Recent scientific advances in the use of radar in scientific hydrology

The data needs in scientific hydrology involve measurements of system states and fluxes. The microwave region is particularly well suited for measuring the system states of soil moisture and snow and the major flux into the earth as rainfall. This paper discusses the unique data needs of hydrology and presents some recent examples from AIRSAR experiments

A multi-frequency measurement of thermal microwave emission from soils: The effects of soil texture and surface roughness

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz during July - September of 1981. Three bare fields with different surface roughnesses and soil textures were prepared for the experiment. Ground truth acquisition of soil temperatures and moisture contents for 5 layers down to the depths of 15 cm was made concurrently with radiometric measurements. The experimental results show that the effect of surface roughness is to increase the soils' brightness temperature and to reduce the slope of regression between brightness temperature and moisture content. The slopes of regression for soils with different textures are found to be comparable, and the effect of soil texture is reflected in the difference of regression line intercepts at brightness temperature axis. The result is consistent with laboratory measurement of soils' dielectric permittivity. Measurements on wet smooth bare fields give lower brightness temperatures at 5 GHz than at 1.4 GHz

Intrinsic Spectral Geometry of the Kerr-Newman Event Horizon

We uniquely and explicitly reconstruct the instantaneous intrinsic metric of the Kerr-Newman Event Horizon from the spectrum of its Laplacian. In the process we find that the angular momentum parameter, radius, area; and in the uncharged case, mass, can be written in terms of these eigenvalues. In the uncharged case this immediately leads to the unique and explicit determination of the Kerr metric in terms of the spectrum of the event horizon. Robinson's ``no hair" theorem now yields the corollary: One can ``hear the shape" of noncharged stationary axially symmetric black hole space-times by listening to the vibrational frequencies of its event horizon only.Comment: Final version with improved abstract, updated references, corrected typos, and additional discussio

Spacetime Slices and Surfaces of Revolution

Under certain conditions, a $(1+1)$-dimensional slice $\hat{g}$ of a spherically symmetric black hole spacetime can be equivariantly embedded in $(2+1)$-dimensional Minkowski space. The embedding depends on a real parameter that corresponds physically to the surface gravity $\kappa$ of the black hole horizon. Under conditions that turn out to be closely related, a real surface that possesses rotational symmetry can be equivariantly embedded in 3-dimensional Euclidean space. The embedding does not obviously depend on a parameter. However, the Gaussian curvature is given by a simple formula: If the metric is written $g = \phi(r)^{-1} dr^2 + \phi(r) d\theta^2$, then \K_g=-{1/2}\phi''(r). This note shows that metrics $g$ and $\hat{g}$ occur in dual pairs, and that the embeddings described above are orthogonal facets of a single phenomenon. In particular, the metrics and their respective embeddings differ by a Wick rotation that preserves the ambient symmetry. Consequently, the embedding of $g$ depends on a real parameter. The ambient space is not smooth, and $\kappa$ is inversely proportional to the cone angle at the axis of rotation. Further, the Gaussian curvature of $\hat{g}$ is given by a simple formula that seems not to be widely known.Comment: 15 pages, added reference

Use of NOAA-N satellites for land/water discrimination and flood monitoring

A tool for monitoring the extent of major floods was developed using data collected by the NOAA-6 advanced very high resolution radiometer (AVHRR). A basic understanding of the spectral returns in AVHRR channels 1 and 2 for water, soil, and vegetation was reached using a large number of NOAA-6 scenes from different seasons and geographic locations. A look-up table classifier was developed based on analysis of the reflective channel relationships for each surface feature. The classifier automatically separated land from water and produced classification maps which were registered for a number of acquisitions, including coverage of a major flood on the Parana River of Argentina

Aircraft remote sensing of soil moisture and hydrologic parameters, Taylor Creek, Florida, and Little River, Georgia, 1979 data report

Experiments were conducted to evaluate aircraft remote sensing techniques for hydrology in a wide range of physiographic and climatic regions using several sensor platforms. The data were collected in late 1978 and during 1979 in two humid areas--Taylor Creek, Fla., and Little River, Ga. Soil moisture measurements and climatic observations are presented as well as the remote sensing data collected using thermal infrared, passive microwave, and active microwave systems

Microwave radiometer experiment of soil moisture sensing at BARC test site during summer 1981

Soil moisture was measured by truck mounted microwave radiometers at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz. The soil textures in the two test sites were different so that the soil type effect of microwave radiometric response could be studied. Several fields in each test site were prepared with different surface roughnesses and vegetation covers. Ground truth on the soil moisture, temperature, and the biomass of the vegetation was acquired in support of the microwave radiometric measurements. Soil bulk density for each of the fields in both test sites was sampled. The soils in both sites were measured mechanically and chemically. A tabulation of the measured data is presented and the sensors and operational problems associated with the measurements are discussed

Evaluation of polarimetric SAR parameters for soil moisture retrieval

Results of ongoing efforts to develop an algorithm for soil moisture retrieval from Synthetic Aperture Radar (SAR) imagery are reported. Estimates of soil moisture are of great importance in numerous environmental studies, including hydrology, meteorology, and agriculture. Previous studies using extensive scatterometer measurements have established the optimum parameters for moisture retrieval as C-band HH radar operating at incidence angles between 10 to 15 deg. However, these parameters were not tested or verified with imaging radar systems. The results from different investigators showed considerable variability in the relationship between soil moisture and radar backscattering. This variability suggests that those algorithms are site-specific. Furthermore, the small incidence angle requirement limits the spatial application, especially for airborne radar systems

Radiometric measurements over bare and vegetated fields at 1.4 GHz and 5 GHz frequencies

Microwave emission from bare and vegetated fields was measured with dual polarized radiometers at 1.4 GHz and 5 GHz frequencies. The measured brightness temperatures over bare fields are shown to compare favorably with those calculated from radiative transfer theory with two constant parameters characterizing surface roughness effect. The presence of vegetation cover is found to reduce the sensitivity to soil moisture variation. This sensitivity reduction is generally pronounced the denser, the vegetation cover and the higher the frequency of observation. The effect of vegetation cover is also examined with respect to the measured polarization factor at both frequencies. With the exception of dry corn fields, the measured polarization factor over vegetated fields is found appreciably reduced compared to that over bare fields. A much larger reduction in this factor is found at 5GHz than at 1.4GHz frequency

Preliminary analysis of the sensitivity of AIRSAR images to soil moisture variations

Synthetic Aperture Radar (SAR) images acquired from various sources such as Shuttle Imaging Radar B (SIR-B) and airborne SAR (AIRSAR) have been analyzed for signatures of soil moisture. The SIR-B measurements have shown a strong correlation between measurements of surface soil moisture (0-5 cm) and the radar backscattering coefficient sigma(sup o). The AIRSAR measurements, however, indicated a lower sensitivity. In this study, an attempt has been made to investigate the causes for this reduced sensitivity