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Tobler's First Law in GeoAI
Thursday, September 29, 2022, 11:00 AM - 12:00 PM PDT
Category: Webinars

Tobler's First Law in GeoAI

Presenter: Dr. Wenwen Li (Arizona State University)
Moderator: Dr. Yongmei Lu (Texas State University)

 

Abstract: GeoAI, or geospatial artificial intelligence, is powerful to solve complex geospatial problems. Leveraging recent breakthroughs in deep learning and advanced computing, GeoAI enables scalable processing and intelligent analysis of geospatial big data. A core issue is how to make AI integral to the geospatial science framework. This presentation will introduce a new GeoAI model that enables automated spatial object detection, especially of natural features, in a weakly supervised manner. It will also cover discussions about the enablement of spatially explicit machine learning by integrating Tobler’s First Law of Geography; as well as the generalizability of the GeoAI model, in detecting both manmade and natural features on the surface of the Earth and other planets.
 
A related paper with more background information can be found in: Li, W., Hsu, C. Y., & Hu, M. (2021). Tobler’s First Law in GeoAI: A spatially explicit deep learning model for terrain feature detection under weak supervision. Annals of the American Association of Geographers, 111(7), 1887-1905.
 
The first 100 free copies of the paper can be downloaded through links at (link 1 and link 2).
 
 
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