Artificial intelligence studies in cartography: a review and synthesis of methods, applications, and ethics
The past decade has witnessed the rapid development of geospatial artificial intelligence
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …
(GeoAI) primarily due to the ground-breaking achievements in deep learning and machine …
A graph neural network framework for spatial geodemographic classification
S De Sabbata, P Liu - International Journal of Geographical …, 2023 - Taylor & Francis
Geodemographic classifications are exceptional tools for geographic analysis, business and
policy-making, providing an overview of the socio-demographic structure of a region by …
policy-making, providing an overview of the socio-demographic structure of a region by …
A time-series-based model to detect homogeneous regions of residents' dynamic living habits
H Wang, H Zhang, N Shen, F Zhao, H Zhu… - Geo-spatial …, 2024 - Taylor & Francis
The identification of homogeneous regions representing the dynamic living habits of
residents has long been a central focus in human activity research. Although extensive …
residents has long been a central focus in human activity research. Although extensive …
A multi-hierarchical method to extract spatial network structures from large-scale origin-destination flow data
Extracting spatial network structure (SNS) from large-scale origin-destination flow data is an
important approach for understanding interregional association patterns and interaction …
important approach for understanding interregional association patterns and interaction …
Adding attention to the neural ordinary differential equation for spatio-temporal prediction
Explainable spatio-temporal prediction gains attraction in the development of geospatial
artificial intelligence. The neural ordinal differential equation (NODE) emerges as a new …
artificial intelligence. The neural ordinal differential equation (NODE) emerges as a new …
Mining the spatial distribution pattern of the typical fast-food industry based on point-of-interest data: The case study of Hangzhou, China
Y Zhou, X Shen, C Wang, Y Liao, J Li - ISPRS International Journal of Geo …, 2022 - mdpi.com
There is a Chinese proverb which states “Where there are Shaxian Snacks, there are
generally Lanzhou Ramen nearby”. This proverb reflects the characteristics of spatial …
generally Lanzhou Ramen nearby”. This proverb reflects the characteristics of spatial …
GeoAI-enhanced community detection on spatial networks with graph deep learning
Spatial networks are useful for modeling geographic phenomena where spatial interaction
plays an important role. To analyze the spatial networks and their internal structures, graph …
plays an important role. To analyze the spatial networks and their internal structures, graph …
A multivariate hierarchical regionalization method to discovering spatiotemporal patterns
In GIScience, the regionalization method is widely used for geographical data mining,
spatiotemporal pattern discovery, and regional studies. An ideal regionalization method …
spatiotemporal pattern discovery, and regional studies. An ideal regionalization method …
Multivariate analysis in data science for the geospatial distribution of the breast cancer mortality rate in Colombia
This research is framed in the area of biomathematics and contributes to the epidemiological
surveillance entities in Colombia to clarify how breast cancer mortality rate (BCM) is spatially …
surveillance entities in Colombia to clarify how breast cancer mortality rate (BCM) is spatially …
Spatially constrained statistical approach for determining the optimal number of regions in regionalization
Determining the optimal number of regions is a challenging issue in regionalization.
Although cluster validity indices developed for non-spatial clustering have been used to …
Although cluster validity indices developed for non-spatial clustering have been used to …