Physical Sciences and Mathematics Commons^™

Enhancing Landslide Susceptibility Modelling Through A Novel Non-Landslide Sampling Method And Ensemble Learning Technique, Chao Zhou, Yue Wang, Ying Cao, Ramesh P. Singh, Bayes Ahmed, Mahdi Motagh, Yang Wang, Ling Chen, Guangchao Tan, Shanshan Li

Mathematics, Physics, and Computer Science Faculty Articles and Research

In recent years, several catastrophic landslide events have been observed throughout the globe, threatening to lives and infrastructures. To minimize the impact of landslides, the need of landslide susceptibility map is important. The study aims to extract high-quality non-landslide samples and improve the accuracy of landslide susceptibility modelling (LSM) outcomes by applying a coupled method of ensemble learning and Machine Learning (ML). The Zigui-Badong section of the Three Gorges Reservoir area (TGRA) in China was considered in the present study. Twelve influencing factors were selected as inputs for LSM, and the relationship between each causal factor and landslide spatial development …

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 …

Monitoring Dam Stability Using Psi And Sbas Analysis, Rejoice Thomas, Wenzhao Li, Shahryar Fazli, Nikolay Grisel Todorov, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Water preservation and maximization of its efficient use is key in areas facing water scarcity like California. One of the most important resources available to us are dams, which are useful to address a variety of needs like water supply, flood control, and maintaining environmental flows. However, if not managed properly, dams can be disastrous to humans and wildlife alike, different water species, habitats, and even impact water quality for a region. In this context, we have used newer Synthetic Aperture Radar Interferometry techniques like Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) to estimate the displacement rates at …

Multi-Sectoral Impact Assessment Of An Extreme African Dust Episode In The Eastern Mediterranean In March 2018, Alexandra Monteiro, Sara Basart, Stelios Kazadzis, Antonis Gkikas, Sophie Vandenbussche, Aurelio Tobias, Carla Gama, Carlos Pérez García-Pando, Enric Tarradellas, George Notas, Nick Middleton, Jonilda Kushta, Vassilis Amiridis, Kostas Lagouvardos, Panagiotis G. Kosmopoulos, Vasiliki Kotroni, Maria Kanakidou, Nikos Mihalopoulos, Nikos Kalivitis, Pavla Daggson-Waldhauserová, Hesham El-Askary, Klaus Sievers, T. Giannaros, Lucia Mona, Marcus Hirtl, Paul Skomorowski, Slobodan Nickovic, Athanasios Votsis, Timo H. Virtanen, Theodoros Christoudias, Biagio Di Mauro, Serena Trippetta, Stanislav Kutuzov, Outi Meinander

Mathematics, Physics, and Computer Science Faculty Articles and Research

In late March 2018, a large part of the Eastern Mediterranean experienced an extraordinary episode of African dust, one of the most intense in recent years, here referred to as the “Minoan Red” event. The episode mainly affected the Greek island of Crete, where the highest aerosol concentrations over the past 15 yeas were recorded, although impacts were also felt well beyond this core area. Our study fills a gap in dust research by assessing the multi-sectoral impacts of sand and dust storms and their socioeconomic implications. Specifically, we provide a multi-sectoral impact assessment of Crete during the occurrence of …

High Spatial And Temporal Resolution Census Data Reveals Communities At Risk Along The Wildland-Urban Interface (Wui) In California, Usa, Jessica E. Viner, Slade T. Laszewski, Wesley Ho, Justin Ewoldt, Pionnah Gregorio, Liz Lyon, Brian Hoover, Shenyue Jia

Mathematics, Physics, and Computer Science Faculty Articles and Research

We tracked census tract level population change along California's wild land-urban interface (WUI) during the past decade (2010-2019), an ecological sensitive region transitioning from developed land to wilderness. Our results from Mann-Kendall analysis, a method employed for monotonic trend detection showed that about one-third (29.1%) of census tracts in California’s WUI have seen a significant population increase from 2010 to 2019, affecting 12.7% population in California.

