-From-Motion (Sfm) Modeling Of Freshwater Environments Using Unpiloted Aerial Systems (Uas): Challenges And Lessons Learned, Benjamin T. Fraser, Christine L. Bunyon, Russell G. Congalton

Faculty Publications

The pairing of Unpiloted Aerial Systems (UAS) and Structure from Motion (SfM) has provided new capabilities for modeling freshwater environments. Applications of UAS-SfM range from water quality monitoring to the mapping of aquatic vegetation. The models produced provide users with the ability to analyze features at ultra-high-resolutions and across scales not easily achieved through in situ sampling. Despite the demonstrated benefits of UAS-SfM in freshwater and other natural resource disciplines, there remain fundamental technical challenges in the modeling of environments with homogenous surfaces (e.g., water). In this research, the effectiveness of several image collection and processing approaches for the modelling …

Challenges Of Using More Precise Temporal And Spatial Resolution Of Remote Sensing Data For Surface Water Quality Monitoring, Ivan Rykin

Dartmouth College Master’s Theses

Monitoring river suspended sediment concentration (SSC) is critical for environmental challenges such as understanding the fate of thawed permafrost sediment and its impact on global carbon cycling. However, traditional SSC monitoring using Landsat imagery is limited by spatial and temporal constraints, particularly for narrow rivers in cloudy and/or snowy regions.

This study investigates the use of higher spatial (3 m) and temporal (daily) resolution satellite imagery from the PlanetScope constellation to estimate SSC in remote rivers such as those in the Arctic. I compare the performance of PlanetScope’s spectral resolution (4 and 8 bands) with Landsat 7. Merging data from …

Seasonal Dynamics In Land Surface Temperature In Response To Land Use Land Cover Changes Using Google Earth Engine, Lei Feng, Sajjad Hussain, Narcisa G. Pricope, Sana Arshad, Aqil Tariq, Li Feng, Muhammad Mubeen, Rana Waqar Aslam, Mohammed S. Fnais, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Changes in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, …

Integrating Remote Sensing And Machine Learning To Determine Past, Current And Future Crop Water Use From The Nubian Sandstone Aquifer System, Moaz Ishag

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

The agriculture sector is a significant consumer of water, and sustainable water use begins with monitoring irrigated land. Delineating irrigated land supports decision-makers and promotes the sustainable use of this crucial resource. This study focuses on the Nubian Sandstone Aquifer System (NSAS), the largest aquifers in the world, which spans Egypt, Sudan, Libya, and Chad. The study aims to: 1) quantify the increase in irrigated hectares (both pivot and non-pivot) from 2000-2001 to 2023-2024; 2) identify major irrigated crop types and their water requirements; and 3) quantify groundwater crop water use from the NSAS using remote sensing via the Google …

The Ecosystem As Super-Organ/Ism, Revisited: Scaling Hydraulics To Forests Under Climate Change, Jeffrey D. Wood, Matteo Detto, Marvin Browne, Nathan J.B. Kraft, Alexandra G. Konings, Joshua B. Fisher, Gregory R. Quetin, Anna T. Trugman, Troy S. Magney, Camila D. Medeiros, Nidhi Vinod, Thomas N. Buckley, Lawren Sack

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO₂) uptake and water vapor loss, important for predicting and managing the future of Earth's ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals, or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Net Fluxes Of Broadband Shortwave And Photosynthetically Active Radiation Complement Ndvi And Near Infrared Reflectance Of Vegetation To Explain Gross Photosynthesis Variability Across Ecosystems And Climate, Kanishka Mallick, Joseph Verfaillie, Tianxin Wang, Ariane Arias Ortiz, Daphne Szutu, Koong Yi, Yanghui Kang, Robert Shortt, Tian Hu, Mauro Sulis, Zoltan Szantoi, Gilles Boulet, Joshua B. Fisher, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A significant challenge in global change research is understanding how vegetation interacts with the environment to influence ecosystem gross primary productivity (GPP) through carbon assimilation. One emerging objective is to consistently predict GPP fluctuations worldwide by establishing a robust scaling relationship between GPP measured at flux towers and satellite spectral reflectance data. However, a major hurdle in achieving this goal is the discrepancy in spatial resolution between early satellite measurements and eddy flux measurements. By using a large set of growing season data covering 100 site-years in North and Central America, we explored the potential of transforming incident and reflected …

Kinematic And Dynamic Structure Of The 18 May 2020 Squall Line Over South Korea, Wishnu Agum Swastiko, Chia-Lun Tsai, Seung Hee Kim, Gyuwon Lee

