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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Bibliographic Details
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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Summary: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.
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ISSN:0143-1161
1366-5901
1366-5901
DOI:10.1080/01431161.2019.1569791