Shadi Oveisgharan

An Error Model for Biomass Estimates Derived From Polarimetric Radar Backscatter

Estimating the amount of above ground biomass in forested areas and the measurement of carbon flux through the quantification of disturbance and regrowth are critical to develop a better understanding of ecosystem processes. Well-resolved and globally consistent inventories of forest carbon must rely on remote sensing measurements, particularly from polarimetric radars. While a wide variety of studies conducted over the past three decades have shown how radar polarimetric measurements can be used to estimate above ground carbon for regions with less than 100 Mg of biomass per hectare, there is no established methodology for assessing biomass estimation accuracy based on a priori instrument and mission parameters. In this paper, a framework for assessing biomass estimation accuracy is presented that is a blend of the basic imaging physics and empirically derived parameters that describe various relationships between biomass and radar polarimetric observable quantities. The implications of this error model on the design and performance of a polarimetric radar are explored using instrument, mission, and science parameters from a notional Earth observing mission.

Effect of Soil Moisture on polarimetric-interferometric repeat pass observations by UAVSAR during 2010 Canadian Soil Moisture campaign

Soil Moisture Active Passive (SMAP), a proposed mission in support of the Earth Science Decadal Survey, conducted a field campaign in June 2010 to support algorithm development. As part of the experiment in situ soil moisture measurements were made over a two week period in which multiple UAVSAR flights were conducted. Repeat-pass polarimetric-interferometric data generated from these flights were analyzed to see if phase changes could be correlated with soil moisture changes. Also, we compared the data to that predicted by simple surface scattering models and showed moderate agreement with the Oh model [4].

Spaceborne GNSS-R from the SMAP Mission: First Assessment of Polarimetric Scatterometry over Land and Cryosphere

This work describes the first global scale assessment of a Global Navigation Satellite Systems Reflectometry (GNSS-R) experiment performed on-board the Soil Moisture Active Passive (SMAP) mission for soil moisture and biomass determination. Scattered GPS L2 signals (1227.6 MHz) were collected by the SMAP’s dual-polarization (Horizontal H and Vertical V) radar receiver and then processed on-ground using a known replica of the GPS L2C code. The scattering properties over land are evaluated using the Signal-to-Noise Ratio (SNR), the Polarimetric Ratio (PR), and the width of the waveforms’ trailing and leading edges. These parameters show sensitivity to the effects of the Earth’s topography and Above Ground Biomass (ABG) even over Amazonian and Boreal forests. These effects are shown to be an important factor in precise soil moisture and biomass determination. Additionally, it is found that PR shows sensitivity to soil moisture content over different land cover types. In particular, the following values of the PR are found over: (a) tropical forests ~−1.2 dB; (b) boreal forests ~0.8 dB; (c) Greenland ~2.8 dB; and (d) the Sahara Desert ~3.2 dB.

Sensitivity of Pol-InSAR Measurements to Vegetation Parameters

Estimation of forest height from combined polarimetric and interferometric synthetic aperture radar (Pol-InSAR) measurements has been the focus of radar remote sensing studies in the past decade. The simplicity of the random-volume-over-ground (RVoG) model makes it one of the most widely used candidates for estimating canopy height. However, the polarization-independent extinction coefficient assumption in the RVoG model fails in some certain types of the canopies, as suggested by the oriented-volume-over-ground (OVoG) model. The sensitivity of coherence magnitude and phase to different parameters of the canopy is expressed in a closed-form formulation in this paper for the first time. In order to simplify our formulation, the forest is represented by a layer of discrete randomly distributed dielectric scatterers over ground, with azimuthal symmetry. The sensitivity analysis of this work quantifies the contribution of differential extinction due to polarization change in interferometric coherence. Therefore, we can quantitatively evaluate whether the RVoG model is accurate enough to be used for a specific kind of canopy or the OVoG model is needed for better estimation. A simple layer of leaves over ground is used to simulate the sensitivity of Pol-InSAR measurements to different parameters.

