ID: 1478
Presenting Author: Maryam Forghaniallahabadi
Session: 581 - Experiences in enhancing communication through the application of AI in IA
Status: pending
Systematic review of AI and digital tools in Environmental Assessment: effects on data quality and trust; maps uses and risks; urges transparency, strong verification, and secure data.
The rise of digital technologies is transforming Environmental Assessment (EA), enabling continuous monitoring and interactive communication of environmental impacts. However, the reliability of these advancements critically depends on the quality and integrity of underlying data. This systematic literature review examines how Artificial Intelligence (AI) and other digital tools influence data quality, integrity, and trustworthiness in the EA processes e.g. monitoring. Using the PRISMA methodology and NVivo-assisted thematic analysis of 63 peer-reviewed studies, four key application domains emerged: (1) predictive modelling and simulation, (2) automated data collection and real-time processing, (3) decision-support systems for impact evaluation, and (4) interactive digital platforms for communicating progress. To analyse these applications further, the review adopts four conceptual dimensions: socio-technical systems theory, to explore the interaction between digital tools and institutional practices; responsible innovation, to assess ethical and inclusive use of AI for environmental monitoring; environmental governance, to evaluate how digitalization affects transparency and accountability; and digital transformation, to understand the implications for data-driven decision-making. The findings reveal both opportunities and risks: to explore how data integrity i.e. through robust verification mechanisms, transparent algorithms, and secure data infrastructures is essential for credible and actionable impact assessments.
Maryam Forghaniallahabadi, PhD researcher in Environment and Sustainability at the University of Dundee, explores digital tools, data integrity, and smart spatial planning in environmental assessment.