Spatial Statistics 2025: At the Dawn of AI

During the Spatial Statistics 2025 conference in Noordwijk, the Netherlands, specific attention will be given to the opportunities, including challenges to be addressed, that Artificial Intelligence (AI) opens up and how spatial statistics can be developed further with AI.

The latest developments in spatial statistics will be presented, emphasising their contributions at the dawn of AI, now and in the future. The optimal use of collected data, predicting in space and time, object recognition and segmentation, and transferability in the presence of spatial and temporal correlations are typical, but not exhaustive examples.

Comments from delegates of the 6^th Spatial Statistics Conference

“High quality of content and well thought out schedule and time for discussion through on-site lunches with poster sessions.”

“Great atmosphere, very collaborative and collegial.”

“I got the opportunity to meet and interact with some renowned experts in spatial statistics whom I have read and referenced during my Ph.D. study.”

Our society, atmosphere and environment are dynamic, and are continuously changing at many scales of time and space. A recent rapid development in society concerns the emergence of AI.

AI is supported by large numbers of available data, requiring statistical methods to handle these. Simultaneously, in the spatial domain, a large and important collection of spatial statistical methods and domain knowledge are being developed to help address the demands of society. The number and variety of data sources are increasing with the advent of more and more satellite and aircraft sensors, ground stations, surveys, mobile devices, and internet sources, recording human, climatic and environmental processes. These spatial and spatio-temporal data require to be transformed into meaningful information and both spatial statistics and AI are complementary in achieving this.

Artificial Intelligence has its roots in computer science. In the past, it has resulted in artificial neural networks including the multi-layer perceptron, while more recently, we recognize how deep learning has resulted in the development of convolutional neural networks and the transformer. Now, natural language processing has brought about a profound shift in thinking and opened great opportunities for research.

Spatial statistics, with its roots in probability theory and stochastic processes, has much to bring to the AI table. Moreover, the development of Statistical Learning in a spatial context has built a bridge towards spatial big data.

At the dawn of AI, therefore, spatial statistics should play a major role in the development and application of AI and, at the same time, AI can benefit the development of spatial statistics.

Conference topics

We are accepting oral and poster abstracts on the topics listed below. They should be submitted using the online abstract submission system opens in new tab/window.

Deadline: 24 January 2025

Methods

• Spatial deep learning

• Spatial statistical learning

• Neural networks in space

• Large language models in space

• Natural language processing for spatial challenges

• Spatio/temporal modeling of points and objects

• Causality in space and time

• Modeling and predicting of extremes

• Space-time statistics: geostatistics, point patterns, estimation methods, large dimensions

• Discrete spatial variation

• Spatial and spatio/temporal variability and dependence

• Stochastic geometry, tessellation, point processes, random sets

Applications

• Environment: soil, water, atmosphere

• Interface of neural computing and spatial/spatio-temporal statistics

• Climate system modeling and observations

• Health e.g. epidemiology, geohealth and global health

• Spatially-explicit ecological models

• Plant and animal epidemiology

• Quantifying the spatial extent of hazards and risk

• Crime, poverty, liveability mapping

Deadlines

Abstract submission deadline: 24 January 2025

Workshop proposal deadline: 24 January 2025

Author notification deadline: 21 March 2025

Author registration deadline: 2 May 2025

Early booking deadline: 2 May 2025

Supporting publication

Special Issue

A special conference issue of Spatial Statistics: At the Dawn of AI will be produced. Further information will be available soon.

Previous conference Special Issues

Spatial Statistics: Climate and the Environment (2024) https://www.sciencedirect.com/special-issue/10Z1BLBW7ZD opens in new tab/window

Spatial Statistics: Towards Spatial Data Science (2021) https://www.sciencedirect.com/journal/spatial-statistics/vol/42/suppl/C opens in new tab/window

Spatial Statistics: One world, one health (2017) www.sciencedirect.com/journal/spatial-statistics/vol/28 opens in new tab/window

Spatial Statistics Avignon: Emerging Patterns (2015) www.sciencedirect.com/journal/spatial-statistics/vol/18/part/PA opens in new tab/window

Revealing Intricacies in Spatial and Spatio-Temporal Data: Papers from the Spatial Statistics 2013 Conference (2013) www.sciencedirect.com/journal/spatial-statistics/vol/9/suppl/C opens in new tab/window

