An Exploratory Study to Derive Precipitation over Land from X-Band Synthetic Aperture Radar Measurements

2008 ◽  
Vol 47 (2) ◽  
pp. 562-575 ◽  
Author(s):  
J. A. Weinman ◽  
F. S. Marzano
Keyword(s):  
Synthetic Aperture Radar ◽  
Cloud Model ◽  
Microwave Radiometer ◽  
Synthetic Aperture ◽  
Large Field ◽  
Horizontal Distance ◽  
X Band ◽  
Microwave Radiometers ◽  
Global Precipitation ◽  
Aperture Radar

Abstract Global precipitation measurements from space-based radars and microwave radiometers have been the subject of numerous studies during the past decade. Rainfall retrievals over land from spaceborne microwave radiometers depend mainly on scattering from frozen hydrometeors. Unfortunately, the relationship between frozen hydrometeors and rainfall varies considerably. The large field of view and related beam filling of microwave radiometer footprints introduce additional difficulties. Some of these problems will be addressed by the improved sensors that will be placed on the Global Precipitation Measurement (GPM) core satellite. Two shuttle missions demonstrated that X-band synthetic aperture radar (X-SAR) could observe rainfall over land. Several X-band SARs that can provide such measurements will be launched in the coming decade. These include four Constellation of Small Satellites for Mediterranean Basin Observations (COSMO-SkyMed), two TerraSAR-X, and a fifth Korea Multipurpose Satellite (KOMPSAT-5) to be launched by the Italian, German, and Korean Space Agencies, respectively. Data from these satellites could augment the information available to the GPM science community. The present study presents computations of normalized radar cross sections (NRCS) that employed a simple, idealized two-layer cloud model that contained both rain and frozen hydrometeors. The modeled spatial distributions of these hydrometeors varied with height and horizontal distance. An exploratory algorithm was developed to retrieve the shape, width, and simple representations of the vertical profiles of frozen hydrometeors and rain from modeled NRCS scans. A discussion of uncertainties in the retrieval is presented.

Rain-induced characteristics in C- and X-band synthetic aperture radar observations of tropical cyclones

2021 ◽  
Vol 12 (6) ◽  
pp. 573-584
Author(s):  
Xinzhe Yuan ◽  
Weizeng Shao ◽  
Bing Han ◽  
Xiaochen Wang ◽  
Xiaoqing Wang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Tropical Cyclones ◽  
Synthetic Aperture ◽  
Radar Observations ◽  
X Band ◽  
Aperture Radar

Overview of results of Spaceborne Imaging Radar-C, X-Band Synthetic Aperture Radar (SIR-C/X-SAR)

1995 ◽  
Vol 33 (4) ◽  
pp. 817-828 ◽  
Author(s):  
E.R. Stofan ◽  
D.L. Evans ◽  
C. Schmullius ◽  
B. Holt ◽  
J.J. Plaut ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Imaging Radar ◽  
X Band ◽  
Aperture Radar

scholarly journals PolSAR-Decomposition-Based Extended Water Cloud Modeling for Forest Aboveground Biomass Estimation

2019 ◽  
Vol 11 (19) ◽  
pp. 2287 ◽  
Author(s):  
Kumar ◽  
Garg ◽  
Govil ◽  
Kushwaha
Keyword(s):  
Synthetic Aperture Radar ◽  
Aboveground Biomass ◽  
Cloud Model ◽  
Synthetic Aperture ◽  
Model Parameters ◽  
Semiempirical Model ◽  
Volume Scattering ◽  
Water Cloud ◽  
Forest Aboveground Biomass ◽  
Aperture Radar