The population increase along WUI is largely driven by the sixteen counties in the San Francisco Bay Area (10) and Southern California (6). We also found that higher proportion of WUI residents in Bay …

Recurrent Pattern Of Extreme Fire Weather In California, Rackhun Son, S-Y Simon Wang, Seung Hee Kim, Hyungjun Kim, Jee-Hoon Jeong, Jin-Ho Yoon

Mathematics, Physics, and Computer Science Faculty Articles and Research

Historical wildfire events in California have shown a tendency to occur every five to seven years with a rapidly increasing tendency in recent decades. This oscillation is evident in multiple historical climate records, some more than a century long, and appears to be continuing. Analysis shows that this 5–7 year oscillation is linked to a sequence of anomalous large-scale climate patterns with an eastward propagation in both the ocean and atmosphere. While warmer temperature emerges from the northern central Pacific to the west coast of California, La Niña pattern develops simultaneously, implying that the lifecycle of the El Niño-Southern Oscillation …

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

Reaction Intensity Partitioning: A New Perspective Of The National Fire Danger Rating System Energy Release Component, Francis M. Fujioka, David R. Weise, Shyh-Chin Chen, Seung Hee Kim, Menas C. Kafatos

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Rothermel fire spread model provides the scientific basis for the US National Fire Danger Rating System (NFDRS) and several other important fire management applications. This study proposes a new perspective of the model that partitions the reaction intensity function and Energy Release Component (ERC) equations as an alternative that simplifies calculations while providing more insight into the temporal variability of the energy release component of fire danger. We compare the theoretical maximum reaction intensities and corresponding ERCs across 1978, 1988 and 2016 NFDRS fuel models as they are currently computed and as they would be computed under the proposed …

Investigating Decadal Changes Of Multiple Hydrological Products And Land-Cover Changes In The Mediterranean Region For 2009–2018, Wenzhao Li, Sachi Perera, Erik Linstead, Rejoice Thomas, Hesham El-Askary, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Land-cover change is a critical concern due to its climatic, ecological, and socioeconomic consequences. In this study, we used multiple variables including precipitation, vegetation index, surface soil moisture, and evapotranspiration obtained from different satellite sources to study their association with land-cover changes in the Mediterranean region. Both observational and modeling data were used for climatology and correlation analysis. Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) and Global Land Data Assimilation System (GLDAS) were used to extract surface soil moisture and evapotranspiration data. Intercomparing the results of FLDAS and GLDAS suggested that FLDAS data had better …

Changes In Fire Weather Climatology Under 1.5 ◦C And 2.0 ◦C Warming, Rackhun Son, Hyungjun Kim, Shih-Yu (Simon) Wang, Jee-Hoon Jeong, Sung-Ho Woo, Ji-Yoon Jeong, Byung-Doo Lee, Seung Hee Kim, Matthew Laplante, Chun-Geun Kwon, Jin-Ho Yoon

Mathematics, Physics, and Computer Science Faculty Articles and Research

The 2015 Paris Agreement led to a number of studies that assessed the impact of the 1.5 ◦C and 2.0 ◦C increases in global temperature over preindustrial levels. However, those assessments have not actively investigated the impact of these levels of warming on fire weather. In view of a recent series of high-profile wildfire events worldwide, we access fire weather sensitivity based on a set of multi-model large ensemble climate simulations for these low-emission scenarios. The results indicate that the half degree difference between these two thresholds may lead to a significantly increased hazard of wildfire in certain parts of …

Investigating The Lagged Relationship Between Smap Soil Moisture And Live Fuel Moisture In California, Usa, Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Keun Hang S. Yang, Menas Kafatos

Mathematics, Physics, and Computer Science Faculty Articles and Research

Live fuel moisture (LFM), defined as the ratio between water in the fresh biomass out of the dry biomass, is a vital measurement of vegetation water content and flammability. In this study, we investigated the dynamics of in-situ measurement of LFM at all the active sites in California, USA and revealed the difference between evergreen forest and shrub/scrub, the two dominant land cover types in California's fire-prone regions. We found that LFM of evergreen forest responses to soil moisture increase later than shrub/scrub, due to a later occurrence of major precipitation, a lower air temperature, and the different plant physiology. …

An Assessment Of The Filling Process Of The Grand Ethiopian Renaissance Dam And Its Impact On The Downstream Countries, Prakrut Kansara, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa, Mohamed Abdelaty Sayed

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, has been filling at a fast rate. This project has created issues for the Nile Basin countries of Egypt, Sudan, and Ethiopia. The filling of GERD has an impact on the Nile Basin hydrology and specifically the water storages (lakes/reservoirs) and flow downstream. In this study, through the analysis of multi-source satellite imagery, we study the filling of the GERD reservoir. The time-series generated using Sentinel-1 SAR imagery displays the number of classified water pixels in the dam from early June 2017 to September 2020, indicating a contrasting …

