GeoAI in the US Geological Survey for topographic mapping

被引：5

作者：

Usery, E. Lynn ^{[1
]}

Arundel, Samantha T. ^{[1
]}

Shavers, Ethan ^{[1
]}

Stanislawski, Lawrence ^{[1
]}

Thiem, Philip ^{[1
]}

Varanka, Dalia ^{[1
]}

机构：

[1] US Geol Survey, Ctr Excellence Geospatial Informat Sci, Rolla, MO 65401 USA

来源：

TRANSACTIONS IN GIS | 2022年 / 26卷 / 01期

关键词：

EXTRACTION; RESOLUTION; CYBERGIS; NET; PERFORMANCE; PATTERNS; MODELS; FLOOD; GIS;

D O I：

10.1111/tgis.12830

中图分类号：

P9 [自然地理学]; K9 [地理];

学科分类号：

0705 ; 070501 ;

摘要：

Geospatial artificial intelligence (GeoAI) can be defined broadly as the application of artificial intelligence methods and techniques to geospatial data, processes, models, and applications. The application of these methods to topographic data and phenomena is a focus of research in the US Geological Survey (USGS). Specifically, the USGS has researched and developed applications in terrain feature extraction, hydrographic network extraction, and semantic modeling. This article is a documentation of the recent work and current state of research and development. The article helps define the accomplishments and directions of research and applications in fields of GeoAI for topographic mapping within the USGS and more broadly.

引用

页码：25 / 40

页数：16

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