Artificial Intelligence for Multisource Geospatial Information

doi:10.3390/books978-3-0365-6386-2

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Artificial Intelligence for Multisource Geospatial Information

Edited by

January 2023

254 pages

ISBN978-3-0365-6387-9 (Hardback)
ISBN978-3-0365-6386-2 (PDF)

https://doi.org/10.3390/books978-3-0365-6386-2

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This book is a reprint of the Special Issue Artificial Intelligence for Multisource Geospatial Information that was published in

Computer Science & Mathematics

Environmental & Earth Sciences

Summary

This reprint collects 10 original research contributions published in the Special Issue entitled “Artificial Intelligence for Multisource Geospatial Information” of the ISPRS International Journal of Geo-Information. The focus is on different methods of Geospatial Artificial Intelligence (GeoAI) based on deep learning using different network architectures, clustering, soft computing, and semantic approaches. They are proposed to deal with a variety of Geospatial Big Data (GBD), such as georeferenced texts and photos in social networks, remote sensing images, cartographic maps, multidimensional geo databases, metadata in spatial data infrastructures, and for different tasks, such as for multisource georeferenced text integration and geodata flexible querying, for social sensing by applying sentiment analysis, clustering and geo analysis, for segmentation of roads, clouds and snow, and for detection of small targets and people on the streets.

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Hardback

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Keywords

geosemantics; implicit semantics; formal semantics; powerful semantics; satellite image; semantic segmentation; encoder–decoder; CNN; TH-1; cloud and snow detection; label quality; street crime; people on the street; streetscape; Baidu Street View image; spatial lag negative binomial regression; deep learning; convolutional neural network; backbone network; target detection; remote sensing images; segmentation; high resolution; transformer; deep learning; OLAP; fuzzy SOLAP-based framework; fuzzy spatiotemporal queries; fuzzy spatiotemporal predictive query; fuzzy query visualization; machine learning; classification; LiDAR; 3D point cloud; urban trees; image feature vector; clustering; Siamese Network; automatic classification of tourist photos; deep learning model; Arabic tweets; COVID-19 pandemic; sentiment analysis; social data mining; spatio-temporal correlation; off-line integration of geo-tagged data sets; data sets about public places; soft integration methodology; effective soft integration through a stand-along tool; n/a