Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Arabian Gulf (2)
- FLDAS (2)
- Google Earth Engine (2)
- 3 (1)
- 5 (1)
-
- 7 (1)
- Atmospheric modeling (1)
- Beach loss (1)
- Beamforming (1)
- Biological system modeling (1)
- Bootstrap method (1)
- CHIRPS (1)
- Carbon (1)
- Climate classification (1)
- Coastal squeeze (1)
- Desertification (1)
- Drylands (1)
- ENSO effects (1)
- EVI (1)
- El niño (1)
- Empirical mode decomposition (1)
- Forest fires (1)
- Fully convolutional neural networks (1)
- GLDAS (1)
- GNSS TEC (1)
- GRACE (1)
- Google Cloud Platform (1)
- Greater Hinggan Mountain area (1)
- Hydrology (1)
- Impervious surface (1)
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
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
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
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
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
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
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
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
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
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
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 …