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.

scholarly journals Determination Of Snow Facies and Ice Velocity Using Synthetic Aperture Radar Imagery

1990 ◽  
Vol 14 ◽  
pp. 330-330
Author(s):  
R.A. Bindschadler ◽  
P.L. Vornberger
Keyword(s):  
Synthetic Aperture Radar ◽  
Liquid Water ◽  
Snow Accumulation ◽  
Surface Velocity ◽  
Synthetic Aperture ◽  
Stream Network ◽  
Backscatter Signal ◽  
Volume Scattering ◽  
Aperture Radar

The properties of synthetic aperture radar (SAR) imagery are appropriate for its use to map snow facies. These facies, defined by Benson (1962), are subdivisions of the accumulation area of an ice sheet or polar glacier and represent the interaction of the ice mass with the climate through the processes of snow accumulation and melting. Changes in these climatic parameters are expected to cause changes in the extent and character of these facies. The ability of SAR to discriminate these facies is due to the significant amount of sub-surface volume scattering in the measured radar backscatter signal and the strong absorption of radar energy by liquid water. The amount of volume scattering is dependent on the size and distribution of scatterers in the medium. This dependence varies over the size range of snow grains to ice lenses. Specific examples of the ability to detect different scatterer populations in ice sheets with SAR are shown. Other examples are given to demonstrate the reduction of backscatter signal when liquid water is present.Another important application of SAR data is the determination of surface velocity. Coregistration of a SAR and a TM image spanning an eight-year period was completed for an area in south-western Greenland. The composite image shows that, while the network of surface streams is nearly unchanged, their distance from lakes upstream increased over the eight-year interval between images. Because the lakes are likely fixed in space, a result of surface depressions whose positions are determined by the stationary bedrock topography, the displacement of the stream network was used to calculate a surface velocity of 40 ± 10 m per year near the equilibrium line.

scholarly journals Integrating Imaging Spectrometer and Synthetic Aperture Radar Data for Estimating Wetland Vegetation Aboveground Biomass in Coastal Louisiana

2019 ◽  
Vol 11 (21) ◽  
pp. 2533 ◽  
Author(s):  
Daniel Jensen ◽  
Kyle C. Cavanaugh ◽  
Marc Simard ◽  
Gregory S. Okin ◽  
Edward Castañeda-Moya ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Aboveground Biomass ◽  
Wetland Vegetation ◽  
Synthetic Aperture ◽  
Forested Wetland ◽  
Imaging Spectrometer ◽  
Synthetic Aperture Radar Data ◽  
Coastal Louisiana ◽  
Spectrometer Data ◽  
Aperture Radar

Aboveground biomass (AGB) plays a critical functional role in coastal wetland ecosystem stability, with high biomass vegetation contributing to organic matter production, sediment accretion potential, and the surface elevation’s ability to keep pace with relative sea level rise. Many remote sensing studies have employed either imaging spectrometer or synthetic aperture radar (SAR) for AGB estimation in various environments for assessing ecosystem health and carbon storage. This study leverages airborne data from NASA’s Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) to assess their unique capabilities in combination to estimate AGB in coastal deltaic wetlands. Here we develop AGB models for emergent herbaceous and forested wetland vegetation in coastal Louisiana. In addition to horizontally emitted, vertically received (HV) backscatter, SAR parameters are expressed by the Freeman–Durden polarimetric decomposition components representing volume and double-bounce scattering. The imaging spectrometer parameters include normalized difference vegetation index (NDVI), reflectance from 290 visible-shortwave infrared (VSWIR) bands, the first derivatives from those bands, or partial least squares (PLS) x-scores derived from those data. Model metrics and cross-validation indicate that the integrated models using the Freeman-Durden components and PLS x-scores improve AGB estimates for both wetland vegetation types. In our study domain over Louisiana’s Wax Lake Delta (WLD), we estimated a mean herbaceous wetland AGB of 3.58 Megagrams/hectare (Mg/ha) and a total of 3551.31 Mg over 9.92 km2, and a mean forested wetland AGB of 294.78 Mg/ha and a total of 27,499.14 Mg over 0.93 km2. While the addition of SAR-derived values to imaging spectrometer data provides a nominal error decrease for herbaceous wetland AGB, this combination significantly improves forested wetland AGB prediction. This integrative approach is particularly effective in forested wetlands as canopy-level biochemical characteristics are captured by the imaging spectrometer in addition to the variable structural information measured by the SAR.

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.

scholarly journals Determination Of Snow Facies and Ice Velocity Using Synthetic Aperture Radar Imagery

1990 ◽  
Vol 14 ◽  
pp. 330
Author(s):  
R.A. Bindschadler ◽  
P.L. Vornberger
Keyword(s):  
Synthetic Aperture Radar ◽  
Liquid Water ◽  
Snow Accumulation ◽  
Surface Velocity ◽  
Synthetic Aperture ◽  
Stream Network ◽  
Backscatter Signal ◽  
Volume Scattering ◽  
Aperture Radar

The properties of synthetic aperture radar (SAR) imagery are appropriate for its use to map snow facies. These facies, defined by Benson (1962), are subdivisions of the accumulation area of an ice sheet or polar glacier and represent the interaction of the ice mass with the climate through the processes of snow accumulation and melting. Changes in these climatic parameters are expected to cause changes in the extent and character of these facies. The ability of SAR to discriminate these facies is due to the significant amount of sub-surface volume scattering in the measured radar backscatter signal and the strong absorption of radar energy by liquid water. The amount of volume scattering is dependent on the size and distribution of scatterers in the medium. This dependence varies over the size range of snow grains to ice lenses. Specific examples of the ability to detect different scatterer populations in ice sheets with SAR are shown. Other examples are given to demonstrate the reduction of backscatter signal when liquid water is present. Another important application of SAR data is the determination of surface velocity. Coregistration of a SAR and a TM image spanning an eight-year period was completed for an area in south-western Greenland. The composite image shows that, while the network of surface streams is nearly unchanged, their distance from lakes upstream increased over the eight-year interval between images. Because the lakes are likely fixed in space, a result of surface depressions whose positions are determined by the stationary bedrock topography, the displacement of the stream network was used to calculate a surface velocity of 40 ± 10 m per year near the equilibrium line.

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