An Assessment Of The Hydrological Trends Using Synergistic Approaches Of Remote Sensing And Model Evaluations Over Global Arid And Semi-Arid Regions, Wenzhao Li, Hesham El-Askary, Rejoice Thomas, Surya Prakash Tiwari, Karuppasamy Manikandan, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought and rapid population growth. This will further intensify the risk of desertification, which will seriously affect the local ecological environment, food security and people’s lives. The goal of this research is to analyze the hydrological and land cover characteristics and variability over global arid and semi-arid regions over the last decade (2010–2019) using an integrative approach of …

Characterizing El Niño-Southern Oscillation Effects On The Blue Nile Yield And The Nile River Basin Precipitation Using Empirical Mode Decomposition, Justin A. Le, Hesham El-Askary, Mohamed Allali, Eman Sayed, Hani Sweliem, Thomas C. Piechota, Daniele C. Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Using new mathematical and data-driven techniques, we propose new indices to measure and predict the strength of different El Niño events and how they affect regions like the Nile River Basin (NRB). Empirical Mode Decomposition (EMD), when applied to Southern Oscillation Index (SOI), yields three Intrinsic Mode Functions (IMF) tracking recognizable and physically significant non-stationary processes. The aim is to characterize underlying signals driving ENSO as reflected in SOI, and show that those signals also meaningfully affect other physical processes with scientific and predictive utility. In the end, signals are identified which have a strong statistical relationship with various physical …

Multidecadal Analysis Of Beach Loss At The Major Offshore Sea Turtle Nesting Islands In The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Rejoice Thomas, Hesham El-Askary, Sachi Perera, Ace Vincent B. Flandez, Abdullajid U. Basali, Joselito Francis A. Alcaria, Jinoy Gopalan, Surya Prakash Tiwari, Mubarak Al-Jedani, Perdana K. Prihartato, Ronald A. Loughlan, Ali Qasem, Mohamed A. Qurban, Wail Falath, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Undocumented historical losses of sea turtle nesting beaches worldwide could overestimate the successes of conservation measures and misrepresent the actual status of the sea turtle population. In addition, the suitability of many sea turtle nesting sites continues to decline even without in-depth scientific studies of the extent of losses and impacts to the population. In this study, multidecadal changes in the outlines and area of Jana and Karan islands, major sea turtle nesting sites in the Arabian Gulf, were compared using available Kodak aerographic images, USGS EROS Declassified satellite imagery, and ESRI satellite images. A decrease of 5.1% and 1.7% …

Forecasting Vegetation Health In The Mena Region By Predicting Vegetation Indicators With Machine Learning Models, Sachi Perera, Wenzhao Li, Erik Linstead, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Machine learning (ML) techniques can be applied to predict and monitor drought conditions due to climate change. Predicting future vegetation health indicators (such as EVI, NDVI, and LAI) is one approach to forecast drought events for hotspots (e.g. Middle East and North Africa (MENA) regions). Recently, ML models were implemented to predict EVI values using parameters such as land types, time series, historical vegetation indices, land surface temperature, soil moisture, evapotranspiration etc. In this work, we collected the MODIS atmospherically corrected surface spectral reflectance imagery with multiple vegetation related indices for modeling and evaluation of drought conditions in the MENA …

The Source Detection Of 28 September 2018 Sulawesi Tsunami By Using Ionospheric Gnss Total Electron Content Disturbance, Jann-Yenq Liu, Chi-Yen Lin, Yuh-Ing Chen, Tso-Ren Wu, Meng-Ju Chung, Tien-Chi Liu, Yu-Lin Tsai, Loren C. Chang, Chi-Kuang Chao, Dimitar Ouzounov, Katsumi Hattori

Mathematics, Physics, and Computer Science Faculty Articles and Research

The 28 September 2018 magnitude Mw7.8 Palu, Indonesia earthquake (0.178° S, 119.840° E, depth 13 km) occurred at 10:02 UTC. The major earthquake triggered catastrophic liquefaction, landslides, and a near-field tsunami. The ionospheric total electron content (TEC) derived from records of 5 ground-based global navigation satellite system (GNSS) receivers is employed to detect tsunami traveling ionospheric disturbances (TTIDs). In total, 15 TTIDs have been detected. The ray-tracing and beamforming techniques are then used to find the TTID source location. The bootstrap method is applied in order to further explore the possible location of the tsunami source based on results of …

