Topical Collection on "Ecological Informatics: The Movement to Make the Planet Greener and Cleaner"

By integrating environmental research and cutting-edge computer technology, the emerging area of ecological informatics aims to increase global sustainability. This interdisciplinary rule addresses current ecological concerns by utilizing technological developments and data-driven insights. The importance of climate change and environmental degradation is increasing, highlighting the need for creative approaches to efficiently monitor, simulate, and manage ecosystems. Information technology must be integrated with ecological principles in order to promote sustainable operations and reduce ecological footprints. Ecological informatics provides an integrated approach to environmental management by using sensors, satellites, and Internet of Things devices to collect data in real time. Subsequently, machine learning, artificial intelligence, and advanced analytics are used to discover patterns and predictions from environmental data. Decision support systems, which support environmental managers and policymakers to make prompt, well-informed decisions, are made possible by these insights.

Ecological informatics integrates multiple technologies to improve environmental information and management. This includes tracking biodiversity, vegetation health, and land cover by remote sensing with satellites and drones. GIS facilitates spatial analysis, which is used in habitat mapping, resource management, and conservation planning. Some the tasks that machine learning algorithms help with include species identification, anomaly detection, and ecological forecasting. Big data analytics is also essential for examining massive datasets and identifying significant patterns and trends for ecological research and conservation initiatives. Using comprehensive environmental data, ecological informatics' precision conservation concentrates conservation efforts. Citizen science encourages community involvement in environmental monitoring by including individuals in data collecting through online and mobile apps. Blockchain technology increases environmental transaction and certification transparency, boosting conservation activities to be transparent and regulatory compliance.

In ecological informatics, predictive modeling enhances the accuracy of prediction in ecological changes. Incorporating with policy employs data-driven insights to influence environmental policies effectively. Global collaboration promotes international partnerships aimed at comprehensive ecosystem management, ensuring coordinated efforts in environmental conservation and sustainability initiatives worldwide. Despite its potential, ecological informatics has several challenges include ensuring data quality, and integrating various sources, addressing technological accessibility to bridge digital divides in accessing ecological technologies, and promoting interdisciplinary collaboration among technology, ecology, and policy. To overcome these challenges, standardizing data through protocols for collection, sharing, and analysis, capacity building via training programs for communities and stakeholders, and advocating for policy alignment that supports data-driven environmental management. However, ecological informatics plays a crucial role in advancing scientific cooperation and technology innovation to achieve environmental sustainability.

Topics of interest for the special issue include, but are not limited to, the following:

Integration of Information Technology and Ecological Principles for Sustainable Operations.
Role of Ecological Informatics in Addressing Climate Change and Environmental Degradation.
Application of Machine Learning and Artificial Intelligence in Ecological Data Analysis.
Challenges and Opportunities in Scaling Up Ecological Informatics Solutions.
Ethical Considerations in the Use of Ecological Data and Technology.
Applications of Satellite and Drone Remote Sensing in Biodiversity Monitoring.
Employing Big Data Analytics for Pattern Recognition and Trend Analysis in Ecological Research.
Utilization of Blockchain Technology in Environmental Transparency and Certification.
Analysis of Remote Sensing and GIS in Vegetation Health Monitoring.
Optimizing Machine Learning Algorithms for Anomaly Detection in Ecological Systems.

Strategies to Overcome Challenges in ecological informatics.

Collection Editor(s)

Keywords:

Ecological informatics
Environment
Ecomat
Greener Earth
Ecology
Geography

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Member of ALPSP

Topical Collection on "Ecological Informatics: The Movement to Make the Planet Greener and Cleaner"