Multisource and multitemporal data fusion in remote sensing: A comprehensive review of the state of the art

IEEE Geoscience and Remote Sensing Magazine

Volumn 7, Issue 1, 2019, Pages 6-39

  Ghamisi, Pedram ^a   Rasti, Behnood ^b   Yokoya, Naoto ^c   Wang, Qunming ^d   Hofle, Bernhard ^e   Bruzzone, Lorenzo ^f   Bovolo, Francesca ^g   Chi, Mingmin ^h   Anders, Katharina ^e   Gloaguen, Richard ^a   Atkinson, Peter M ⁱ   Benediktsson, Jon Atli ^b  

^a INSTITUTE OF ION BEAM PHYSICS AND MATERIALS RESEARCH   (Germany)

^b UNIVERSITY OF ICELAND   (Iceland)

^c Disaster Resilience Science Team   (Japan)

^d TONGJI UNIVERSITY   (China)

^e UNIVERSITY OF HEIDELBERG   (Germany)

^f UNIVERSITY OF TRENTO   (Italy)

^g FONDAZIONE BRUNO KESSLER   (Italy)

^h FUDAN UNIVERSITY   (China)

ⁱ QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DATA FUSION;

ANCILLARY DATA; DATA SET; MULTI-MODAL DATA; MULTI-TEMPORAL DATA; MULTISOURCE DATA; REMOTE SENSING DATA; REMOTE-SENSING; REMOTELY SENSED DATA; SHARP INCREASE; STATE OF THE ART;

REMOTE SENSING;

DATA ASSIMILATION; DATA INTERPRETATION; DATA INVERSION; HETEROGENEITY; REMOTE SENSING; RESEARCH WORK;

EID: 85063456875     PISSN: 24732397     EISSN: 21686831     Source Type: Journal    
DOI: 10.1109/MGRS.2018.2890023     Document Type: Review

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