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

Ghamisi, P. and Rasti, B. and Yokoya, N. and Wang, Q. and Hofle, B. and Bruzzone, L. and Bovolo, F. and Chi, M. and Anders, K. and Gloaguen, R. and Atkinson, P.M. and Benediktsson, J.A. (2019) Multisource and multitemporal data fusion in remote sensing:A comprehensive review of the state of the art. IEEE Geoscience and Remote Sensing Magazine, 7 (1). pp. 6-39. ISSN 2473-2397

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Abstract

The recent, sharp increase in the availability of data captured by different sensors, combined with their considerable heterogeneity, poses a serious challenge for the effective and efficient processing of remotely sensed data. Such an increase in remote sensing and ancillary data sets, however, opens up the possibility of utilizing multimodal data sets in a joint manner to further improve the performance of the processing approaches with respect to applications at hand. Multisource data fusion has, therefore, received enormous attention from researchers worldwide for a wide variety of applications. Moreover, thanks to the revisit capability of several.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Geoscience and Remote Sensing Magazine
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ID Code:
132809
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Deposited On:
29 Apr 2019 16:15
Refereed?:
Yes
Published?:
Published
Last Modified:
20 Sep 2020 05:29