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At least 415 records · Page 23

Evaluating the Type and State of Alaska Taiga Forests with Imaging Radar for Use in Ecosystem Models

Changes in the seasonal CO2 flux of the boreal forests may result from increased atmospheric CO2 concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO2 flux and its seasonal amplitude based on meteorological data, are required. In this paper we address the use of synthetic aperture radar (SAR) to map fores type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO2 flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO2 flux. CO2 flux maps are generated, from which areal estimates of CO2 flux are derived.

Alaska↗

Modeling Broadband Phase Noise from Extended Targets in a 170 GHz Cloud-Imaging Radar

VIPR (Vapor Inside-cloud Profiling Radar) is a differential absorption radar operating over 155-175 GHz, covering a portion of the lower frequency flank of the 183 GHz water vapor absorption resonance. Transmitting at a ~1.9 mm wavelength, VIPR is highly sensitive to scattering from small particles comprising clouds and precipitation. Variation of VIPR’s cloud and precipitation echo power with frequency is often dominated by water vapor absorption, allowing humidity profiles to be retrieved along the radar’s beam path. One confounding effect in practical measurements is phase noise carried by the radar’s transmit signal, which can result in strong range sidelobes extending from bright targets and obscuring the echo signals of more weakly scattering clouds. Here we show that the magnitude and shape of phase-noise induced clutter from extended, bright cloud signals can be accurately modeled using a combination of empirical measurements of surface-echo phase noise and an analytic model based on the phase-noise sidelobe magnitude from a theoretical point target. This improved understanding of a potential clutter source in millimeter-wave imagine radar can lead to better performance modeling, and it provides motivation to improve the phase noise of very high frequency local oscillators.

Cooper, Ken B.↗

Inference of surface power spectra from inversion of multifrequency polarimetric radar data

During the summer of 1988 an intensive field experiment was conducted in the vicinity of Pisgah lava field in the Mojave Desert. As part of the experiment, physical properties such as microtopography, composition, soil moisture, and dielectric constant at five different sites representing surfaces with rms heights varying from less than one centimeter to tens of centimeters were measured. In addition, polarimetric radar images at P-band, L-band and C-band were acquired at three different incidence angles with the NASA/JPL airborne imaging radar polarimeter. Using trihedral corner reflectors deployed in the area prior to imaging, the radar images were calibrated to provide values for each resolution element in each scene. This paper reports on the derivation of the power spectrum of surface microtopography by solution of the small perturbation model for multiple incidence angle and multiple frequency radar data. Power-law fits to the power spectra have exponents that are nearly the same for all surfaces. These values are close to those from measured microtopography profiles.

Van Zyl, Jacob J.↗

Amazon Rain Forest Classification Using J-ERS-1 SAR Data

The Amazon rain forest is a region of the earth that is undergoing rapid change. Man-made disturbance, such as clear cutting for agriculture or mining, is altering the rain forest ecosystem. For many parts of the rain forest, seasonal changes from the wet to the dry season are also significant. Changes in the seasonal cycle of flooding and draining can cause significant alterations in the forest ecosystem.Because much of the Amazon basin is regularly covered by thick clouds, optical and infrared coverage from the LANDSAT and SPOT satellites is sporadic. Imaging radar offers a much better potential for regular monitoring of changes in this region. In particular, the J-ERS-1 satellite carries an L-band HH SAR system, which via an on-board tape recorder, can collect data from almost anywhere on the globe at any time of year.In this paper, we show how J-ERS-1 radar images can be used to accurately classify different forest types (i.e., forest, hill forest, flooded forest), disturbed areas such as clear cuts and urban areas, and river courses in the Amazon basin. J-ERS-1 data has also shown significant differences between the dry and wet season, indicating a strong potential for monitoring seasonal change. The algorithm used to classify J-ERS-1 data is a standard maximum-likelihood classifier, using the radar image local mean and standard deviation of texture as input. Rivers and clear cuts are detected using edge detection and region-growing algorithms. Since this classifier is intended to operate successfully on data taken over the entire Amazon, several options are available to enable the user to modify the algorithm to suit a particular image.

J-ERS-1↗

The SIR-A atlas

The scientific payload on the Space Shuttle Columbia carried into Earth orbit is discussed. Part of the payload was the Shuttle Imaging Radar system (SIR-A). The objectives of the SIR-A experiment were to acquire radar images of a wide variety of different geologic terrains around the Earth, to demonstrate the capability of the Shuttle as a platform for conducting spaceborne scientific investigations, and to analyze and interpret the data in the radar images. The SIR-A sensor imaged about 10 million sq km of the Earth's surface. High resolution images were acquired over portions of every continent and some of the oceans between latitudes 41 N and 35 S. The SIR-A incidence angle ranges from 47 deg to 53 across an image swath of approximately 50 km.

Ford, J. P.↗

Spaceborne radar subsurface imaging in hyperarid regions

Imaging data acquired with the Shuttle Imaging Radar (SIR-A) over the hyperarid region of Egypt/Sudan clearly show surface penetration through the sand cover. Even though absorption does occur in the sand layer, surface refraction leads to a steeper incidence angle at the sand/bedrock interface resulting in a stronger backscatter. A simple backscatter model shows that for a low-loss thin sand layer the presence of the covering layer enhances the capability to image the subsurface interface, particularly at large incidence angles and HH polarization.

