Machine Intelligence for GeoAnalytics and Remote Sensing

About this event

The Machine Intelligence for GeoAnalytics and Remote Sensing (MIGARS) conference is an eminent event that explores the intersection of machine intelligence approaches, spatial analytics, and remote sensing technologies. With advancements in data acquisition and sensing platforms, the volume, variety, and veracity of data streams in remote sensing are increasingly challenging. MIGARS aims to tackle these challenges by facilitating the handling, processing, automating, and transforming of complex geo-data from multiple sources, including IoT devices and sensors, into clear, actionable insights for decision-making and planetary monitoring. This fourth edition of MIGARS will gather researchers, experts, and practitioners from various fields such as artificial intelligence, remote sensing, geosciences, climate change, and environmental research, all committed to advancing geospatial technologies and their applications.The conference is jointly organized by the Indian Institute of Space Science and Technology (IIST), the Digital University of Kerala, and Vasavi College of Engineering, with the venue set at the Digital University of Kerala in Trivandrum, India. The event will feature opportunities for authors to present their research, with additional emphasis on quality and originality through the MIGARS Young Researcher Award, which recognizes impactful contributions in Remote Sensing and Machine Learning from early-career researchers. Furthermore, outstanding papers will be invited to submit extended versions for publication in a special stream of IEEE GRSS journals. The conference has strict guidelines regarding the submission of manuscripts, prohibiting the use of content generated by large-scale AI systems, ensuring the integrity and quality of the research presented. Participants are encouraged to engage in collaborative discussions and explore the potential applications of intelligent computational approaches for geo-data-based solutions beneficial to society.