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In this paper, we evaluate the polarimetric sensitivity of multi-frequency synthetic aperture radars (SARs) for detecting landslide areas in forest-covered mountains. We tested L-band airborne and X-band spaceborne SARs, i.e. the airborne Polarimetric Interferometric SAR in L-band (Pi-SAR-L2), Terra SAR X, and Cosmo Skymed, at the Totsukawa-mura test site in Nara, Japan. We found that three parameters-the coherence of HH and VV, polarimetric entropy, and the power ratio of HH/HV-are very effective, especially with L-band SAR, for detecting land cover changes from a forest to a landslide. Results show that X-band SARs are less sensitive to landslide areas because the X-band penetrates less through a forest compared to the L-band.

The Japan Aerospace Exploration Agency (JAXA) has produced the world's first 10m resolution L-band SAR global mosaic datasets. These data sets were generated to monitor forest changes from the 1990s to present. SRTM-3 (90m resolution) DEM was used to correct the terrain-induced SAR intensity variations and the ortho-rectification.Both corrections were applied for geometric and radiometric calibration purposes. The data sets are useful to monitor the temporal forest cover and forest change, and were used to derive forest/non-forest information.

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The tremendous potential of ALOS-4/PALSAR-3 for further advancements in forest monitoring from local to global scales are discussed on the basis of the groundbreaking achievements made by its predecessor ALOS-2/PALSAR-2, the first long-term L-band SAR forest observation mission in history. The unprecedented seamless and frequent dual-polarization observation of the entire tropical forest belt between 2016 and 2022 has revolutionized the idea of global forest monitoring. In the upcoming ALOS-4 era, wide-area imaging with greatly improved spatial resolution and image quality at shorter revisit times will further boost the reliability for all kinds of forest remote sensing applications including forest classification, biomass estimation and deforestation detection.