Evaluating the Sensitivity of Polarimetric Features Related to Rotation Domain and Mapping Chinese Fir AGB Using Quad-Polarimetric SAR Images

Abstract

Unaffected by cloud cover and solar illumination, synthetic aperture radar (SAR) images coupled with quad-polarimetric techniques have significant potential for mapping forest aboveground biomass (AGB) in the mountains of southern China. To improve the accuracy of mapping forest AGB, it is necessary to accurately interpret and evaluate the sensitivity of polarimetric features related to polarimetric response in complex forests. In this study, several rotated polarimetric features were extracted from L-band quad-polarimetric ALOS PALSAR-2 images based on uniform polarimetric matrix rotation theory. In addition, the sensitivity of rotated polarimetric features with forest parameters was evaluated by the Pearson correlation coefficient, sensitivity index (SI), and saturation levels. Ultimately, the forest AGB was mapped with various combinatorial feature sets by a proposed feature selection method based on the sensitivity index. The results illustrated that rotated polarimetric features extracted from the rotational domain have higher sensitivity with various forest parameters and higher saturation levels for mapping forests than other traditional features. After using the proposed feature selection method and combinatorial feature sets, the rRMSE of mapped forest AGB ranged from 22.5% to 33.9% for two acquired images, and the best result was obtained from the combination of three types of polarimetric features (BC + C4 + Ro). It is also confirmed that different types of features extracted from quad-polarimetric SAR images have better compensation effects and the accuracy of mapped forest AGB is significantly improved.

Using a Vegetation Index to Monitor the Death Process of Chinese Fir Based on Hyperspectral Data

“…The main landform of the forest is low to medium mountains, with altitudes ranging from 115 to 1270 m above sea level. The forest land of the forest farm has a total area of 6748.2 ha, mainly ecological public welfare forests consisting of Chinese fir plantations [21].…”

“…x FOR PEER REVIEW 3 of 13 sea level. The forest land of the forest farm has a total area of 6748.2 ha, mainly ecological public welfare forests consisting of Chinese fir plantations [21].…”

Editorial for the Special Issue “SAR for Forest Mapping II”

“…This Special Issue consists of nine research papers [1][2][3][4][5][6][7][8][9], which investigate several aspects related to forest parameter estimation and retrieval using SAR-based methods, such as the mapping of forest cover [1][2][3], above-ground biomass (AGB) [4], and growing stem volume (GSV) [5], as well as forest height inversion [6], forest structure characterization [7], the estimation of phenological changes [8], and damages in drought-affected forests [9] using SAR data time series. All the methods proposed in these papers were validated using real SAR data and benchmarked with state-of-the-art approaches, thus comprehensively demonstrating the theoretical and practical contributions of the research.…”

“…To improve the accuracy of mapping forest AGB by means of polarimetric SAR, it is necessary to accurately interpret and evaluate the sensitivity of the polarimetric features related to polarimetric response in complex forests. In [4], several rotated polarimetric features are extracted from L-band quad-polarimetric ALOS PALSAR-2 images based on the uniform polarimetric matrix rotation theory. The sensitivity of rotated polarimetric features is evaluated using forest parameters, and the forest AGB is mapped with various combinatorial feature sets.…”