Research Papers
ACM SIGSPATIAL 2026 Call for Papers - Research Track
Submission link: https://easychair.org/conferences/?conf=acmsigspatial2026
Overview
The thirty-fourth ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2026 (ACM SIGSPATIAL 2026) will be held in Riverside, California, USA, in November 2026. The conference began in 1993 as a series of symposia and workshops to bring together researchers, developers, users, and practitioners on novel systems based on spatial data and knowledge, and foster interdisciplinary discussions and research across all aspects of spatial information systems. The conference provides a forum for original research contributions that cover all conceptual, design, and implementation aspects of geospatial data, ranging from applications to data storage and query processing to the Internet of Spatial Things and spatial AI. The conference is the premier annual event of the ACM Special Interest Group on Spatial Information (ACM SIGSPATIAL). Researchers, students, and practitioners are invited to submit original, unpublished research papers that are not under consideration for publication elsewhere.
Important Dates
- Abstract Submission:
Friday, May 22nd, 2026Friday, May 29th, 2026, 11:59 PM Pacific Time - Paper Submission:
Friday, May 29th, 2026Friday, June 5th, 2026, 11:59 PM Pacific Time - Notification of Accept/Reject: Wednesday, Aug 5th, 2026, 11:59 PM Pacific Time
- Camera-ready: Wednesday, August 19th, 2026, 11:59 PM Pacific Time
Research track contributions: two types of papers
There are two types of papers in the research track:
- Regular Research Papers
- Experiment, Benchmark & Experience Papers
1. Regular Research Papers
Papers about theory, models, and algorithms. These papers present original research on foundational concepts, such as novel models and algorithms for spatial computing. These papers are invited, where appropriate, to include a prototype implementation and evaluation that may include comparisons with alternate approaches. Example: a novel algorithm for complex query processing or a novel model of spatial causal inference.
Papers about systems. These papers describe the design, implementation, and empirical evaluation of a novel system, framework, or processing pipeline created to address a specific problem. It typically provides a detailed explanation of a real-world problem, the architecture, functionality, and performance of the system, and an evaluation that may include comparisons with alternate systems. Example: a platform for spatio-temporal data analysis in real-time.
2. Experiment, benchmark, and experience papers
Papers about experiments. These papers evaluate multiple existing solutions to a problem and, through extensive experimentation, offer novel insights through a comprehensive analysis of their strengths and weaknesses. Example: evaluating anomaly detection algorithms using various datasets.
Papers about benchmarks. These papers introduce new benchmarks for evaluating and comparing different techniques, systems, or algorithms. They provide a standardized reference point to guide experimental research and foster consistent evaluation practices. Example: benchmarking spatio-temporal causal analysis algorithms.
Papers about experiences. These papers provide insights, lessons learned, and real-world experiences from deploying existing systems. They focus on practical challenges and observations from real-world usage, which are crucial for understanding the limitations of existing solutions. All the co-authors of an experience paper can be from academia. Example: lessons learned from the deployment of a system for indoor tracking.
Topics of Interest
Spatial AI
- Generative AI for spatial reasoning and simulation
- Spatial and spatio-temporal foundation models
- Causal reasoning in space and time
- Spatial machine learning and explainability
- Privacy and ethics in spatial computing
- Spatial and spatio-temporal reasoning in robotics
- Agentic GeoAI
- Trustworthy and responsible GeoAI
- Spatial and spatio-temporal Retrieval Augmented Generation (RAG) Techniques
- Spatial representation learning, encoding, and grounding methods for multi-modal data
- Evaluation benchmarks for foundation models
- Safety, hallucination control, and uncertainty quantification in spatially grounded foundation models
Spatial Computing Systems and Big Spatial Data Infrastructure
- Spatial and spatio-temporal analysis
- Query processing and optimization
- Spatial data mining, pattern analysis and knowledge discovery
- Spatio-temporal data management
- Spatial decision support
- Spatial data quality and uncertainty
- Geo-entity linkage, geo-enrichment
- Distributed and parallel algorithms
- Geospatial architectures and middleware
- GPU and novel hardware solutions
- Cloud and edge spatial data platforms
- Spatial vector databases
- Spatial graph data management and analysis
- Unified relational/graph/vector architectures for spatial retrieval-augmented generation
Pervasive Spatial Computing and Internet of Spatial Things
- Localization and tracking indoors/outdoors
- Contact tracing
- Location-based services
- Spatio-temporal sensor networks
- Traffic telematics
- Mobile systems and vehicular ad hoc networks
- Edge spatial computing systems and on-device intelligence
- Virtual/Augmented/Mixed reality for spatial computing
- Spatial computing in autonomous vehicles
- Cyber-physical systems and their applications in spatial computing
Spatial Data Acquisition, Integration, and Processing
