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• W2600584518 abstract "Multi-frequency SAR has the potential to improve classification accuracy for land cover classification compared to single frequency SAR. Within the context of Copernicus the main SAR contributing mission is Sentinel-1, which is a C-band SAR. Utilizing frequencies from third party missions, such as TerraSAR-X (X-band) and ALOS-2 PALSAR (L-band), the information from multiple sensors can be combined for higher classification accuracy. Two sites are investigated, namely a semi-arid study site in Tanzania and a forested study site in the Democratic Republic of the Congo (DRC). The classification accuracy of using L, C, X, LC, LX, CX and LCX frequency combinations are compared. Additional data layers are inter-channel ratios and the mean texture measure for selected window sizes. The land cover classes chosen are bare, burnt, dense trees and sparse vegetation for the Tanzania study site, with bare, burnt, dense trees, sparse vegetation, thinner dense trees, water and settlements classified in the DRC study site. The classifier used is the standard decision tree, with optical RapidEye imagery first classified to act as the response layer in the classification model. For both study sites the highest overall classification accuracies are given using either the LX or LCX combination at 53–54%, with much higher individual class accuracies of 70–80% for especially dense trees, water and bare (Tanzania) land cover classes." @default.
• W2600584518 created "2017-04-07" @default.
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• W2600584518 date "2017-03-25" @default.
• W2600584518 modified "2023-10-17" @default.
• W2600584518 title "Multi‐Frequency SAR Applications for Land Cover Classification Within Copernicus Downstream Services" @default.
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• W2600584518 doi "https://doi.org/10.1002/9781118793787.ch5" @default.
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