Polarimetric synthetic aperture radar (PolSAR) remote sensing has been widely used for forest mapping and monitoring. PolSAR data has the capability to provide scattering information that is contributed by different scatterers within a single SAR resolution cell. A methodology for a PolSAR-based extended water cloud model (EWCM) has been proposed and evaluated in this study. Fully polarimetric phased array type L-band synthetic aperture radar (PALSAR) data of advanced land observing satellite (ALOS) was used in this study for forest aboveground biomass (AGB) retrieval of Dudhwa National Park, India. The shift in the polarization orientation angle (POA) is a major problem that affects the PolSAR-based scattering information. The two sources of POA shift are Faraday rotation angle (FRA) and structural properties of the scatterer. Analysis was carried out to explore the effect of FRA in the SAR data. Deorientation of PolSAR data was implemented to minimize any ambiguity in the scattering retrieval of model-based decomposition. After POA compensation of the coherency matrix, a decrease in the power of volume scattering elements was observed for the forest patches. This study proposed a framework to extend the water cloud model for AGB retrieval. The proposed PolSAR-based EWCM showed less dependency on field data for model parameters retrieval. The PolSAR-based scattering was used as input model parameters to derive AGB for the forest area. Regression between PolSAR-decomposition-based volume scattering and AGB was performed. Without deorientation of the PolSAR coherency matrix, EWCM showed a modeled AGB of 92.90 t ha−1, and a 0.36 R2 was recorded through linear regression between the field-measured AGB and the modeled output. After deorientation of the PolSAR data, an increased R2 (0.78) with lower RMSE (59.77 t ha−1) was obtained from EWCM. The study proves the potential of a PolSAR-based semiempirical model for forest AGB retrieval. This study strongly recommends the POA compensation of the coherency matrix for PolSAR-scattering-based semiempirical modeling for forest AGB retrieval.

Identifying Building Damage Patterns in the 2016 Meinong, Taiwan Earthquake Using Post-Event Dual-Polarimetric ALOS-2/PALSAR-2 Imagery

2018 ◽  
Vol 13 (2) ◽  
pp. 291-302 ◽  
Author(s):  
Yanbing Bai ◽  
◽  
Bruno Adriano ◽  
Erick Mas ◽  
Shunichi Koshimura
Keyword(s):  
Statistical Analysis ◽  
High Resolution ◽  
Synthetic Aperture Radar ◽  
Building Damage ◽  
Synthetic Aperture ◽  
Color Features ◽  
X Band ◽  
Radar Imagery ◽  
Synthetic Aperture Radar Imagery ◽  
Aperture Radar

The 2016 magnitude 6.4 Meinong earthquake caused catastrophic damage to peoples lives and properties in Taiwan. Synthetic Aperture Radar remote sensing is a useful tool to rapidly grasp the near real-time building damage to areas affected by the earthquake. Previous studies employed X-band single polarized high-resolution synthetic aperture radar imagery to identify building damage. However, suitable X-band single polarized high-resolution synthetic aperture radar imagery is not always accessible. Therefore, this research applied L-band dual-polarimetric ALOS-2/PALSAR-2 data to analyze the radar scattering characteristics of three types of affected buildings in the 2016 Meinong earthquake. The results show that collapsed buildings are characterized by a weak double-bounce scattering due to a reduced dihedral structure, while the characteristics of slightly damaged buildings are similar to those of undamaged buildings. Furthermore, the discrimination ability of a series of polarimetric, texture, and color features derived from the dual-polarimetric SAR data for three types of buildings affected by the earthquake are quantified based on a statistical analysis using the pixels in the combined areas of layover, shadow, and building footprint of each building. The results of the statistical analysis show that the spaceborne dual-polarimetric ALOS-2/PALSAR-2 images have good potential to distinguish between slightly damaged buildings and collapsed and tilted buildings. However, it is still difficult to distinguish between collapsed and tilted buildings. In addition, the results of the statistical analysis show that the mean value and variance value of the Gray-Level Co-Occurrence Matrix of the span image are two suitable features by which the categories of building damage can be distinguished. The polarimetric and color features demonstrated poorer performance in terms of distinguishing between damage categories than the texture features.

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