Spatial interpolation using conditional generative adversarial neural networks

Spatial interpolation is a traditional geostatistical operation that aims at predicting the attribute values of unobserved locations given a sample of data defined on point supports. However, the continuity and heterogeneity underlying spatial data are too complex to be approximated by classic stati...

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Veröffentlicht in:	International journal of geographical information science : IJGIS Jg. 34; H. 4; S. 735 - 758
Hauptverfasser:	Zhu, Di, Cheng, Ximeng, Zhang, Fan, Yao, Xin, Gao, Yong, Liu, Yu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 02.04.2020 Taylor & Francis LLC
Schlagworte:	Artificial intelligence Coders Deep learning encoder-decoder Encoders-Decoders generative adversarial networks Geostatistics Heterogeneity Interpolation Machine learning Mathematical models Neural networks Spatial data Spatial interpolation spatial prediction Statistical analysis Statistical models
ISSN:	1365-8816, 1362-3087, 1365-8824
Online-Zugang:	Volltext
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