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Crop classification with multitemporal polarimetric SAR data

Professor Shaun Quegan (1), J. Gomez-Dans(1) , M. C. Gonzalez-Sampedro(2) , Dr Ir. Dirk H. Hoekman(3) , Dr Thuy Le Toan(4) , and Dr Henning Skriver(5)

(1) University of Sheffield, Hicks Building, Hounsfield Rd, Sheffield S3 7RH, United Kingdom
(2) Faculty of Physics, Dr Moliner 50, E-46100 Burjassot, Valencia, Spain
(3) Wageningen Agricultural University, Nieuwe Kanaal 11, 6709 PA Wageningen, Netherlands
(4) CESBIO, 18 ave. Edouard Belin, 31401 Toulouse, France
(5) Technical University of Denmark, Building 348, DK-2800 Lyngby, Denmark

Abstract

Multitemporal measurements gathered by EMISAR over the Foulum (Jutland) test site and AirSAR over the Wageningen test site provide an unrivalled opportunity to examine the factors affecting classification of northern European agricultural crops using both polarimetric and multitemporal information. Data analysis, guided by physical principles, has been used to investigate those polarimetric features most adapted to separating different classes of crops (with the emphasis on C band data). This has led to a hierarchical approach in which broad classes (spring vs winter crops) are successively subdivided into more specific classes using the most appropriate polarimetric features. While the overall ordering and rationale of the hierarchy is determined by the physics, hence is inherently transferable between different regions, the scheme increasingly relies on statistical methods to fix the decision boundaries, thus allowing adaptivity to local conditions. Because an underlying principle is exploitation of the prevalent scattering mechanisms, the behaviour and structure of the scheme is very dependent on the temporal evolution of the crop state. The performance of the approach will be demonstrated using both of the airborne datasets.

 

Full paper

 

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