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- A'Campo, WillekeStockholms universitet,Institutionen för naturgeografi (author)
Arctic Tundra Land Cover Classification on the Beaufort Coast Using the Kennaugh Element Framework on Dual-Polarimetric TerraSAR-X Imagery
- Article/chapterEnglish2021
Publisher, publication year, extent ...
- 2021-11-25
- MDPI AG,2021
- printrdacarrier
Numbers
- LIBRIS-ID:oai:DiVA.org:su-201276
- https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-201276URI
- https://doi.org/10.3390/rs13234780DOI
Supplementary language notes
- Language:English
- Summary in:English
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Notes
- Arctic tundra landscapes are highly complex and are rapidly changing due to the warming climate. Datasets that document the spatial and temporal variability of the landscape are needed to monitor the rapid changes. Synthetic Aperture Radar (SAR) imagery is specifically suitable for monitoring the Arctic, as SAR, unlike optical remote sensing, can provide time series regardless of weather and illumination conditions. This study examines the potential of seasonal backscatter mechanisms in Arctic tundra environments for improving land cover classification purposes by using a time series of HH/HV TerraSAR-X (TSX) imagery. A Random Forest (RF) classification was applied on multi-temporal Sigma Nought intensity and multi-temporal Kennaugh matrix element data. The backscatter analysis revealed clear differences in the polarimetric response of water, soil, and vegetation, while backscatter signal variations within different vegetation classes were more nuanced. The RF models showed that land cover classes could be distinguished with 92.4% accuracy for the Kennaugh element data, compared to 57.7% accuracy for the Sigma Nought intensity data. Texture predictors, while improving the classification accuracy on the one hand, degraded the spatial resolution of the land cover product. The Kennaugh elements derived from TSX winter acquisitions were most important for the RF model, followed by the Kennaugh elements derived from summer and autumn acquisitions. The results of this study demonstrate that multi-temporal Kennaugh elements derived from dual-polarized X-band imagery are a powerful tool for Arctic tundra land cover mapping.
Subject headings and genre
- TEKNIK OCH TEKNOLOGIER Naturresursteknik hsv//swe
- ENGINEERING AND TECHNOLOGY Environmental Engineering hsv//eng
- Synthetic Aperture Radar (SAR)
- polarimetry
- Kennaugh Element Framework (KEF)
- TerraSAR-X (TSX)
- Arctic
- tundra
- Random Forest (RF)
Added entries (persons, corporate bodies, meetings, titles ...)
- Bartsch, Annett (author)
- Roth, Achim (author)
- Wendleder, Anna (author)
- Martin, Victoria S. (author)
- Durstewitz, LucaStockholms universitet,Institutionen för naturgeografi(Swepub:su)ludu0718 (author)
- Lodi, Rachele (author)
- Wagner, JuliaStockholms universitet,Institutionen för naturgeografi(Swepub:su)juwa8499 (author)
- Hugelius, GustafStockholms universitet,Institutionen för naturgeografi(Swepub:su)chuge (author)
- Stockholms universitetInstitutionen för naturgeografi (creator_code:org_t)
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- In:Remote Sensing: MDPI AG13:232072-4292
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