Elachi, C.↗

Four channel simultaneous X-L band imaging SAR radar

Design considerations, construction, and testing of a four-channel microwave radar imaging system are described. Various components of the system are described in some detail including the receiver, transmitter, recorders, and the general timing circuitry. Results from flight tests of the system are described. The system is unique in that images from four microwave channels are provided and the data is obtained simultaneously. Energy is radiated at both 3 cm and 25 cm wavelengths; the four receiving channels are 3 cm, like and crossed polarization and 25 cm, like and crossed polarization.

Rawson, R.↗

Radar Analysis and Visualization Environment (RAVEN): Software for polarimetric radar analysis

Imaging radar data provides information about the geometric and dielectric properties of the Earth's surface. The Jet Propulsion Laboratory (JPL) polarimetric Airborne Synthetic Aperture Radar (AIRSAR) is currently obtaining imaging radar data for use in geologic, vegetation, snow and ice, and ocean studies. In the near future, the Shuttle Imaging Radar C (SIR-C/X-SAR) and the Earth Observing System Synthetic Aperture Radar (EOS SAR) will also collect polarimetric radar data. A need exists for a user-friendly, interactive software package for analysis of these polarimetric radar data sets. Previous software packages, such as JPL's Multiview, while providing some analysis capabilities for these data, did not allow interactive viewing and were tied to specific image display hardware with operating system dependencies. A prototype software system, the 'Radar Analysis and Visualization Environment' (RAVEN) under development at the Center for the Study of Earth from Space (CSES) at the University of Colorado, is designed to deal with data from the JPL AIRSAR instrument and other proposed polarimetric radar instruments. RAVEN is being developed using the Interactive Data Language (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system in an X-windows environment to allow for rapid, interactive visualization of AIRSAR data in both image and graphical ways. It provides a user-friendly interface through the use of menus, sliders, buttons, and display windows.

Kierein-Young, K. S.↗

The Yellowstone Fires as Observed by SIR-C SAR

Covers SIR-C (Spaceborne Imaging Radar C) SAR (Synthetic Aperture Radar) imaging of the 1988 Yellowstone National Forest fires. Discusses some of the images and data collected, and some conclusions drawn from them about both the fires, and SIR-C SAR imaging capabilities.

SIR-C Spaceborne Imaging Radar C Radar SAR Synthet↗

Comparison of Shuttle Imaging Radar-B ocean wave image spectra with linear model predictions based on aircraft measurements

During October 1984, coincident Shuttle Imaging Radar-B synthetic aperture radar (SAR) imagery and wave measurements from airborne instrumentation were acquired. The two-dimensional wave spectrum was measured by both a radar ocean-wave spectrometer and a surface-contour radar aboard the aircraft. In this paper, two-dimensional SAR image intensity variance spectra are compared with these independent measures of ocean wave spectra to verify previously proposed models of the relationship between such SAR image spectra and ocean wave spectra. The results illustrate both the functional relationship between SAR image spectra and ocean wave spectra and the limitations imposed on the imaging of short-wavelength, azimuth-traveling waves.

Monaldo, Frank M.↗

Spaceborne Imaging Radar-C instrument

The Spaceborne Imaging Radar-C is the next radar in the series of spaceborne radar experiments, which began with Seasat and continued with SIR-A and SIR-B. The SIR-C instrument has been designed to obtain simultaneous multifrequency and simultaneous multipolarization radar images from a low earth orbit. It is a multiparameter imaging radar that will be flown during at least two different seasons. The instrument operates in the squint alignment mode, the extended aperture mode, the scansar mode, and the interferometry mode. The instrument uses engineering techniques such as beam nulling for echo tracking, pulse repetition frequency hopping for Doppler centroid tracking, generating the frequency step chirp for radar parameter flexibility, block floating-point quantizing for data rate compression, and elevation beamwidth broadening for increasing the swath illumination.

Huneycutt, Bryan L.↗

Satellite radars for geologic mapping in tropical regions

This paper presents interpretations of the satellite radar images of cloud-covered portions of Indonesia and Amazonia obtained from NASA's Shuttle imaging radar experiments in 1981 (SIR-A) and 1984 (SIR-B). It was found that different terrain categories observed from distinctive image textures correlate well with major lithologic associations. The images show geologic structures at regional and local scales. The SIR-B images of East Kalimantan, Indonesia, reveal structural features and terrain distributions that had been overlooked or not perceived in previous surface mapping. Variability in radar response from the vegetation cover is interpretable only in coastal areas or alluvial areas that are relatively level.

Ford, J. P.↗

Inference of geophysical parameters from multifrequency polarimetric radar observations and model inversion

In summer 1988 an intensive field experiment was conducted in the vicinity of the Pisgah lava flow in the Mojave Desert. Physical properties such as microtopography, composition, soil moisture, and dielectric constant were measured at five sites representing surfaces with rms heights varying from less than one centimeter to tens of centimeters. In addition, polarimetric radar images at P-band, L-band, and C-band were acquired at three different incidence angles with the NASA/JPL airborne imaging radar polarimeter. Using trihedral corner reflectors deployed in the area prior to imaging, the L- and C-band images were calibrated to provide sigma0 values for each resolution element in the scene. The results of inferring geophysical parameters such as rms surface height and correlation length of the measured surfaces by fitting the observed signatures with those predicted by the small-perturbation model are presented: for smoother surfaces, the rms height values inferred are in good agreement with in situ measurements.

Van Zyl, J. J.↗