Ka-Band Mapping and Measurements of Interferometric Penetration of the Greenland Ice Sheets by the GLISTIN Radar

Measuring ice surface topography over the major ice caps of Greenland and Antarctica is crucial to quantifying and understanding the effect of climate change on the Earths environment. Multiple sensors including radars, lidars, and optical systems have been utilized in making these measurements. To integrate data from these multiple sensors into a coherent and self-consistent history of ice cap topography requires knowledge of where vertically within the snow volume the elevation measurement corresponds. This paper examines the penetration of a Ka-band cross-track interferometric radar into the dry firn at Greenlands summit using the NASA GLISTIN Ka-band interferometric radar. GLISTIN elevation measurements are compared to NASA Wallops Airborne Terrain Mapper lidar and kinematic GPS survey measurements to assess the amount of relative penetration with GPS-surveyed corner reflectors deployed to establish the absolute vertical positioning of the radar data. We found an interferometric penetration depth estimate of 27

Soil Moisture and Vegetation Water Content Retrieval Using QuikSCAT Data

\pm

Spaceborne GNSS-R from the SMAP mission: First assessment of polarimetric scatterometry

0.3 cm. Moreover, we compare these penetration measurements to model derived estimates of the amount of interferometric penetration and provide sensitivity analysis of the amount of penetration to various ice properties. Interferometric radar mapping systems also have the ability to make wide swath topographic measurements over a wide range of weather conditions either day or night making them ideal instruments for wide area mapping. We illustrate this aspect of interferometric radar mapping with a mosaic of 24 passes of the GLISTIN instrument of the Jakobshavn Glacier area.

GNSS-R from the SMAP and CyGNSS missions: Application to polarimetric scatterometry and ocean altimetry

Climate change and hydrological cycles can critically impact future water resources. Uncertainties in current climate models result in disagreement on the amount of water resources. Soil moisture and vegetation water content are key environmental variables on evaporation and transpiration at the land–atmosphere boundary. Radar remote sensing helps to improve our estimate of water resources spatially and temporally. This work proposes a backscattered power formulation for the Ku-band. Li et al. (2010) retrieved soil moisture and vegetation water content values using Windsat data and simultaneous collocated QuikSCAT backscattered power are used to estimate different parameters of backscatter formulation. These parameters are used to estimate soil moisture and vegetation water content using QuikSCAT power everywhere and every day during the summer season. The 2-folded cross validation method is used to evaluate the performance of soil moisture and vegetation water content retrieval. A relatively large correlation is observed between vegetation water content using WindSat and QuikSCAT data in land classes of Evergreen Needleleaf, Evergreen Broadleaf, Deciduous Broadleaf, and Mixed Forests. Similarly, the retrieved soil moisture using QuikSCAT in areas with bare surface fraction of greater than 60% shows relatively high correlation with WindSat values. QuikSCAT satellite collects data over land globally almost every day. Therefore, QuikSCAT data can be used to generate a global map of soil moisture and vegetation water content daily from 2000 to 2009.

Interferometric penetration into dry snow and sea ice at Ka-band

NASAs Soil Moisture Active Passive (SMAP) mission has been tuned to perform a Global Navigation Satellite Systems Reflectometry (GNSS-R) experiment. The motivation of this study is to assess the capabilities of GNSS-R for soil moisture determination, biomass monitoring and cryosphere studies. The use for first time of the Polarimetric Ratio (PR) from a spaceborne platform shows significant sensitivity to soil moisture. Additionally, the investigation for first time of the leading and trailing edges width sensitivity to Above Ground Biomass (AGB) and rough topography shows promising results. Better understanding of these effects in the reflected waveforms will improve the development of retrieval algorithms.

SMAP radar receiver measures land surface freeze/thaw state through capture of forward-scattered L-band signals

Global Navigation Satellite Systems Reflectometry (GNSS-R) ocean applications includes scatterometry and altimetry. In this work, an investigation is performed on polarimetric scatterometry over ocean surface using data from a GNSS-R experiment on-board the Soil Moisture Active Passive (SMAP) mission, and on ocean surface topography from the Cyclone Global Navigation Satellite System (CyGNSS) mission using new retrieval algorithms. The former one provides global coverage because of the Sun Synchronous Orbit (SSO), while the latter one focuses on tropical latitudes providing a spatial sampling of 32 swaths. First results from SMAP over the Artic Sea show clearly sea ice effects on the reflected waveforms.