GeoIndustry @ ACM SIGSPATIAL 2025

About

With the rapid revolution and increasing availability of geospatial data not only academia, but also industry aspire for solutions to further leverage the big data and AI technologies to create new products, improve efficiencies and provide novel solutions to existing problems. However, despite the widespread interest, there is a lack of communication between the researchers in academia and industry. This limits advancements at the intersection and causes redundant or siloed efforts on both sides. Academia often has limited access to the rich and potentially useful big geospatial datasets and related real problems. In addition, the solutions proposed by the academic researchers alone are usually developed for a small scale with many assumptions, leaving a less-attended gap between methods and their applicability at scale for industrial applications. On the other hand, the industry has the data and problems at scale. However, since existing research is often not on par, industry researchers may lean towards using the traditional approaches that are developed without spatial consideration (e.g., ignoring spatial and temporal dependencies), and project teams have limited time and efforts to dive deep on the development of novel techniques that can be high-risk, but high-potential. This opens up opportunities for synergistic collaboration between industrial practitioners and academic researchers. The goal of this workshop is to offer a forum to exchange thoughts and ideas between industry and academia and reduce those siloed efforts by exploring synergies between the researchers on both sides. We envision that the collaborations, via invited and regular talks, can not only accelerate the research-to-impact cycle, but also foster workforce development for future geospatial researchers.

Organization Committee

Program Chairs

Heba Aly (Amazon)
Emre Eftelioglu (Amazon)
Song Gao (University of Wisconsin-Madison)
Yan Li (Amazon)
Jinmeng Rao (Google DeepMind)
Yiqun Xie (University of Maryland)

Program Committee

Mingquan Chen (Google)	Jayant Gupta (Oracle)
Yan Li (Amazon)	Chenxi Lin (PAII Inc)
Hongxu Ma (Google DeepMind)	Gengchen Mai (UT Austin)
Guang Wang (Florida State University)	Nemin Wu (University of Georgia)

Webmaster

Zhihao Wang (University of Maryland)

Schedule

Monday November 3, 2025 - Minneapolis, Georgia, USA

Time	Title
08:00 - 08:10	Opening Remarks
08:10 - 09:00	[Keynote Talk] Wherobots, The Spatial Intelligence Cloud for Data ETL, Analytics and AI at Planetary Scale Speaker: Jia Yu, Co-founder of Wherobots
09:00 - 09:15	Decentralized Trajectory Matching for Revealing Unauthorized Stalking by Bluetooth Trackers Ben Galon, Yaron Kanza and Eliyahu Safra
09:15 - 09:30	Generating Synthetic Populations Without Borders: A Geographically Independent Approach Sedar Olmez, Maxim Smilovitskiy, Iris Fermin and Sven van den Berghe
09:30 - 09:45	LocaGen: Low-Overhead Indoor Localization Through Spatial Augmentation Abdelrahman Abdelmotlb, Abdallah Taman, Sherif Mostafa and Moustafa Youssef
09:45 - 10:00	Analysis of segregation in human movements through POI co-occurrence networks based on connected car data Haruki Sato, Yukihisa Fujita and Fujio Toriumi
10:00 - 10:15	NeuroMobi: User-Independent Human Mobility Analysis using Brain Signals Tony Gerges, Yahia Alkaranshawy, Sherif Mostafa and Moustafa Youssef
10:15 - 10:45	Coffee Break
10:45 - 11:00	Geo-enrichment in a Data Lakehouse: Exploring Challenges and Opportunities Maria Luisa Damiani, Venkata Sudheer Siddabattula, Fatima Hachem, Marco Mesiti, Matteo Leo and Giampiero Rosa
11:00 - 11:15	From Point Clouds to Forest Analytics: libTTS, a Practical Toolkit for the Geoindustry Xin Xu, Federico Iuricich, John Armston and Leila De Floriani
11:15 - 11:30	AI Hazard Finder: Real-Time Extraction of Time, Location, and Type for Global Hazards Armin Soltan, Marcus Chuaunsu, Alberto Martinez, Pourya Fallahi, Ray Shirkhodaei and Joseph Green
11:30 - 11:45	Grid Attention Transformer (GAT): Attention Mechanisms in Grid-Based Transformers for Vegetation Risk Analysis. Gyanko Yussif, David Lagomasino, Emi Uchida and Abdeltawab Hendawi
11:45 - 12:00	Anomaly Detection for Locating Abandoned Oil and Gas Wells Using ResNet models William Thomas, Caixia Wang and Ibrahim Adeniran
12:00 - 14:00	Lunch
14:00 - 14:50	[Keynote Talk] Beyond RGB: Unlocking Multi-Spectral Vision with Gemini Speaker: Ganesh Mallya, Google
14:50 - 15:05	Few-shot Vision-language Prompt Tuning of VLMs for On-road Object Detection Minsoo Choi, Ravi Garg, Mohamed Moustafa, Tarun Bhatia and Amber Roy Chowdhury
15:05 - 15:20	Evaluating Geospatial Reasoning Capabilities in Large Language Models: A Benchmark on Geometry Classification, Topological Relations and Direction Estimation Yu Chin Huang, Yuhan Ji and Song Gao
15:20 - 15:35	Characterizing the Effectiveness of DINOv2 as an Off-the-Shelf Foundation Model for Earth Monitoring Tasks: Preliminary Results Ruichen Wang, Cooper Li, Sophia Hou, Alexander Lu, Zhihao Wang, Xiaowei Jia and Yiqun Xie
15:35 - 15:50	Street View for Whom? An Initial Examination of Google Street View's Urban Coverage and Socioeconomic Indicators in the US Zeyu Wang, Yingchao Jian, Adam Visokay, Don MacKenzie and Jon Froehlich
15:50 - 16:20	Coffee Break
16:20 - 16:35	GBA-UBF : A Large-Scale and Fine-Grained Building Function Classification Dataset in the Greater Bay Area Chunsong Chen, Yichen Hou, Huan Chen, Junlin Li, Rong Fu, Qiushen Lai, Ting Han and Yiping Chen
16:35 - 16:50	Edge Length Loss for Improved Building Polygon Extraction Kuanren Qian and Mohamed Moustafa
16:50 - 17:05	A Framework to Optimize Shelf Space Allocations for Physical Stores Yuchen Luo, Zhen Li, Gianluca Grilli, Bruno Lopez-Videla, Xiaoyi Gu and James Domingo
17:05 - 17:20	Optimization of Beef Noodle Shop Layout in Lanzhou City Based on Accessibility Analysis Xiaoxiao Guo, Wenda Wang, Shaohua Wang, Hao Wang, Chang Liu and Jingyi Zhou
17:20 - 18:00	Panel Discussion and Closing Remarks

