Biography
Dr Elsherbiny is a professor of Bio-system engineering at the National Authority for Remote Sensing and Space Sciences (NARSS), Egypt. His research interests include field irrigation and water relations, evapotranspiration, crop monitoring, drought, and climate change effects on agriculture. Dr. Elsherbiny obtained his MSc and PhD in Science from Ain Shams University, Egypt in 2008 and 2012, respectively.
Abstract
Remote sensing technologies have transformed agriculture management by providing a full set of instruments for precision and efficiency in farming techniques. This lecture analyzes the critical significance of RS in major elements of agricultural management, such as water monitoring, nutrient monitoring, pest and disease control, crop monitoring, yield calculation, and weather prediction. Weather forecasting using RS data provides useful insights into short- and long-term weather trends, allowing for preemptive risk management and adaptable agricultural techniques. Farmers may use weather forecasting to reduce risks, improve planting and harvesting dates, and reduce weather-related losses. Farmers and agricultural practitioners may acquire timely and spatially explicit data required for informed decision-making by integrating multiple RS platforms such as satellites, drones, and ground-based sensors. Remote sensing provides water monitoring capabilities that allow for the measurement of soil moisture levels, irrigation efficiency, and drought detection. This allows for better water resource management and increases crop resistance to water stress. Nutrient monitoring using RS techniques enables the evaluation of soil fertility, nutrient deficits, and crop nutrient absorption. Farmers may enhance crop nutrition by monitoring spectral signatures and vegetation indicators. RS is critical to pest and disease management because it allows for early identification and monitoring of insect infestations, disease outbreaks, and crop stress. This allows for more prompt interventions, lowering crop losses and the requirement for chemical inputs, boosting long-term pest control methods. Crop health, growth dynamics, and phenological phases may all be monitored in real time via remote sensing. Farmers may track crop growth, identify problem areas, and execute focused management techniques by monitoring vegetation vigor, biomass buildup, and canopy cover. production estimation using remote sensing-based models allows for more precise agricultural production predictions, which aids in market forecasting, resource allocation, and risk management. Farmers may improve yield projections, manage inputs, and increase profitability by combining remote sensing data with modern analytics. Remote sensing is a cornerstone of modern agricultural management, providing a comprehensive solution to the different issues that farmers encounter. Farmers may attain higher accuracy, efficiency, and sustainability in agricultural practices by integrating remote sensing technology with sophisticated analytics, contributing to food security and environmental stewardship.
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