Fusion of multi-temporal paz and sentinel-1 data for crop classification

Busquier, Mario; Valcarce-Diñeiro, Rubén; Lopez-Sanchez, Juan M.; Plaza, Javier; Sánchez, Nilda; Arias-Pérez, Benjamín

Abstract

The accurate identification of crops is essential to help environmental sustainability and support agricultural policies. This study presents the use of a Spanish radar mission, PAZ, to classify agricultural areas with a very high spatial resolution. PAZ was recently launched, and it operates at X band, joining the synthetic aperture radar (SAR) constellation along with TerraSAR-X and TanDEM-X satellites. Owing to its novelty and its ability to classify crop areas (both taking individually its time series and blending with the Sentinel-1 series), it has been tested in an agricultural area of the central-western part of Spain during 2020. The random forest algorithm was selected to classify the time series under five alternatives of standalone/fused data. The map accuracy resulting from the PAZ series standalone was acceptable, but it highlighted the need for a denser time-series of data. The overall accuracy provided by eight PAZ images or by eight Sentinel-1 images was below 60%. The fusion of both sets of eight images improved the overall accuracy by more than 10%. In addition, the exploitation of the whole Sentinel-1 series, with many more observations (up to 40 in the same temporal window) improved the results, reaching an overall accuracy around 76%. This overall performance was similar to that obtained by the joint use of all the available images of the two frequency bands (C and X).

Citation

Busquier, M., Valcarce-Diñeiro, R., Lopez-Sanchez, J. M., Plaza, J., Sánchez, N., & Arias-Pérez, B. (2021). Fusion of multi-temporal paz and sentinel-1 data for crop classification. Remote Sensing, 13(19), Article 3195. https://doi.org/10.3390/rs13193915

• Journal Article Type: Article
• Acceptance Date: Sep 27, 2021
• Online Publication Date: Sep 30, 2021
• Publication Date: Oct 1, 2021
• Deposit Date: Nov 27, 2024
• Publicly Available Date: Nov 28, 2024
• Journal: Remote Sensing
• Electronic ISSN: 2072-4292
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 19
• Article Number: 3195
• DOI: https://doi.org/10.3390/rs13193915
• Keywords: Crop classification; Synthetic aperture radar; Fusion; Time series
• Public URL: https://hull-repository.worktribe.com/output/4716156