- Standardization and semantic interoperability
- Earth observation and satellite data processing
- Computational geometry and computer graphics
- Spatial scene understanding and spatial awareness in images and videos
- Spatial, geo-social and trajectory simulation
- Spatio-temporal stream processing
- Governance and cross-organization spatial data sharing
- Spatial knowledge graphs
- Multi-modal spatial computing and data fusion
- Space and planetary mapping
Spatial Search
- Geographic information retrieval
- Human-computer interaction and visualization for spatial systems
- Similarity searching
- Spatial data structures and algorithms
- Spatial modeling and reasoning
- Spatio-textual searching
- Natural language interfaces and conversational search over spatial data
Spatial Intelligence for Society
- Intelligent transportation and sustainable mobility
- Epidemiology and health
- Cyber and physical security
- Smart cities and spaces
- Urban data and planning
- Geospatial computer vision applications
- Location business intelligence
- Personalized geospatial recommendation systems
- Environmental, climate, and natural systems
- Agricultural, food, and water systems
- Defense, intelligence, and public safety
- Utilities and urban infrastructure
- Geo health and epidemiology
- Industrial applications
Quantum Spatial Computing and Technologies
- Quantum computing for spatial data and applications
- Hybrid quantum-classical pipelines for spatial computing applications
- Quantum simulations for spatial systems and phenomena
- Quantum machine learning for spatial applications
- Quantum-inspired spatial indexing and search
- Quantum spatial databases
- Quantum sensing for spatial data and applications
- GPS-free quantum navigation technologies
- Benchmarks and empirical studies for quantum technologies on spatial workloads
Digital Twins in Spatial Computing Systems
- Urban, regional, and planetary digital twins
- Earth systems digital twins for climate, hazards, hydrology, and Earth ecosystem dynamics
- Facility digital twins for buildings, campuses, utilities, and industrial assets
- Mobility digital twins for flows of people, vehicles, goods, and services
- Human-centric and socio-economic digital twins for human services, social systems, health systems, transportation systems, and livability.
- Digital twin platforms
Submission
Submission link: https://easychair.org/conferences/?conf=acmsigspatial2026
General information
- Regular Research Papers: up to 10 pages excluding references
- Experiment, Benchmark & Experience Papers: up to 10 pages excluding references
As for Regular Research Papers and Experiment, Benchmark & Experience papers: papers are limited to 10 pages (excluding references), with up to 2 additional pages after the references to be used for appendices. Submissions that do not follow the page limit requirements will be desk-rejected without technical reviews.
Paper titles. Experiment, Benchmark & Experience should contain their type as a suffix in the title. The suffix is [Experiment]. For example: 'Evaluating spatial navigation systems on Mars [Experiment]'. If the paper is accepted, the suffix will not be part of the camera-ready copy.
Authors. ACM SIGSPATIAL is a single-blind conference; therefore, the names and affiliations of the authors should be listed in the submitted version. The author list is considered final after the submission deadline, and no changes, including the author order, are allowed to accepted papers.
Poster Papers. Based on the reviewers' evaluations, the Program Committee may recommend that certain papers be accepted as 4-page (including references) short papers for poster presentation. Both full and short papers will appear in the conference proceedings. The length is based on the ACM two-column conference proceedings template.
Conflict, authorship, and content
ACM Policy on Authorship. Authors should review and follow the ACM Policy on Authorship, which includes guidelines on the use of generative AI software tools for manuscript writing. In particular, the authors are responsible for all submitted manuscripts and should disclose the use of AI software tools in the paper. Generative AI tools and technologies, such as ChatGPT, may not be listed as authors of an ACM-published work. The use of generative AI tools and technologies to create content is permitted but must be fully disclosed in the Work. For example, the authors could include the following statement in the Acknowledgements section of the Work: ChatGPT was utilized to generate sections of this Work, including text, tables, graphs, code, data, citations, etc. PC Chairs reserve the right to desk-reject a paper without review if the use of AI software tools is not marked appropriately.
ACM Policy on Conflict of Interest. As part of the submission, you will be asked to mark your conflict of interest with the Program Committee members. Authors should review the Conflict of Interest Policy for ACM Publications to decide if there is a conflict of interest. In summary, the following is a non-comprehensive list of examples of COI:
- All PhD advisors/advisees regardless of the graduation date.
- All current co-workers or a co-worker in the past 24 months. A co-worker is a person working at the same institution as one of the authors, whether or not they actively collaborate. Short-term affiliations, such as a summer internship or short visits, do not result in an institutional COI with all co-workers. However, the mentor and other collaborators are still marked.