Institute for ECHO Articles and Research

The diagonal squall line that passed through the Korean Peninsula on the 18 May 2020 was examined using wind data retrieved from multiple Doppler radar synthesis focusing on its kinematic and dynamic aspects. The low-level jet, along with warm and moist air in the lower level, served as the primary source of moisture supply during the initiation and formation process. The presence of a cold pool accompanying the squall line played a role in retaining moisture at the surface. As the squall line approached the Korean Peninsula, the convective bands in the northern segment (NS) and southern segment (SS) of …

Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the spatiotemporal associations of data on input variables, a deep learning (DL) architecture with the combination of a convolutional neural network and a recurrent neural network can be an ideal design for nowcasting rainfall. In this study, a long short-term memory (LSTM) modeling structure is proposed with convolutional operations on input variables. To resolve the issue of …

Ground Electric Field, Atmospheric Weather And Electric Grid Variations In Northeast Greece Influenced By The March 2012 Solar Activity And The Moderate To Intense Geomagnetic Storms, Georgios Anagnostopoulos, Anastasios Karkanis, Athanasios Kampatagis, Panagiotis Marhavilas, Sofia-Anna Menesidou, Dimitrios Efthymiadis, Stefanos Keskinis, Dimitar Ouzounov, Nick Hatzigeorgiu, Michael Danakis

Mathematics, Physics, and Computer Science Faculty Articles and Research

In a recent paper, we extended a previous study on the solar solar influence to the generation of the March 2012 heatwave in the northeastern USA. In the present study we check the possible relationship of solar activity with the early March 2012 bad weather in northeast Thrace, Greece. To this end, we examined data from various remote sensing instrumentation monitoring the Sun (SDO satellite), Interplanetary space (ACE satellite), the Earth’s magnetosphere (Earth-based measurements, NOAA-19 satellite), the top of the clouds (Terra and Aqua satellites), and the near ground atmosphere. Our comparative data analysis suggests that: (i) the winter-like weather …

Spatial Analyses On Pre-Earthquake Ionospheric Anomalies And Magnetic Storms Observed By China Seismo-Electromagnetic Satellite In August 2018, Jann-Yeng Tiger Liu, Xuhui Shen, Fu-Yuan Chang, Yuh-Ing Chen, Yang-Yi Sun, Chieh‑Hung Chen, Sergey Pulinets, Katsumi Hattori, Dimitar Ouzounov, Valerio Tramutoli, Michel Parrot, Wei-Sheng Chen, Cheng-Yan Liu, Fei Zhang, Dapeng Liu, Xue-Min Zhang, Rui Yan, Qiao Wang

Mathematics, Physics, and Computer Science Faculty Articles and Research

The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate pre-earthquake ionospheric anomalies (PEIAs) and ionospheric space weather. The CSES probes manifest longitudinal features of four-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs. CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric …

Evaluation Of Seven Satellite-Based And Two Reanalysis Global Terrestrial Evapotranspiration Products, Zijing Xie, Yunjun Yao, Qingxin Tang, Meng Liu, Joshua B. Fisher, Jiquan Chen, Xiaotong Zhang, Kun Jia, Yufu Li, Ke Shang, Bo Jiang, Junming Yang, Ruiyang Yu, Xueyi Zhang, Xiaozheng Guo, Lu Liu, Jing Ning, Jiahui Fan, Lilin Zhang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Although comprehensive evaluation of different types of global terrestrial evapotranspiration (ET) products has been conducted, the satellite remote sensing techniques have prompted the development of several available global ET products, warranting a reassessment as products continue to evolve. Recently, we produced the long-term Global LAnd Surface Satellite (GLASS) ET product, but there is a lack of comparison and evaluation with other ET products and EC observations on a global scale. In this study, we evaluated the accuracy and uncertainty of seven satellite-based (GLASS-AVHRR, GLASS-MODIS, BESS, FLUXCOM, GLEAM, MOD16, and PML_V2) and two reanalysis (ERA5 and MERRA2) global terrestrial ET products …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022, Sandeep Kumar Mondal, Vatsal D. Patel, Rishikesh Bharti, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Karakoram Himalayas are vulnerable to glacial lake outburst floods (GLOFs), which cause catastrophic floods in the surrounding areas. The increasing natural and anthropogenic activities, especially in the Indo-Gangetic Plains at the southern flank of the towering Himalayas, could be the cause of climate change affecting the frequency of the natural hazards in the Himalayas. In the present study, a detailed analysis of the Shisper Lake breach of 7 May 2022 is carried out using satellite remote sensing. A decreasing trend in the glacial mass balance is observed between 2017 and 2021; in this period, frequent GLOF episodes occurred. A pronounced …