Long-Term Ndvi And Recent Vegetation Cover Profiles Of Major Offshore Island Nesting Sites Of Sea Turtles In Saudi Waters Of The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Hesham El-Askary, Ace Vincent B. Flandez, Joshua J. Dagoy, Joselito Francis A. Alcaria, Abdullajid U. Basali, Khaled A. Al-Abdulkader, Ronald A. Loughland, Mohamed A. Qurban

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vegetation is an important ecological component of offshore islands in the Arabian Gulf (AG), which maintains long-term resilience of these islands. This is achieved by influencing sediment retention and moisture acquisition via condensation during periods of high humidity and by providing a variety of microhabitats for island fauna. The resilience of offshore islands’ ecosystems in the Saudi waters is important because they host the largest number of nesting hawksbill and green turtles in the AG. This study defines the characteristics and the long-term trends in vegetation cover of the offshore islands used by sea turtles as nesting grounds in the …

Synergistic Use Of Remote Sensing And Modeling For Estimating Net Primary Productivity In The Red Sea With Vgpm, Eppley-Vgpm, And Cbpm Models Intercomparison, Wenzhao Li, Surya Prakash Tiwari, Hesham El-Askary, Mohamed Ali Qurban, Vassilis Amiridis, K. P. Manikandan, Michael J. Garay, Olga V. Kalashnikova, Thomas C. Piechota, Daniele C. Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Primary productivity (PP) has been recently investigated using remote sensing-based models over quite limited geographical areas of the Red Sea. This work sheds light on how phytoplankton and primary production would react to the effects of global warming in the extreme environment of the Red Sea and, hence, illuminates how similar regions may behave in the context of climate variability. study focuses on using satellite observations to conduct an intercomparison of three net primary production (NPP) models--the vertically generalized production model (VGPM), the Eppley-VGPM, and the carbon-based production model (CbPM)--produced over the Red Sea domain for the 1998-2018 time period. …

Earth Observation And Cloud Computing In Support Of Two Sustainable Development Goals For The River Nile Watershed Countries, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

In September 2015, the members of United Nations adopted the 2030 Agenda for Sustainable Development with universal applicability of 17 Sustainable Development Goals (SDGs) and 169 targets. The SDGs are consequential for the development of the countries in the Nile watershed, which are affected by water scarcity and experiencing rapid urbanization associated with population growth. Earth Observation (EO) has become an important tool to monitor the progress and implementation of specific SDG targets through its wide accessibility and global coverage. In addition, the advancement of algorithms and tools deployed in cloud computing platforms provide an equal opportunity to use EO …

Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin

Mathematics, Physics, and Computer Science Faculty Articles and Research

Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent …

A Feasibility Study On The Application Of Tvdi On Accessing Wildfire Danger In The Korean Peninsula, Kwang Nyun Kim, Seung Hee Kim, Myoung Soo Won, Keun Chang Jang, Won Jun Choi, Yun Gon Lee

Mathematics, Physics, and Computer Science Faculty Articles and Research

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to …

Long-Term Aerosol Trends And Variability Over Central Saudi Arabia Using Optical Characteristics From Solar Village Aeronet Measurements, Mohammed Al Otaibi, Ashraf Farahat, Bassam Tawabini, M. Hafidz Omar, Emad Ramadan, Abdelgadir Abuelgasim, Ramesh Singh

Mathematics, Physics, and Computer Science Faculty Articles and Research

Natural and anthropogenic aerosols over the Kingdom of Saudi Arabia (KSA) play a major role in affecting the regional radiation budget. The long-term variability of these aerosols’ physical and optical parameters, including aerosol optical depth (AOD) and Ångström exponent (α), were measured at a location near central KSA using the Solar Village (SV) AERONET (Aerosol Robotic Network) station during the period December 1999–January 2013. The AERONET measurements show an overall increase in AOD on an annual basis. This upward trend is mainly attributed to a prolonged increase in the monthly/seasonal mean AOD during March–June and during August– September. In contrast, …

Assessing Environmentally Sensitive Land To Desertification Using Medalus Method In Mongolia, Eun Jung Lee, Dongfan Piao, Cholho Song, Jiwon Kim, Chul-Hee Lim, Eunji Kim, Jooyeon Moon, Menas Kafatos, Munkhnsan Lamchin, Seong Woo Jeon, Woo-Kyun Lee

Mathematics, Physics, and Computer Science Faculty Articles and Research

Desertification is a global phenomenon caused by various processes, including climate change, vegetation processes, and human activities. The need to combat desertification is increasing in many countries. A reasonable assessment of the vulnerability or sensitivity of land cover to desertification at national scales is crucial to formulate appropriate strategies or policies for combating it. The main purpose of this work was to quantitatively assess the sensitivity of land cover to desertification in Mongolia using the MEDALUS approach. The MEDALUS method is a widely known technique for assessing desertification in the Mediterranean area. In this study, the method was adjusted to …

