We investigated the sensitivity to vegetation cover type of active (PALSAR) and passive (SMAP) freeze/thaw (F/T) classification. We also used F/T classification from high-resolution PALSAR data (30 m) to follow the evolution of frozen and thawed soil states obtained from an adaptive algorithm with low-resolution SMAP data (36 km). We used PALSAR and SMAP scenes acquired from June 2015 to January 2017 over the Tursujuq National Park (Umiujaq, Quebec, Canada). A new F/T algorithm with a specific reference threshold under each vegetation type (shrub, grass, lichen, wetland, and bare land) is proposed to classify PALSAR pixels. The validation of the PALSAR F/T classification with soil temperature at ∼5 cm depth revealed a greater overall accuracy (> 80%), with horizontal transmitted and vertical received (HV) thresholds. The PALSAR F/T classification shows that a SMAP pixel is classified as frozen when more than 50% of its area is frozen at the surface. We confirmed the sensitivity to vegetation cover type of passive and active F/T classification with L-band sensor.
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28 December 2021
Landscape Freeze/Thaw Mapping from Active and Passive Microwave Earth Observations Over the Tursujuq National Park, Quebec, Canada
Cheima Touati,
Tahiana Ratsimbazafy,
Jimmy Poulin,
Monique Bernier,
Saeid Homayouni,
Ralf Ludwig
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Ecoscience
Vol. 28 • No. 3-4
December 2021
Vol. 28 • No. 3-4
December 2021
algorithmes gel/dégel
freeze/thaw algorithms
Nunavik
Nunavik
PALSAR
PALSAR
SMAP