Insar Time Series Analysis To Evaluate Subsidence Risk Of Monumental Chandigarh City (India) And Surroundings, Jungrack Kim, Shih-Yuan Lin, Tejpal Singh, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Groundwater depletion is one of the serious geo-environmental issues causing ground subsidence, which damage buildings, infrastructures and causes loss of life. The quantitative and qualitative evaluation of groundwater variability requires multiple approaches to measure hydraulic head level and geodetic deformation. In this study, we have made efforts to integrate multiple hierarchical space-borne data, including Gravity Recovery and Climate Experiment (GRACE), Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR), geological and hydrological data, to quantify subsidence in Chandigarh city and its surroundings. First, we conducted New-Small BAseline Subsets (NSBAS) and pointwise persistent scatterer (PS) InSAR techniques in parallel, using three-years Sentinel-1 data showing …

A Comparative Study Of Vinti-Based Orbit Propagation And Estimation For Cubesats In Very Low Earth Orbits, Ethan Michael Senecal

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, there has been a growing interest in CubeSats and very low Earth orbit (VLEO) space missions. Mission SeaLion, a collaborative CubeSat mission between Old Dominion University, the U.S. Coast Guard Academy, and U.S. Air Force Institute of Technology, planned to launch a 3U CubeSat into VLEO. The VLEO mission is a particularly challenging environment for navigation and orbit propagation because drag introduces a significant perturbation for orbit models such as SGP4. Additionally, mission requirements left no capacity for attitude determination or control, further reducing knowledge of drag behavior of the satellite in flight. This deficiency is a …

Timing And Magnitude Of Drought Impacts On Carbon Uptake Across A Grassland Biome, Andrew Felton, Gregory R. Goldsmith

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Although drought is known to negatively impact grassland functioning, the timing and magnitude of these impacts within a growing season remains unresolved. Previous small-scale assessments indicate grasslands may only respond to drought during narrow periods within a year; however, large-scale assessments are now needed to uncover the general patterns and determinants of this timing. We combined remote sensing datasets of gross primary productivity and weather to assess the timing and magnitude of grassland responses to drought at 5 km² temporal resolution across two expansive ecoregions of the western US Great Plains biome: the C₄-dominated shortgrass steppe and …

Linkages Between Atmospheric Circulation, Weather, Climate, Land Cover And Social Dynamics Of The Tibetan Plateau, Shobha Kumari Yadav

Graduate Theses, Dissertations, and Problem Reports (ETD)

The Tibetan Plateau (TP) is an important landmass that plays a significant role in both regional and global climates. In recent decades, the TP has undergone significant changes due to climate and human activities. Since the 1980s anthropogenic activities, such as the stocking of livestock, land cover change, permafrost degradation, urbanization, highway construction, deforestation and desertification, and unsustainable land management practices, have greatly increased over the TP. As a result, grasslands have undergone rapid degradation and have altered the land surface which in turn has altered the exchange of heat and moisture properties between land and the atmosphere. But gaps …

Impact Of Atmospheric Correction On Classification And Quantification Of Seagrass Density From Worldview-2 Imagery, Victoria J. Hill, Richard C. Zimmerman, Paul Bissett, David Kohler, Blake Schaeffer, Megan Coffer, Jiang Li, Kazi Aminul Islam

OES Faculty Publications

Mapping the seagrass distribution and density in the underwater landscape can improve global Blue Carbon estimates. However, atmospheric absorption and scattering introduce errors in space-based sensors’ retrieval of sea surface reflectance, affecting seagrass presence, density, and above-ground carbon (AGC_seagrass) estimates. This study assessed atmospheric correction’s impact on mapping seagrass using WorldView-2 satellite imagery from Saint Joseph Bay, Saint George Sound, and Keaton Beach in Florida, USA. Coincident in situ measurements of water-leaving radiance (L_w), optical properties, and seagrass leaf area index (LAI) were collected. Seagrass classification and the retrieval of LAI were compared after empirical line …

Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

Highly short-term forecasting, or nowcasting, of heavy rainfall due to rapidly evolving mesoscale convective systems (MCSs) is particularly challenging for traditional numerical weather prediction models. To overcome such a challenge, a growing number of studies have shown significant advantages of using machine learning (ML) modeling techniques with remote sensing data, especially weather radar data, for high-resolution rainfall nowcasting. To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall that can also be associated with domain knowledge. In this study, a set of MCS types consisting of …

Possible Overestimation Of Nitrogen Dioxide Outgassing During The Beirut 2020 Explosion, Ashraf Farahat, Nayla El-Kork, Ramesh P. Singh, Feng Jing

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

On 4 August 2020, a strong explosion occurred near the Beirut seaport, Lebanon and killed more than 200 people and damaged numerous buildings in the vicinity. As Amonium Nitrate (AN) caused the explosion, many studies claimed the release of large amounts of NO₂ in the atmosphere may have resulted in a health hazard in Beirut and the vicinity. In order to reasonably evaluate the significance of NO₂ amounts released in the atmosphere, it is important to investigate the spatio-temporal distribution of NO₂ during and after the blast and compare it to the average day-to-day background emissions from …