Crop type classification using a combination of optical and radar remote sensing data: a review

Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor techn...

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Published in:	International journal of remote sensing Vol. 40; no. 17; pp. 6553 - 6595
Main Authors:	Orynbaikyzy, Aiym, Gessner, Ursula, Conrad, Christopher
Format:	Journal Article
Language:	English
Published:	London Taylor & Francis 02.09.2019 Taylor & Francis Ltd
Subjects:	Classification Crops Data Data integration Food security Imagery Mapping Monitoring Multisensor fusion Radar Radar data Radar imaging Remote sensing Satellite data Satellite imagery Sensors Spaceborne remote sensing Vegetation vegetation structure
ISSN:	0143-1161, 1366-5901, 1366-5901
Online Access:	Get full text
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Abstract	Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor technologies and processing capabilities, the potential of multi-source satellite imagery has gained increasing attention. The combination of optical and radar data is particularly promising in the context of crop type classification as it allows explaining the advantages of both sensor types with respect to e.g. vegetation structure and biochemical properties. This review article gives a comprehensive overview of studies on crop type classification using optical and radar data fusion approaches. A structured review of fusion approaches, classification strategies and potential for mapping specific crop types is provided. Finally, the partially untapped potential of radar-optical fusion approaches, research gaps and challenges for upcoming future studies are highlighted and discussed.
AbstractList	Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor technologies and processing capabilities, the potential of multi-source satellite imagery has gained increasing attention. The combination of optical and radar data is particularly promising in the context of crop type classification as it allows explaining the advantages of both sensor types with respect to e.g. vegetation structure and biochemical properties. This review article gives a comprehensive overview of studies on crop type classification using optical and radar data fusion approaches. A structured review of fusion approaches, classification strategies and potential for mapping specific crop types is provided. Finally, the partially untapped potential of radar-optical fusion approaches, research gaps and challenges for upcoming future studies are highlighted and discussed.
Author	Orynbaikyzy, Aiym Gessner, Ursula Conrad, Christopher
Author_xml	– sequence: 1 givenname: Aiym surname: Orynbaikyzy fullname: Orynbaikyzy, Aiym email: aiym.orynbaikyzy@dlr.de organization: German Aerospace Center (DLR), German Remote Sensing Data Center (DFD) – sequence: 2 givenname: Ursula surname: Gessner fullname: Gessner, Ursula organization: German Aerospace Center (DLR), German Remote Sensing Data Center (DFD) – sequence: 3 givenname: Christopher surname: Conrad fullname: Conrad, Christopher organization: University of Halle
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Snippet	Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years,...
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SubjectTerms	Classification Crops Data Data integration Food security Imagery Mapping Monitoring Multisensor fusion Radar Radar data Radar imaging Remote sensing Satellite data Satellite imagery Sensors Spaceborne remote sensing Vegetation vegetation structure
Title	Crop type classification using a combination of optical and radar remote sensing data: a review
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