First Demonstration of Space-Borne Polarization Coherence Tomography for Characterizing Hyrcanian Forest Structural Diversity

Structural diversity is recognized as a complementary aspect of biological and plays fundamental role in forest management, conservation, restoration. Hence, the assessment structural has become major effort primary international processes, dealing with biodiversity sustainable management. Because prohibitive costs associated ground measurements structure, despite their high accuracy, space-borne polarization coherence tomography (PCT) can introduce an alternative approach given its ability to provide vertical reflectivity profile spatiotemporal resolutions related detecting changes. In this study, for first time ever, potential PCT was evaluated broad-leaved Hyrcanian Iran over 308 circular sample plots area 0.1 ha. Two aspects horizontal structure diversity, including standard deviation diameter at breast height (σdbh) number trees (N), were predicted important characteristics wood production biomass estimation. addition, performance prediction algorithms, multiple linear regression (MLR), k-nearest neighbors (k-NN), random (RF), support vector (SVR) compared. We addressed issue temporal decorrelation utilizing single-pass TanDEM-X interferometer. The data acquired DEM mode single HH. Consequently, airborne laser scanning (ALS) used estimate initial values hv phase φ0. Fourier–Legendre series approximate relative each pixel. To link averaged within plot corresponding σdbh N, thirteen geometrical physical parameters defined (P1−P13). Leave-one-out cross validation (LOOCV) showed better k-NN than other algorithms predicting N. It resulted root mean square error (rRMSE) 32.80%, absolute (MAE) 4.69 cm, R2* 0.25 σdbh, whereas only 22% variation N explained using algorithm rRMSE 41.56%. This study revealed promising results even though accuracy still limited. entire framework characterizing possible effect scale necessary future studies.