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Remote Sens. 2016, 8(5), 362; doi:10.3390/rs8050362

Improved Early Crop Type Identification By Joint Use of High Temporal Resolution SAR And Optical Image Time Series

CESBIO - UMR 5126, 18 avenue Edouard Belin, 31401 Toulouse CEDEX 9, France
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Academic Editors: Clement Atzberger and Prasad S. Thenkabail
Received: 5 January 2016 / Revised: 10 April 2016 / Accepted: 14 April 2016 / Published: 26 April 2016
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Abstract

High temporal and spatial resolution optical image time series have been proven efficient for crop type mapping at the end of the agricultural season. However, due to cloud cover and image availability, crop identification earlier in the season is difficult. The recent availability of high temporal and spatial resolution SAR image time series, opens the possibility of improving early crop type mapping. This paper studies the impact of such SAR image time series when used in complement of optical imagery. The pertinent SAR image features, the optimal working resolution, the effect of speckle filtering and the use of temporal gap-filling of the optical image time series are assessed. SAR image time series as those provided by the Sentinel-1 satellites allow significant improvements in terms of land cover classification, both in terms of accuracy at the end of the season and for early crop identification. Haralik textures (Entropy, Inertia), the polarization ratio and the local mean together with the VV imagery were found to be the most pertinent features. Working at at 10 m resolution and using speckle filtering yield better results than other configurations. Finally it was shown that the use of SAR imagery allows to use optical data without gap-filling yielding results which are equivalent to the use of gap-filling in the case of perfect cloud screening, and better results in the case of cloud screening errors. View Full-Text
Keywords: crop type mapping; land-cover; satellite image time series; Sentinel-1; Sentinel-2; Landsat 8; Random Forests crop type mapping; land-cover; satellite image time series; Sentinel-1; Sentinel-2; Landsat 8; Random Forests
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Inglada, J.; Vincent, A.; Arias, M.; Marais-Sicre, C. Improved Early Crop Type Identification By Joint Use of High Temporal Resolution SAR And Optical Image Time Series. Remote Sens. 2016, 8, 362.

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