- Any co-author of a research paper in the last 24 months, regardless of whether the paper was peer-reviewed or not, e.g., white papers or arXiv papers also count. Community papers that have a large number of authors and do not stem from a specific research project do not constitute a COI, e.g. the reports titled "Towards Mobility Data Science" and "Diversity and Inclusion Activities in Database Conferences: A 2021 Report" do not by themselves result in a COI.
- A research collaborator in the past 24 months, whether or not this collaboration resulted in a publication.
- Close friends or relatives.
When in doubt, please contact the Program Committee Chairs or mark any potential conflicts on the submission website and include a note explaining why you believe they should be flagged. The Program Committee Chairs will review them and decide how to use that information. PC Chairs reserve the right to desk-reject a paper without review if COIs are not marked appropriately.
Note on EasyChair: EasyChair does not have a mechanism to indicate that a paper has no COIs. If you confirm that there are no conflicts, then you do not need to submit the COI form.
ACM Policy on Inappropriate Content. ACM Publications cannot be used to propagate political or religious views or denigrate individuals or groups of people. See https://www.acm.org/publications/policies/inappropriate-content-policy
Formatting Templates. Manuscripts should be submitted in PDF format and formatted using the ACM templates available at http://www.acm.org/publications/proceedings-template. ACM SIGSPATIAL uses the Conference Proceedings Primary Article template with a two-column format for both reviewing and camera-ready versions. Do not use any software options, either in LaTeX commands or any other editors, that generate single-column manuscripts either for reviewing or camera-ready versions. Alterations to the template, especially to gain more space, will be grounds for desk rejection without further technical review.
All papers should be submitted through EasyChair using the following link: https://easychair.org/conferences/?conf=acmsigspatial2026
Accepted Papers, Registration and Presentation. Papers accepted for ACM SIGSPATIAL 2026 will be published in the ACM Digital Library under the Proceedings of the 34th ACM International Conference on Advances in Geographic Information Systems. Upon the paper acceptance, the contact author(s) will receive detailed instructions on how to prepare and submit the camera-ready copy of the accepted paper. Each accepted paper must have a separate paid author registration (i.e., an author cannot pay a single registration for more than one paper), and one author must attend the conference in person to present the accepted submission. Otherwise, the accepted submission will not appear in the conference proceedings or the ACM Digital Library version of the conference proceedings.
Important note on ACM OPEN
Starting January 1, 2026, ACM will fully transition to Open Access (https://libraries.acm.org/acmopen). All ACM publications, including those from ACM-sponsored conferences, will be 100% Open Access. To sustain this approach, ACM will charge Article Processing Charges (APCs) for certain types of manuscripts, listed on https://libraries.acm.org/acmopen/article-types. If the accepted paper has at least one author affiliated with an OPEN participating institution (see the complete list at https://libraries.acm.org/acmopen/open-participants), the paper’s APC is already covered, and the authors will not pay any extra charges. If none of the authors has such an affiliation, the other option is to pay the APC. To ease the transition in 2026, the ACM has implemented policies on waivers and discounts, available at https://www.acm.org/publications/policies/policy-on-open-access-apc-waivers-and-discounts. The 2026 discount guidelines state that articles where one of the named co-authors is an ACM or SIG Member, the subsidized rate is $250/article (down from the list price of $700), and for articles where none of the named co-authors is an ACM or SIG Member, the subsidized rate is $350/article (down from the list price of $1,000). For articles eligible for 50% geographic discounts, the discount will be applied to the applicable subsidized rate.
For the ACM SIGSPATIAL 2026 conference, SIGSPATIAL accepts and handles requests for waivers for authors who have financial hardship according to the ACM policies, accessible on https://www.acm.org/publications/policies/policy-on-discretionary-open-access-apc-waivers. Guidelines for submitting waiver requests will be released along with the camera-ready instructions.
