Ahmed A. Hashem
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
Also affiliated: Suez Canal University (2020–2024); Purdue University West Lafayette (2020); University of Arkansas System (2022–2024); Bangladesh Agricultural Research Institute (2023)
Faculty Researcher
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Ahmed A. Hashem's research focuses on the application of remote sensing technologies and machine learning for agricultural applications. His work investigates methods for determining crop nutrient deficiencies, such as nitrogen in maize, and detecting variations in crop yield using unmanned aerial vehicle (UAV) imagery and deep learning techniques. Hashem also studies the impact of soil and water conditions, including salinity and shallow groundwater, on crop productivity and evapotranspiration, often employing remote sensing for analysis.
His publications include research on improving soil and crop properties through amendments like gypsum and compost, as well as the use of nanoparticles. He has also explored optimizing water resource management through simulation-optimization approaches for aquifer recharge. Hashem's scholarship metrics include an h-index of 7, with 17 total publications and 219 citations. He has collaborated with several faculty members at Arkansas State University, including Emily S. Bellis and John W. Nowlin.
Metrics
- h-index: 7
- Publications: 17
- Citations: 226
Selected Publications
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A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts (2024)
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Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach (2024)
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Small Unmanned Aircraft Systems and Agro-Terrestrial Surveys Comparison for Generating Digital Elevation Surfaces for Irrigation and Precision Grading (2023)
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A Maximal Overlap Discrete Wavelet Packet Transform Coupled with an LSTM Deep Learning Model for Improving Multilevel Groundwater Level Forecasts (2023)
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The combined impact of shallow groundwater and soil salinity on evapotranspiration using remote sensing in an agricultural alluvial setting (2023)
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Effect of Gypsum, Compost, and Foliar Application of Some Nanoparticles in Improving Some Chemical and Physical Properties of Soil and the Yield and Water Productivity of Faba Beans in Salt-Affected Soils (2023)
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NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning (2022)
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Early cascade rice irrigation shutoff (ECIS) conserves water: implications for cascade flood automation (2022)
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Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning (2022)
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Determining nitrogen deficiencies for maize using various remote sensing indices (2022)
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Assessment of Landsat-Based Evapotranspiration Using Weighing Lysimeters in the Texas High Plains (2020)
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Landsat Hourly Evapotranspiration Flux Assessment using Lysimeters for the Texas High Plains (2020)
Collaboration Network
Top Collaborators
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach
- Small Unmanned Aircraft Systems and Agro-Terrestrial Surveys Comparison for Generating Digital Elevation Surfaces for Irrigation and Precision Grading
- Early cascade rice irrigation shutoff (ECIS) conserves water: implications for cascade flood automation
- A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts
Showing 5 of 6 shared publications
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach
- Small Unmanned Aircraft Systems and Agro-Terrestrial Surveys Comparison for Generating Digital Elevation Surfaces for Irrigation and Precision Grading
- A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts
- A Maximal Overlap Discrete Wavelet Packet Transform Coupled with an LSTM Deep Learning Model for Improving Multilevel Groundwater Level Forecasts
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Small Unmanned Aircraft Systems and Agro-Terrestrial Surveys Comparison for Generating Digital Elevation Surfaces for Irrigation and Precision Grading
- Early cascade rice irrigation shutoff (ECIS) conserves water: implications for cascade flood automation
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach
- NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach
- A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts
- A Maximal Overlap Discrete Wavelet Packet Transform Coupled with an LSTM Deep Learning Model for Improving Multilevel Groundwater Level Forecasts
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach
- A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts
- A Maximal Overlap Discrete Wavelet Packet Transform Coupled with an LSTM Deep Learning Model for Improving Multilevel Groundwater Level Forecasts
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Effect of Gypsum, Compost, and Foliar Application of Some Nanoparticles in Improving Some Chemical and Physical Properties of Soil and the Yield and Water Productivity of Faba Beans in Salt-Affected Soils
- The combined impact of shallow groundwater and soil salinity on evapotranspiration using remote sensing in an agricultural alluvial setting
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
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