Landscape Freeze/Thaw Mapping from Active and Passive Microwave Earth Observations Over the Tursujuq National Park, Quebec, Canada

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 l...

Full description

Bibliographic Details
Published in:Écoscience
Main Authors: Cheima Touati, Tahiana Ratsimbazafy, Jimmy Poulin, Monique Bernier, Saeid Homayouni, Ralf Ludwig
Format: Text
Language:English
Published: Centre d'études nordiques, Université Laval 2021
Subjects:
Online Access:https://doi.org/10.1080/11956860.2021.1969790
Description
Summary: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.