Program Committee
Research Track PC Chairs
- Kyoung-Sook Kim, National Institute of Advanced Industrial Science and Technology (AIST)
- Amr Magdy, University of California, Riverside
- Moustafa Youssef, American University in Cairo
Research Track Senior PC Members
- Carola Wenk, Tulane University
- Yanjie Fu, Arizona State University
- Xun Zhou, Harbin Institute of Technology, Shenzhen
- Hsun-Ping Hsieh, National Cheng Kung University
- Ranga Raju Vatsavai, North Carolina State University
- Andreas Züfle, Emory University
- Muhammad Aamir Cheema, Monash University
- Yan Huang, Department of Computer Science and Engineering, University of North Texas
- Zhe Jiang, the University of Florida
- Chiara Renso, ISTI-CNR, Pisa, Italy
- Martin Werner, Technical University of Munich
- Mahmoud Sakr, ULB
- Raymond Chi-Wing Wong, The Hong Kong University of Science and Technology
- Peer Kröger, Christian-Albrechts-Universität zu Kiel
- Sanjay Madria, Missouri S & T
- Gabriel Ghinita, University of Massachusetts, Boston
- Walid Aref, Purdue University
- Emre Eftelioglu, Amazon
- Hirozumi Yamaguchi, Osaka University
- Yaron Kanza, AT&T Research
- W Randolph Franklin, Rensselaer Polytechnic Institute
- Mario Nascimento, University of Alberta
- Gao Cong, Nanyang Technological University
- Stephan Winter, The University of Melbourne
- Dieter Pfoser, George Mason University
- Lars Kulik, The University of Melbourne
- Matthias Schubert, LMU Munich
- Maria Luisa Damiani, University of Milan
- Matthias Renz, Christian-Albrechts-Universität zu Kiel
- Karine Zeitouni, University of Versailles-Saint-Quentin
- Simonas Saltenis, Vilnius University
- Goce Trajcevski, Iowa State University
- Flora D. Salim, University of New South Wales
- Liang Zhao, Emory University
- Kyriakos Mouratidis, Singapore Management University
- Yao-Yi Chiang, University of Minnesota
- Leila De Floriani, University of Maryland
- Alberto Belussi, University of Verona
- Heba Aly, Amazon
- Fusheng Wang, Stony Brook University
- Joon Heo, Yonsei University
- John Krumm, University of Southern California
Research Track PC Members
- Jia Yu, Washington State University
- Jan-Henrik Haunert, Universität Bonn
- Ioannis Kontopoulos, National Technical University of Athens, Greece
- Takuro Yonezawa, Nagoya University
- Jilin Hu, East China Normal University
- Yuxuan Liang, Hong Kong University of Science and Technology (Guangzhou)
- Yue Jiang, Nanyang Technological Unversity
- Gilles Dejaegere, Université libre de Bruxelles
- Dejun Teng, Shandong University
- Xu Teng, Esri
- Ibrahim Sabek, University of Southern California
- Fabio Pinelli, IMT Lucca
- Yinzhao Yan, Huawei
- Haitao Yuan, Nanyang Technological University
- Christophe Claramunt, Naval Academy Research Institute
- Song Wu, Aalborg University
- Zhangyu Wang, University of Maine
- Jianzhong Qi, The University of Melbourne
- Daichi Amagata, The University of Osaka
- Prem Prakash Jayaraman, Swinburne University of Technology
- Shengya Zhang, University of Minnesota
- Wei Li, Harbin Engineering University
- Lei Li, The Hong Kong University of Science and Technology (Guangzhou)
- Bruno Martins, IST and INESC-ID - Instituto Superior Técnico, University of Lisbon
- Jianqiu Xu, Nanjing University of Aeronautics and Astronautics
- Amilcar Soares, Linnaeus University
- Kostas Patroumpas, Information Management Systems Institute, Athena Research Center
- Michela Bertolotto, University College Dublin
- Harry Kai-Ho Chan, University of Sheffield
- Zaher Al Aghbari, University Of Sharjah
- Chiara Pugliese, IIT - CNR, Pisa, Italy
- Jiangneng Li, Nanyang Technological University
- Nicole Schneider, University of Maryland
- Hamada Rizk, Osaka University
- Demetris Zeinalipour, University of Cyprus
- Michael Mcguire, Towson University/Computer and Information Sciences
- Rui Zhu, School of Geographical Sciences, University of Bristol
- Viswanath Gunturi, University of Hull
- Takahiro Yabe, NYU
- Mengxuan Zhang, Australian National University
- Kwangsoo Yang, Florida Atlantic University
- Debraj De, Oak Ridge National Laboratory (ORNL)
- Betsy George, Oracle America
- Jianwu Wang, University of Maryland, Baltimore County
- Suining He, The University of Connecticut
- Guimu Guo, Rowan University
- Manos Papagelis, York University
- Mark Mckenney, Southern Illinois University Edwardsville
- Baris Kazar, ORACLE AMERICA INC
- Lin Yang, DeepMap
- Jalal Khalil, St. Cloud State University
- Yan Li, Amazon.com
- Xin Cao, The University of New South Wales
- Wenlu Wang, Texas A&M University - Corpus Christi
- Haiquan Chen, California State University Sacramento
- Majid Saeedan, University of California, Riverside
- Kevin Buchin, Technical University Dortmund
- Pei-Xuan Li, National Cheng Kung University
- Ashwin Shashidharan, Environmental Systems Research Institute
- Joon-Seok Kim, Emory University
- Qiang Zhu, University of Michigan - Dearborn
- Licia Amichi, ORNL
- Rodrigo Sasse David, Aalborg University
- Abdeltawab Hendawi, University of Rhode Island
- Hua Lu, Aalborg University
- Yanhua Li, Worcester Polytechnic Institute (WPI)
- Kanchan Chowdhury, Marquette University
- An-Min Wu, University of Southern California
- Samriddhi Singla, Meta Platforms Inc.
