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Technological Monitoring and Management in Hydrophyte-Based Heavy Metal Stress Management
Abstract
Remote sensing has emerged as a pivotal technology in the monitoring and management of heavy metal contamination in various environments. By utilizing satellite imagery, aerial photography, and advanced sensor technologies, researchers can effectively assess the spatial distribution and concentration of heavy metals in soil, water, and vegetation. This paper explores the various remote sensing techniques employed in heavy metal monitoring, highlighting their applications in detecting environmental stressors and assessing the health of ecosystems. Through the integration of remote sensing data with geographic information systems (GIS) and machine learning algorithms, it is possible to develop predictive models that facilitate timely interventions and remediation strategies. The findings underscore the importance of remote sensing as a non-invasive and efficient approach to environmental monitoring, providing valuable insights for policymakers and environmental managers in their efforts to combat heavy metal pollution.
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