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Título
Fusion of Multi-Temporal PAZ and Sentinel-1 Data for Crop Classification
Autor(es)
Palabras clave
Crop classification
Synthetic aperture radar
Fusion
Time series
Radar
Cultivos
Clasificación
Clasificación UNESCO
2506.16 Teledetección (Geología)
3103.06 Cultivos de Campo
Fecha de publicación
2021
Editor
MDPI
Citación
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). https://doi.org/10.3390/RS13193915
Resumen
[EN] 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).
URI
DOI
10.3390/rs13193915
Versión del editor
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Patrocinador
The authors would like to thank to INTA-PAZ Science Team for providing the PAZ data in the framework of AO-001-015 project