Urban Health Related Air Quality Indicators Over The Middle East And North Africa Countries Using Multiple Satellites And Aeronet Data, Maram El-Nadry, Wenzhao Li, Hesham El-Askary, Mohamed A. Awad, Alaa Ramadan Awad

Mathematics, Physics, and Computer Science Faculty Articles and Research

Air pollution is reported as one of the most severe environmental problems in the Middle East and North Africa (MENA) region. Remotely sensed data from newly available TROPOMI - TROPOspheric Monitoring Instrument on board Sentinel-5 Precursor, shows an annual mean of high-resolution maps of selected air quality indicators (NO2, CO, O3, and UVAI) of the MENA countries for the first time. The correlation analysis among the aforementioned indicators show the coherency of the air pollutants in urban areas. Multi-year data from the Aerosol Robotic Network (AERONET) stations from nine MENA countries are utilized here to study the aerosol optical depth …

Gamma Ray And Radon Anomalies In Northern Taiwan As A Possible Preearthquake Indicator Around The Plate Boundary, Ching-Chou Fu, Lou-Chuang Lee, Tsanyao Frank Yang, Cheng-Horng Lin, Cheng-Hong Chen, Vivek Walia, Tsung-Kwei Liu, Dimitar Ouzounov, Gioacchino Giuliani, Tzu-Hua Lai, Peng-Kang Wang

Mathematics, Physics, and Computer Science Faculty Articles and Research

Taiwan is tectonically situated in an oblique collision zone between the Philippine Sea Plate (PSP) and the Eurasian Plate (EP). Continuous observations of gamma rays at the Yangmingshan (YMSG) station and soil radon at the Tapingti (TPT) station were recorded in the volcanic area and around a major fault zone, respectively, in Taiwan for seismic studies. A number of anomalous high gamma ray counts and radon concentrations at certain times were found. It is noted that significant increases of soil radon concentrations were observed and followed by the increase in gamma rays a few days to a few weeks before …

Studying The Impact On Urban Health Over The Greater Delta Region In Egypt Due To Aerosol Variability Using Optical Characteristics From Satellite Observations And Ground-Based Aeronet Measurements, Wenzhao Li, Elham Ali, Islam Abou Al-Magd, Moustafa Mohamed Mourad, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

This research addresses the aerosol characteristics and variability over Cairo and the Greater Delta region over the last 20 years using an integrative multi-sensor approach of remotely sensed and PM10 ground data. The accuracy of these satellite aerosol products is also evaluated and compared through cross-validation against ground observations from the AErosol RObotic NETwork (AERONET) project measured at local stations. The results show the validity of using Multi-angle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms for quantitative aerosol optical depth (AOD) assessment as compared to Ozone Monitoring Instrument (OMI), Sea-viewingWide Field-of-view …

Estimating Live Fuel Moisture Using Smap L-Band Radiometer Soil Moisture For Southern California, Usa, Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Menas Kafatos

Mathematics, Physics, and Computer Science Faculty Articles and Research

Live fuel moisture (LFM) is a field-measured indicator of vegetation water content and a crucial observation of vegetation flammability. This study presents a new multi-variant regression model to estimate LFM in the Mediterranean ecosystem of Southern California, USA, using the Soil Moisture Active Passive (SMAP) L-band radiometer soil moisture (SMAP SM) from April 2015 to December 2018 over 12 chamise (Adenostoma fasciculatum) LFM sites. The two-month lag between SMAP SM and LFM was utilized either as steps to synchronize the SMAP SM to the LFM series or as the leading time window to calculate the accumulative SMAP SM. …

Coral Reef Change Detection In Remote Pacific Islands Using Support Vector Machine Classifiers, Justin J. Gapper, Hesham El-Askary, Erik Linstead, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

Despite the abundance of research on coral reef change detection, few studies have been conducted to assess the spatial generalization principles of a live coral cover classifier trained using remote sensing data from multiple locations. The aim of this study is to develop a machine learning classifier for coral dominated benthic cover-type class (CDBCTC) based on ground truth observations and Landsat images, evaluate the performance of this classifier when tested against new data, then deploy the classifier to perform CDBCTC change analysis of multiple locations. The proposed framework includes image calibration, support vector machine (SVM) training and tuning, statistical assessment …