Spatial Statistics for Mapping the Environment (2011) www.sciencedirect.com/journal/international-journal-of-applied-earth-observation-and-geoinformation/vol/22/suppl/C opens in new tab/window

Related Conference

https://rss.org.uk/training-events/conference-2025/ opens in new tab/window

Marketing Material

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Previous Events

Spatial Statistics 2023: Climate and the Environment 18 - 21 July 2023 | University of Colorado, Boulder, USA

Conference topics

Methods

• Space-time statistics, e.g. geostatistics, point patterns, estimation methods, large dimensions

• Spatial deep learning

• Inverse modeling

• Modeling of extremes

• Stochastic geometry, tesselation, point processes, random sets

• Causal statistical modeling

• Trajectory/movement modeling

Applications

• Climate system modeling and observations

• Spatially-Explicit Ecological Models

• Health e.g. epidemiology, geohealth and global health

• Air, Water and Soil spatio-temporal variability

• Plant and animal epidemiology

• Quantifying the spatial extent of hazards and risk

• Crime and poverty mapping

• Space/time econometrics

• Interface of Neural Computing and Spatial/Spatio-Temporal Statistics

• Inferring Movement and Behavior from Telemetry

Spatial Statistics 2019: Towards Spatial Data Science 10 – 13 July 2019 | Sitges, Spain

Conference Topics

Methods

• Space-time statistics, e.g. geostatistics, point patterns, estimation methods, large dimensions

• New spatial data sources, e.g. social media, Google, citizen science, crowd source maps

• Stochastic geometry, tesselation, point processes, random sets

• Causal statistical modeling

• Trajectory/movement modeling

• Predictive modelling

• Spatial data quality and uncertainty

With these methods being applied in a range of relevant domains. For the theme of the conference, we particularly invite contributions in:

Applications

• Image analyses, e.g. satellite images

• Traffic and transport

• Global change

• Ecology, e.g. dispersion, migration, colonisation and invasion of species

• Plant and animal epidemiology, e.g. emerging epidemics

• Hazards, disasters and risks, e.g. outbreaks, risk mapping

• Crime and poverty mapping

• Health e.g. epidemiology, geohealth and global health

• Spatial econometrics

Spatial Statistics: One world, one health 4-7 July 2017 | Lancaster University, UK

Conference Topics

• Space-time statistics

• Models for point processes

• Lattice models

• Geostatistics

• Copulas in space and time

• Spatial extremes

• Change-point analysis

• Estimation methods

• Issues of scale: upscaling and downscaling methodology

• Stochastic geometry, random sets and stereology

• Causal statistical modeling

• Image analysis (e.g. satellite sensor image time-series, DNA data, brain imaging)

• Predictive modelling

• Spatial data quality and uncertainty

• New spatial data sources (e.g. social media, Google, citizen science, crowd sourced data)

• Large dimensional big spatial data

With these methods being applied in a range of relevant domains. For the theme of the conference, we particularly invite contributions in:

• Statistical aspects of epidemiology

• Geo-Health and One Health

• Plant and animal diseases

• Health and Global change

• Zoonotic and vector-borne diseases (e.g. emerging epidemics)

• Hazards, disasters and risks (e.g. outbreaks, risk mapping)

• Ecology (e.g. dispersion, migration, colonisation and invasion of species)

• Spatial econometrics

Spatial Statistics Avignon: Emerging Patterns 9-12 June 2015 | Avignon, France

Conference Topics

• Space-time statistics (e.g. point patterns models, estimation methods, large dimensions, scale issues)

• Spatial data quality and uncertainty

• Parameter estimation in PDEs

• Stochastic geometry, tesselation, point processes, random sets

• Spatial econometrics

• New spatial data sources (e.g. big, data, social media, Google, citizen science, crowd source maps)

• Image analyses (e.g. satellite images time series, DNA data, nano particles, nervous systems)

• Predictive modelling

• Tipping points (e.g. sea-level rise, socio-economic shifts)

• Hazards, disasters and risks (e.g. tsunamis, earthquakes, landslides, air pollution levels)

• Global change (e.g. stochastic weather generators)

• Health, medical and epidemiology

• Plant and animal epidemiology (emerging epidemics)

• Ecology (e.g. dispersion, migration, colonisation and invasion of species)

Spatial Statistics 2013 Conference

Spatial Statistics for Mapping the Environment (2011)