- Siqin Sisi Wang, University of Southern California
- Jose Macedo, Federal University of Ceara
- Rajasekar Karthik, Oak Ridge National Laboratory
- Huan Li, Zhejiang University
- Ahmed Mahmood, Google
- Mohamed Khalefa, SUNY OLD Westbury
- Dimitrios Skoutas, Athena Research Center
- Jin Soung Yoo, Purdue University Fort Wayne
- Antonios Karatzoglou, Microsoft
- Chrysovalantis Anastasiou, University of Southern California
- Dandan Lin, The Hong Kong University of Science and Technology
- Samira Alkaee Taleghan, University of Colorado Denver
- Mohammed Eunus Ali, Monash University
- Panagiotis Tampakis, University of Southern Denmark
- Akil Sevim, Teradata
- Jeff M. Phillips, University of Utah
- Wan D. Bae, Seattle University
- Yannick Wölker, Christian Albrechts University
- Cyril Ray, Arts et Metiers Institute of Technology, Ecole Navale, IRENav
- Fatme Hachem, Universita degli studi di milano
- Xin Zhang, Amazon AWS
- Asif Baba, University of North texas
- Shen-Shyang Ho, Rowan University
- Man Lung Yiu, The Hong Kong Polytechnic University
- Ki-Joune Li, Pusan National University
- Zhaonan Wang, New York University (NYU) Shanghai
- Clodoveu Davis, Universidade Federal de Minas Gerais
- Mirco Nanni, KDD-Lab ISTI-CNR Pisa
- Yiqun Xie, University of Maryland
- Yijun Lin, University of Minnesota, Twin Cities
- Jagannath Aryal, University of Melbourne
- Marco Mamei, university of modena and reggio emilia
- Mike Horhammer, Oracle Corporation
- Jia Zou, Arizona State University
- Hao Xue, Hong Kong University of Science and Technology (Guangzhou)
- Maryam Rahnemoonfar, Lehigh University
- Yongyi Liu, Oracle America
- Xueqin Chen, Sichuan University
- Ken Yiu
- Kristian Torp, Aalborg University
- Qiang Gao, Southwestern University of Finance and Economics
- Monika Sester, Institute of Cartography and Geoinformatics, LUH
- Jiachen Zhang, University of Southern California
- Vincent Oria, NJIT
- El Kindi Rezig, University of Utah
- Yongquan Hu, National University of Singapore
- Sergio Di Martino, University of Napoli “Federico II”
- Theodoros Chondrogiannis, Norwegian University of Science and Technology (NTNU)
- Ioannis Giannopoulos, TU Wien
- Farhana Choudhury, The University of Melbourne
- Sidi Wu, ETH Zurich
- James Haworth, University College London
- Levi John Wolf, University of Bristol
- Grant McKenzie, McGill University
- Jayant Gupta, UWT
- Chhaya Kulkarni, Towson University
- Mashaal Musleh, University of Minnesota
- Lorenz Hurni, ETH Zurich
- Yunfan Kang, University of Illinois Urbana-Champaign
- Sandro Martinelli Reia, George Mason University
- Roy Levin, Microsoft
- Taylor Oshan, University of Maryland, College Park
- Peter Kiefer, ETH Zurich
- Tahera Hossain, Assistant Professor, Nagoya University
- Nikolaos Koutroumanis, Archimedes AI Unit/Athena RC
- Yumeng Song, Aalborg University
- Maria Despoina Siampou, University of Southern California
- Chenxi Liu, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences
- Krzysztof Janowicz, University of Vienna, Austria
- Yafei Li, Zhengzhou University
- Nico Van de Weghe, Department of Geography, Ghent University
- Liwei Deng, Aalborg University
- Tsz Nam Chan, Shenzhen University
- Yunjun Gao, Zhejiang University
- Sijie Ruan, Beijing Institute of Technology
- Subhrasankha Dey, Aalto University
- Tin Vu, Microsoft
- Christos Doulkeridis, University of Piraeus
- Cy Zhang, Microsoft
- Youness Dehbi, Bonn University