Data Set Information:
This big data set is a fused bi-temporal optical-radar data for cropland classification. The images were collected by RapidEye satellites (optical) and the Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system (Radar) over an agricultural region near Winnipeg, Manitoba, Canada on 2012.
There are 2 * 49 radar features and 2 * 38 optical features for two dates: 05 and 14 July 2012.
Seven crop type classes exist for this data set as follows: 1-Corn; 2-Peas; 3- Canola; 4-Soybeans; 5- Oats; 6- Wheat; and 7-Broadleaf.
175 attributes including:
2- f1 to f49:Polarimetric features on 05 July 2012;
3- f50 to f98:Polarimetric features on 14 July 2012;
4- f99 to f136:Optical features on 05 July 2012;
5- f137 to f174:Optical features on 14 July 2012;
label:crop type class
For more information about these attributes, please refer to relevant papers.
1- Khosravi, I., & Alavipanah, S. K. (2019). A random forest-based framework for crop mapping using temporal, spectral, textural and polarimetric observations. International Journal of Remote Sensing, 40(18), 7221-7251.a€?
2- Khosravi, I., et al. (2018). MSMD: maximum separability and minimum dependency feature selection for cropland classification from optical and radar data. International Journal of Remote Sensing, 39(8), 2159-2176.a€?
These papers can be downloaded from [Web link]
I'd like to present my acknowledgment to the JPL NASA for the PolSAR images, and the SMAPVEX 2012 team, the Agriculture and Agri-Food Canada, for providing the PolSAR and the optical images.
Please cite my relevant papers.
Dr. Iman Khosravi,
Department of Remote Sensing & GIS, Faculty of Geography, University of Tehran, Tehran, I.R. Iran, 1417853933
E-Mail: iman.khosravi '@' ut.ac.ir