![]() In our study we also had a look at the Pauli decomposition of ALOS PALSAR full-polarimetric dataset for San Francisco and what could be noticed from this analysis is that the key and dominating backscatter mechanism within the city is double bounce, resulting from the scattering from the ground coupled with scattering from the faces of buildings ( Figure 2). Authors use various polarimetric decompositions and classification methods on several full-polarimetric datasets, for instance ALOS PALSAR, AIRSAR, and RADARSAT-2 to extract urban area and study the structure of the city. One of the examples of urban area analysis using full-polarimetric datasets, often mentioned in the literature, is the city of San Francisco. This may lead the model-based decomposition to interpret urban areas as being dominated by volume scattering, which is typical for natural objects like vegetated areas. This approach, however, has an assumption of reflection symmetry, which sets a limitation for its applicability, especially in urban areas where rotated buildings (facades not parallel with respect to the satellite flight direction) produce strong cross-pol backscatter. Applying model-based polarimetric decomposition (e.g., Freeman-Durden) on fully polarimetric data allows for the decomposition of the backscattered power of the signal into specific scattering mechanisms: single bounce, double bounce, and volume scattering, which can be assigned typically to surfaces, buildings, and vegetation, respectively ( Figure 1). Cloude and Pottier, or model-based decompositions, e.g. Most of them use polarimetric descriptors, such as the coherency matrix or the covariance matrix, and apply polarimetric decomposition, which allows for the expression of radar backscatter from an object as a combination of scattering responses from a number of simpler objects with known backscatter characteristics (e.g., plane, sphere) or to specify the dominating scattering mechanisms.Īs described in, there are many polarimetric decompositions, such as eigenvector-based incoherent decompositions, e.g. There are many approaches to the utilization of fully polarimetric data in urban areas recognition and classification. Fully polarimetric SAR data can be used to extract physical information about the nature of the medium from which the radar signal was backscattered. One of the features of SAR data, which can be useful in target detection and land cover classification, is the radar wave polarization, because the polarization information contained in the waves backscattered from a given medium is highly related to its geometrical structure, reflectivity, shape, orientation, and geophysical properties. The latter has many advantages due to the possibility of object detection even in the presence of clouds or heavy pollution. Over the last decades, there have been many studies on urban area detection using optical remote sensing imagery, as well as Synthetic Aperture Radar (SAR) data. The classification and delineation of urban areas is still a challenging task in applied remote sensing. Moreover, the article lists factors that should be taken into consideration when performing urban area detection based only on polarimetric data and standard algorithms, such as street and building orientation, building heights, and structures. The findings of this work are very useful for increasing the awareness of the utilization of classification approaches where only pixels with double bounce backscatter mechanisms are classified as urban areas. This area of interest is also discussed in terms of the impact of SAR data resolution on the detection of specific backscatter mechanisms. This paper also mentions the canonical example of San Francisco, widely analyzed in the literature, as a case showing the impact of building deorientation on double bounce scattering. These factors are, among others, the orientation of the buildings, the dimensions of the streets, the type of construction (i.e., numerous planes on the roof), etc. There are many factors that have an impact on the detected backscatter mechanism, and the theoretical principle of predominant double bounce in urban areas can be met only under specific conditions. In this paper, we analyze fully polarimetric ALOS PALSAR data for various cities located on different continents, proving that the theory does not hold for most cases. However, when analyzing urban environments, the observed predominant backscatter may differ from theory depending on many aspects. According to the theory, the main and predominant backscattering mechanism for buildings is double bounce. ![]() ![]() Most methods used today are based on the decomposition of fully polarimetric SAR data, which allows for the extraction of physical information about the nature of the medium and the application of proper classification methods. Synthetic Aperture Radar (SAR) polarimetric datasets are widely used in the detection and classification of urban areas.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |