Ahmed A. Hashem Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
Arkansas State University
faculty
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Biography and Research Information
OverviewAI-generated summary
Ahmed A. Hashem's research focuses on the application of remote sensing technologies and advanced computational methods to address challenges in agriculture and hydrology. His work investigates the use of unmanned aerial vehicles (UAVs) and deep learning for detecting intra-field variations in crop yield, such as in rice cultivation, and for predicting plant phenotypes. Hashem also studies the impact of environmental factors like soil salinity and groundwater levels on agricultural productivity and water use, employing remote sensing to quantify evapotranspiration in agricultural settings. His research extends to optimizing water resource management, including the design of infiltration galleries for aquifer recharge using simulation-optimization approaches. Hashem has published on topics including nitrogen deficiency determination in maize and the effects of soil amendments and nanoparticles on crop yield and soil properties. He has a total of 17 publications, with an h-index of 6 and 196 citations. His key collaborators at Arkansas State University include Emily S. Bellis, John W. Nowlin, Fared Farag, and Jason Causey, with whom he has co-authored multiple publications.
Metrics
- h-index: 6
- Publications: 17
- Citations: 196
Selected Publications
- A maximal overlap discrete wavelet packet transform coupled with an LSTM deep learning model for improving multilevel groundwater level forecasts (2024) DOI
- Optimizing the quantity of recharge water into a sedimentary aquifer through infiltration galleries using a surrogate assisted coupled simulation–optimization approach (2024) DOI
- Small Unmanned Aircraft Systems and Agro-Terrestrial Surveys Comparison for Generating Digital Elevation Surfaces for Irrigation and Precision Grading (2023) DOI
- A Maximal Overlap Discrete Wavelet Packet Transform Coupled with an LSTM Deep Learning Model for Improving Multilevel Groundwater Level Forecasts (2023) DOI
- The combined impact of shallow groundwater and soil salinity on evapotranspiration using remote sensing in an agricultural alluvial setting (2023) DOI
- 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) DOI
- NAPPN Annual Conference Abstract: Characterizing Rice Nitrogen Use Phenotypes from Multitemporal UAV Imagery with Manifold Learning (2022) DOI
- Early cascade rice irrigation shutoff (ECIS) conserves water: implications for cascade flood automation (2022) DOI
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning (2022) DOI
- Determining nitrogen deficiencies for maize using various remote sensing indices (2022) DOI
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