Bridging optical and SAR satellite image time series via contrastive feature extraction for crop classification

Author:

Yuan Yuan,Lin Lei,Zhou Zeng-Guang,Jiang Houjun,Liu Qingshan

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference61 articles.

1. SAR Observations and Modeling of the C-Band Backscatter Variability Due to Multiscale Geometry and Soil-Moisture;Beaudoin;IEEE Trans. Geosci. Remote Sens.,1990

2. Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany;Blickensdorfer,2022

3. Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data;Cai,2020

4. Campos-Taberner, M., Garcia-Haro, F.J., Camps-Valls, G., Grau-Muedra, G., Nutini, F., Busetto, L., Katsantonis, D., Stavrakoudis, D., Minakou, C., Gatti, L., Barbieri, M., Holecz, F., Stroppiana, D., Boschetti, M., 2017. Exploitation of SAR and Optical Sentinel Data to Detect Rice Crop and Estimate Seasonal Dynamics of Leaf Area Index. Remote Sens. 9.

5. Self-Supervised Change Detection in Multiview Remote Sensing Images;Chen,2022

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