Forest Canopy Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) Technology Based on Full-Polarized ALOS/PALSAR Data

Forest canopy height is a basic metric characterizing forest growth and carbon sink capacity. Based on full-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) data, this study used Polarimetric Interferometric (PolInSAR) technology to estimate height. In total the four methods of differential DEM (digital elevation model) algorithm, coherent amplitude phase-amplitude algorithm three-stage random volume over ground (RVoG_3) were proposed obtain their accuracy was compared in consideration impacts coherence coefficient range slope levels. The influence statistical window size analyzed improve estimation accuracy. On basis traditional algorithms, time decoherence performed ALOS/PALSAR data by introducing change rate Landsat NDVI (Normalized Difference Vegetation Index). direction calculated based SRTM (Shuttle Topography Mission) then introduced into s-RVoG (sloped-Random Volume Ground) model optimize results indicated that underestimated significantly, while overestimated After removing systematic coherence, overestimation RVoG_3 restrained, absolute error decreased from 23.68 m 4.86 m. With further decoherence, determination increased 0.2439. introduction slope, shows improvement RVoG model. Our will provide reference for appropriate selection optimization using synthetic aperture radar (SAR) ecosystem monitoring management.