Keynote Talk

Wherobots, The Spatial Intelligence Cloud for Data ETL, Analytics and AI at Planetary Scale

Speaker: Jia Yu, Co-founder of Wherobots

The explosion of geospatial data from satellites, sensors, and connected devices has created unprecedented opportunities and challenges for turning planetary scale data into actionable intelligence. This talk will introduce Wherobots, the Spatial Intelligence Cloud built for large scale data ETL, analytics, and AI. Powered by WherobotsDB, a cloud-native spatial data lakehouse based on open standards, and WherobotsAI, a platform for raster inference and geospatial foundation models, Wherobots enables organizations to build and operationalize spatial intelligence workflows 20× faster and at a fraction of the cost of traditional systems.

Beyond RGB: Unlocking Multi-Spectral Vision with Gemini

Speaker: Ganesh Mallya, Google

Multi-spectral imagery plays a crucial role in diverse Remote Sensing applications including land-use classification, environmental monitoring and urban planning. These images are widely adopted because their additional spectral bands correlate strongly with physical materials on the ground, such as ice, water, and vegetation. This allows for more accurate identification, and their public availability from missions, such as Sentinel-2 and Landsat, only adds to their value. Currently, the automatic analysis of such data is predominantly managed through machine learning models specifically trained for multi-spectral input, which are costly to train and support. Furthermore, although providing a lot of utility for Remote Sensing, such additional inputs cannot be used with powerful generalist large multimodal models, which are capable of solving many visual problems, but are not able to understand specialized multi-spectral signals. To address this, we propose a training-free approach which introduces new multi-spectral data in a Zero-Shot-only mode, as inputs to generalist multimodal models, trained on RGB-only inputs. Our approach leverages the multimodal models' understanding of the visual space, and proposes to adapt to inputs to that space, and to inject domain-specific information as instructions into the model. We exemplify this idea with the Gemini2.5 model and observe strong Zero-Shot performance gains of the approach on popular Remote Sensing benchmarks for land cover and land use classification and demonstrate the easy adaptability of Gemini2.5 to new inputs. These results highlight the potential for geospatial professionals, working with non-standard specialized inputs, to easily leverage powerful multimodal models, such as Gemini2.5, to accelerate their work, benefiting from their rich reasoning and contextual capabilities, grounded in the specialized sensor data.

Call For Papers (PDF version)

The workshop seeks high-quality regular (8-10 pages) and short (4 pages) papers that have not been published in other academic outlets and are not concurrently under peer review. Interested participants should submit a paper in the ACM format. Once accepted, at least one author is required to register for the workshop and the ACM SIGSPATIAL conference, as well as attend the workshop to present the accepted work which will then appear in the ACM Digital Library.

The topics include but are not limited to (in the context of industrial or related problems, such as delivery, routing, recommendation, mapping, resource allocation, and more):

Applications of AI
Big Data systems
Geospatial AI foundation models
Problems and benchmark datasets
Machine learning and deep learning
Computer vision and earth observation
Generative models and simulation
Map generation techniques
Heterogeneous data integration and analysis
Small data learning approaches
Citizen science and data collection
Spatial query processing
Spatial data management and integration
Ethical issues in geospatial data and research
Perspectives on the future of geospatial data and research
Emerging topics and trends

Important Dates

Submission deadline

August 30 September 6, 2025 (anywhere on earth)

Author notification

September 21, 2025 (anywhere on earth)

Workshop date

November 3, 2025

Submission site

https://easychair.org/conferences/?conf=geoindustry2025

GeoIndustry @ ACM SIGSPATIAL 2025
The 4th International Workshop on Spatial Big Data and AI for Industrial Applications

Monday November 3, 2025, Minneapolis, Minnesota