Rses, and lowland wetlands. Spartina alterniflora grows finest on muddy beaches in estuaries. Within the YRD, Spartina alterniflora normally grows within the intertidal zone of estuaries, bays, along with other coastal tidal flats with elevations from 0.7 m under the mean sea level towards the mean high-water level and forms a dense single-species community.As shown in Figure 2, a field survey in the YRD wetland was performed from 9 November 2020 to 13 November 2020. Due to the similar morphological and spectral characteristics also as lack of prior understanding, Phragmites australis and Spartina alterniflora have been merged into the group of grass, whereas shrub was utilised to represent the Tamarix chinensis. Hence, the wetlands in the YRD is divided into seven kinds: saltwater, farmland, river, shrub, grass, Suaeda salsa, and tidal flat. 2.three. Procedures Figure three presents the all round technical flow chart of this study, like information preprocessing, functions extraction, datasets fusion, supervised classification, and FM4-64 Chemical accuracy evaluation. The detailed information processing process is shown beneath.Figure 3. The all round technical flow chart of this study.two.three.1. GF-3 Preprocessing As shown in Figure three, GF-3 PolSAR image processing consists of image preprocessing, features extraction, image classification, and accuracy evaluation.Remote Sens. 2021, 13,8 ofFirst, the preprocessing from the original PolSAR image in single appear complicated (SLC) format was performed with Pixel Facts Expert SAR (PIE-SAR) six.0 and ENVI5.six, like radiometric calibration, polarization filtering, and polarization matrix conversion. Following importing the GF-3 full-polarization SAR information, the radiometric correction course of action might be completed automatically. A polarized PF-05105679 Antagonist scattering matrix can only describe socalled coherent or pure scatterers, whereas distributed scatterers typically use second-order descriptors [54]. Hence, following importing the data, the polarization scattering matrix was converted in to the polarization covariance matrix or polarization coherence matrix by implies of a transformation function. PolSAR image speckle noise seriously impacts the image good quality, accuracy of landcover data extraction, and ground object interpretation. Azimuth and range multi-looking of 33 along with the refined Lee filter together with the window size of three 3 have been employed to minimize speckle noise together with the output image grid size of 8 m. Feature extraction is divided into two steps. The first step is polarization decomposition, which aims to properly separate ground objects dominated by distinctive scattering mechanisms. Polarization functions derived from polarization decomposition can reveal the scattering mechanism of the ground object to figure out the variety. By way of example, surface scattering is dominant in water bodies, whereas secondary scattering and volume scattering are dominant in residential land and forest, respectively. The polarization decomposition was carried by the H-A- decomposition technique and also the three-component Freeman decomposition process, respectively [23]. H-A- decomposition uses the scattering matrix transformation to acquire the coherency matrix [T3], exactly where [T3] is really a semi-positive definite Hermite matrix [31]. The 3 second-order parameters of H-A- decomposition are the eigenvalues and eigenvector functions of [T3], which are defined as follows [32]:entropy H: H = – Pk log3 ( Pk )k =1 3 3(1)Within the formula, Pi = i / k , Pi = 1. Entropy H reflects the randomness with the target scattering mechanism. For e.
