Ocena możliwości wykorzystania satelitarnych danych optycznych i radarowych do identyfikacji typów użytków rolnych

Abstract

Fusion of satellite data from different sources is a technique commonly used in studies focused on land cover and land use. Combining images of various spectral bands allows to increase objects differentiation and thereby improve overall classification accuracy. In this study, I focused on crops maps creation using integrated optical and radar data. Landsat 8 multispectral data from OLI sensor and Sentinel-1A SAR ( Synthetic Aperture Radar ) data were applied here. The study was performed for a test area of the Żywiec Basin, which is a part of the Polish Carpathians. The advantage of this small, agricultural region was that it is covered by a mosaic of different-size cultivated fields. I tested six methods of satellite data integration ( IHS, HPF, PCA, Brovey, Ehlers and wavelet transforms ) and two classification algorithms ( Support Vector Machines and Random Forest ). The results demonstrated that the use of integrated optical and radar data is effective for crops classification – the highest overall accuracy achieved in this study was equal to 87.9% and was obtained for Random Forest classification and Ehlers fusion.