Silica Sand Identification using ALOS PALSAR Full Polarimetry on The Northern Coastline of Rupat Island, Indonesia

Silica sand is one of the minerals which relatively abundant in Indonesia. One of the areas with abundant of silica sand distribution is the northern coastline of Rupat Island, Bengkalis district, Riau province, Indonesia. The distribution of silica sand in this island identified only on the northern coastline in this island. Some selected sample of silica sand was measured to get the percentage of silica sand mineral’s content using X-Ray Fluorescence (XRF). Two adjacent scenes of ALOS PALSAR full-polarimetry were used. The physical properties of silica sand sample such as dielectric constant were measured using dielectric probe kit in the frequency range from 0.3 to 3.0 GHz and used for calculating the backscattering coefficient and the difference characteristics of silica sand with another object. Freeman-Durdeen and Yamaguchi techniques were used to get the scattering decomposition of physical scattering from the incoherent object model based. Surface scattering is the clearest of Scattering decomposition to show silica sand identification compares with other decompositions. From surface scattering, the backscattering coefficient value of silica sand was calculated starting from -59 dB until -52 dB. These values were given by the surface roughness condition, where the roughness is slightly rough planar. The flat condition supported by the grain size of silica sand particles that have almost the same size and shape, that were conducted by using microscopic photograph testing

A Concise Survey of G4U

The general four-component model-based decomposition with unitary transformation of coherency matrix (G4U) is a state-of-the-art four-component decomposition, which has received extensive attentions recently. A literature survey is carried out to indicate the overall influence, improvement, development, evaluation, and application of G4U. Totally, 137 literatures are found mentioning G4U in Google Scholar\c{opyright} until October 7, 2019, which can be attributed into 4 categories in terms of the degree of concentration and 17 subcategories according to the focus of attention. Among these literatures, 61 of them simply mention G4U mainly because it is a new four-component model-based decomposition, a typical model-based decomposition, or even a target decomposition. There are also 9 literatures which improve G4U and develop G4U-like decompositions with unitary transformation of coherency matrix. 20 literatures generally use G4U as a typical target decomposition for comparison or a pseudo-color visualization technique to show the performance of some developed approaches. There are also 47 literatures dedicated to critically evaluate and deeply apply G4U in the remote sensing of forestry, agriculture, wetland, snow, glaciated terrain, earth surface, manmade target, environment, and damages caused by earthquake, tsunami, and landside, which indicates the value and significance of G4U in the true sense