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Dubois, Pascale

Publications and source records attributed to Dubois, Pascale.

10 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Software For Tie-Point Registration Of SAR Data

SAR-REG software package registers synthetic-aperture-radar (SAR) image data to common reference frame based on manual tie-pointing. Image data can be in binary, integer, floating-point, or AIRSAR compressed format. For example, with map of soil characteristics, vegetation map, digital elevation map, or SPOT multispectral image, as long as user can generate binary image to be used by tie-pointing routine and data are available in one of the previously mentioned formats. Written in FORTRAN 77.

Rignot, Eric↗
NASA NTRS1994

Unsupervised Segmentation Of Polarimetric SAR Data

Method of unsupervised segmentation of polarimetric synthetic-aperture-radar (SAR) image data into classes involves selection of classes on basis of multidimensional fuzzy clustering of logarithms of parameters of polarimetric covariance matrix. Data in each class represent parts of image wherein polarimetric SAR backscattering characteristics of terrain regarded as homogeneous. Desirable to have each class represent type of terrain, sea ice, or ocean surface distinguishable from other types via backscattering characteristics. Unsupervised classification does not require training areas, is nearly automated computerized process, and provides nonsubjective selection of image classes naturally well separated by radar.

Rignot, Eric J.↗
NASA NTRS1994

Software For Calibration Of Polarimetric SAR Data

POLCAL (Polarimetric Radar Calibration) software tool intended to assist in calibration of synthetic-aperture radar (SAR) systems. In particular, calibrates Stokes-matrix-format data produced as standard product by NASA/Jet Propulsion Laboratory (JPL) airborne imaging synthetic aperture radar (AIRSAR). Version 4.0 of POLCAL is upgrade of version 2.0. New options include automatic absolute calibration of 89/90 data, distributed-target analysis, calibration of nearby scenes with corner reflectors, altitude or roll-angle corrections, and calibration of errors introduced by known topography. Reduces crosstalk and corrects phase calibration without use of ground calibration equipment. Written in FORTRAN 77.

Van Zyl, Jakob↗
NASA NTRS1993

Geographic information system for fusion and analysis of high-resolution remote sensing and ground data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System (GIS), integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a boreal forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case 1) calibrated DC-8 SAR (Synthetic Aperture Radar) data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case 2) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗
NASA NTRS1992

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗
NASA NTRS1991

Monsoon 1990: Preliminary SAR results

Multifrequency polarimetric synthetic aperture radar (SAR) images of the Walnut Gulch watershed near Tombstone, Arizona were acquired on 28 Mar. 1990 and on 1 Aug. 1990. Trihedral corner reflectors were deployed prior to both overflights to allow calibration of the two SAR data sets. During both overflights, gravimetric soil moisture and dielectric constant measurements were made. Detailed vegetation height, density, and water content measurements were made as part of the Monsoon 1990 Experiment. Preliminary results based on analysis of the multitemporal polarimetric SAR data are presented. Only the C-band data (5.7-cm wavelength) radar images show significant difference between Mar. and Aug., with the strongest difference observed in the HV images. Based on the radar data analysis and the in situ measurements, we conclude that these differences are mainly due to changes in the vegetation and not due to the soil moisture changes.

Vanzyl, Jakob J.↗
NASA NTRS1991

Unsupervised segmentation of polarimetric SAR data using the covariance matrix

An unsupervised selection of polarimetric features useful for the segmentation and analysis of polarimetric synthetic aperture radar (SAR) data is presented. The technique is based on multidimensional clustering of the parameters composing the polarimetric covariance matrix of the data. Clustering is performed on the logarithm of these quantities. Once the polarimetric cluster centers have been determined, segmentation of the polarimetric data into regions is performed using a maximum likelihood polarimetric classifier. Segmentation maps are further improved using a Markov random field to describe the statistics of the regions and computing the maximum of the product of the local conditional densities. Examples with real polarimetric SAR imagery are given to illustrate the potential of this method.

Rignot, Eric↗
NASA NTRS1989

Approach to derivation of SIR-C science requirements for calibration

A study undertaken to determine SIR-C (Shuttle Imaging Radar-C) science requirements for polarimetric calibration is described. A model describing the effect of miscalibration is presented, followed by a description of specific experiments and the resulting requirements levied on the system. The effects of miscalibration on some commonly used measures which can be extracted from SAR (synthetic aperture radar) data are also discussed. It is concluded that polarimetric calibration requirements are strongly application-dependent, and that a compromise must be made to maximize the domain of application of the data without prohibitive cost. Data summarizing SIR-C polarimetric calibration goals are also presented.

Dubois, Pascale↗