Bridging Sustainability and Environmental Impact Assessment: Multi-Scale Bioindication and Remote Sensing for Pollution Monitoring in Agroecosystems

Persistent environmental contaminants pose a substantial threat to agricultural ecosystems, necessitating robust methodologies for evaluation and mitigation of their effects. This study establishes a direct correlation between environmental impact assessment and sustainable agricultural management, showing the feasibility of using multi-scale bioindication and remote sensing technology to effectively monitor the impact of soil pollution in agricultural ecosystems. The key values of this research lie in the ability of the described approach to integrate advanced proximal/remote sensing and in situ analyses to assess the effects of soil contamination on bioindicators, providing a comprehensive framework for evaluating environmental stressors. The proposed methodology was tested on maize ( Zea mays L.) and employs unmanned aerial vehicle-based multi/hyperspectral and thermal imaging to detect vegetation stress indicators such as normalized difference vegetation index and thermal anomalies. The interdisciplinary approach adopted in this research significantly enhances the value of the study by not only focusing on isolated results but also validating the entire methodological workflow. This cross-disciplinary integration ensures that the workflow retains its relevance across various environmental scenarios, enriching the results’ applicability and providing a robust framework for ongoing studies. The research objective of this work was achieved through experimental tests on soils contaminated with heavy metals and organic pollutants exceeding regulatory thresholds that revealed distinct spectral and thermal signatures, demonstrating the efficacy of integrated sensing for detailed environmental assessment. The findings underscore the role of bioindicators as pivotal tools for bridging environmental monitoring and sustainability by providing actionable insights into pollutant impacts and their cascading effects on ecosystems and human health. By equipping stakeholders with precise contamination detection tools, this study aims to provide a methodological approach to expand environmental impact assessment frameworks, supporting sustainable decision-making and risk management. These methodologies contribute to aligning agricultural practices with broader sustainability objectives, ensuring resilient food systems and ecosystem health.