Call for Chapters: Geospatial AI for Disaster Risk Intelligence and Monitoring

Editors

Walid Al-Shaar, Novum Research and Innovation Group (NovumRIG), Lebanon
Mohammad Al Shaar, Novum Research and Innovation Group (NovumRIG), Lebanon

Call for Chapters

Proposals Submission Deadline: June 21, 2026
 Full Chapters Due: October 4, 2026
 Submission Date: October 4, 2026

Introduction

The convergence of artificial intelligence (AI) and geospatial technologies is fundamentally reshaping how humanity monitors, assesses, and responds to environmental and societal risks. In an era marked by accelerating climate extremes, increasingly frequent natural disasters, and complex human-induced hazards, the limitations of conventional risk management frameworks have become critically apparent. GeoAI, defined as the integration of AI with geographic information systems (GIS), remote sensing, and spatial analytics, enables near real-time hazard detection, predictive risk modelling, automated damage assessment, and intelligent decision support across every phase of the disaster risk management cycle. Yet comprehensive literature bridging the technical dimensions of GeoAI with practical applications across multiple hazard types and diverse geographical contexts remains limited. This edited volume addresses these gaps by bringing together cutting-edge methodologies, global case studies, and interdisciplinary perspectives spanning the full disaster risk management continuum, while critically examining the ethical and governance dimensions that must accompany technological advancement in this field.

Objective

This edited volume fills a critical gap in the existing literature by providing a comprehensive, interdisciplinary examination of GeoAI applications across the full disaster risk management continuum. While current research has advanced in isolated technical domains, no single reference work systematically integrates these developments into a unified, operationally grounded framework. This volume addresses that shortcoming by connecting cutting-edge methodologies, including digital twins, federated learning, and explainable AI, with disaster science, urban planning, and public policy. By presenting diverse global case studies and interrogating ethical and governance dimensions that the field has thus far addressed insufficiently, the volume bridges the gap between academic inquiry and operational practice, equipping researchers, policymakers, and practitioners with the conceptual frameworks and applied tools needed to advance the next generation of intelligent and anticipatory risk management systems.

Target Audience

**Target Audience** This volume is geared towards a broad yet specialized readership spanning academia, practice, and policy. It will benefit graduate students and early-career researchers seeking a comprehensive entry point into GeoAI and disaster risk science, as well as established academics working at the intersection of geospatial technologies, remote sensing, and environmental hazards. Practitioners in emergency management, urban planning, and humanitarian response will find actionable frameworks directly applicable to their operational contexts. Policymakers and institutional decision-makers concerned with disaster risk reduction, climate adaptation, and technology governance will equally benefit from the volume's critical examination of ethical and equity dimensions in GeoAI deployment.

Recommended Topics

Topics Covered in This Volume - Foundations of GeoAI and its role in disaster risk reduction - Machine learning and deep learning techniques for hazard mapping - Geospatial data infrastructures and big data analytics - Satellite imagery analysis for multi-hazard detection - IoT sensor networks and edge computing for real-time monitoring - Social media analytics and crowdsourced data for early warning - Machine learning for vulnerability and exposure mapping - Multi-hazard risk assessment and ensemble modelling - Agent-based models integrated with AI for evacuation planning - Automated damage assessment using deep learning and SAR imagery - Resource allocation optimization using reinforcement learning - Natural language processing for emergency communication analysis - Drone-based rapid assessment and 3D reconstruction - Post-disaster recovery monitoring using multi-temporal analysis - Resilience metrics and adaptive capacity assessment - Digital twins for urban disaster resilience simulation - Federated learning for distributed risk monitoring - Blockchain for disaster data integrity and supply chain management - Extended reality (XR) for crisis training and simulation - Algorithmic bias and fairness in risk assessment - Privacy, surveillance, and data ethics in disaster contexts - Digital divide and equitable access to GeoAI technologies - Indigenous knowledge integration and decolonial approaches - Regulatory frameworks and governance structures for GeoAI

Submission Procedure

Researchers and practitioners are invited to submit on or before June 21, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by July 5, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by October 4, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Geospatial AI for Disaster Risk Intelligence and Monitoring. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

June 21, 2026: Proposal Submission Deadline
July 5, 2026: Notification of Acceptance
October 4, 2026: Full Chapter Submission
December 6, 2026: Review Results Returned
January 17, 2027: Final Acceptance Notification
January 31, 2027: Final Chapter Submission

Inquiries

Dr. Walid Al-Shaar Novum Research and Innovation Group (NovumRIG) walid-al-shaar@hotmail.com Dr. Mohammad Al Shaar Novum Research and Innovation Group (NovumRIG) mohammadalshaar1@gmail.com
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