Shuttle Imaging Radar Research Articles

Target Decomposition Based on Symmetric Scattering Model for Hybrid Polarization SAR Imagery

The compact polarimetric (CP) imaging mode is a special, dual-polarization mode in which only one polarization is transmitted and two orthogonal polarizations are simultaneously used to measure the returns. The transmitting polarization can be an arbitrary elliptical wave, and therefore, theoretically, there are numerous possibilities of hybrid dual-pol modes. Since the scattering process is a function of the incident field and scattered field, when we use polarization to measure the backscattering process, radar measurement is polarization-dependent. This leads to difficulties in developing a unified interpretation for target scattering characterization in compact polarimetry, since the scattering models should be modified to take the fact of polarization dependency into account. In this letter, in the framework of a previously proposed CP formalism method, we develop a general model-based target decomposition technique that is applicable to the general CP mode. First, a general link between the fully polarimetric (FP) and the general CP scattering matrix elements is established. Second, the FP models corresponding to a single symmetric scattering mechanism and azimuthally symmetric volume scattering are mapped to the general CP case. Assuming that the 2-D backscatter is composed of a single scattering component and a volume scattering component, the decomposition is finally implemented by solving a quadratic equation. The C-band Shuttle Imaging Radar with Payload C/ X-synthetic aperture radar (SIR C/X-SAR) data are used in the experiment for demonstration.

Quaternary history of the Kiseiba Oasis region, southern Egypt

Kiseiba Oasis and depression are located in southern Egypt between the Selima Sand Sheet to the west and the Nile to the east, an important area that hosted Late Cenozoic drainage, Middle Pleistocene lakes, and numerous Paleolithic and Neolithic cultural sites. A synthesis of orbital data, field surveying and near-surface stratigraphy provides new insights into the Quaternary history of this region. Shuttle Imaging Radar data show a complex of fluvial channels that are due to stringers of surficial fluvial lag, subsurface fluvial deposits, and areas of deep alluvium. Three topographic surfaces are described: 1) the Atmur El-Kibeish, above 230 m elevation, which displays a linear pattern of light radar returns, possibly formed from northeast drainage; 2) the Acheulean Surface, at 200 m elevation, that has dark radar patterns resulting from thick alluvium bounded by pebble sand and calcrete strata, and 3) the Kiseiba Surface, below 190 m, that has a complex series of surface and subsurface fluvial and aeolian sediments. Initial drainage from the Early through Middle Pleistocene was to the northeast, which may have lasted through the Last Interglacial. Later reworking of sediments during the Last Glacial Maximum and the Holocene resulted in topographic inversion, with any subsequent local drainage on the Kiseiba Surface to the southwest, towards the Kiseiba Scarp.

Mapping Palaeohydrography in Deserts: Contribution from Space-Borne Imaging Radar

Space-borne Synthetic Aperture Radar (SAR) has the capability to image subsurface features down to several meters in arid regions. A first demonstration of this capability was performed in the Egyptian desert during the early eighties, thanks to the first Shuttle Imaging Radar mission. Global coverage provided by recent SARs, such as the Japanese ALOS/PALSAR sensor, allowed the mapping of vast ancient hydrographic systems in Northern Africa. We present a summary of palaeohydrography results obtained using PALSAR data over large deserts such as the Sahara and the Gobi. An ancient river system was discovered in eastern Lybia, connecting in the past the Kufrah oasis to the Mediterranean Sea, and the terminal part of the Tamanrasett river was mapped in western Mauritania, ending with a large submarine canyon. In southern Mongolia, PALSAR images combined with topography analysis allowed the mapping of the ancient Ulaan Nuur lake. We finally show the potentials of future low frequency SAR sensors by comparing L-band (1.25 GHz) and P-band (435 MHz) airborne SAR acquisitions over a desert site in southern Tunisia.

Quantifying deforestation in the Brazilian Amazon using Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) and Shuttle Imaging Radar (SIR)-C data

The study examined the capability of dual-polarization SAR data for forest cover mapping and change assessment in the Brazilian Amazon Forest regions. Shuttle Imaging Radar (SIR)-C and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data were analysed to map and quantify deforestation. The images were classified using hybrid classifier, where each land cover was grouped in various spectral sub-classes interpreted on the imagery and later merged together to generate the desired land cover classes. The classification accuracy for forest was reasonably high (>90%). The technique applied in this study can be extended for operational mapping and monitoring of deforestation in the tropics, particularly for those regions which are often covered by cloud.

New insight on paleoriver development in the Nile basin of the eastern Sahara

Since the first detection of paleochannels beneath sand sheets and sand dunes in the Sahara using Shuttle Imaging Radar (SIR-A) data, key advances in the understanding of these features have been made. The Sahara is currently the largest and driest region on Earth. However, it was drained by numerous rivers that are now dry channels beneath sand sheets and sand dunes. The present Sahara reflects past pluvial conditions, and the transitions from heavy rainfall to arid or hyperarid conditions reveal major climate shifts. Here, we propose that the evolution of the Sahara occurred in response to the stages of the location of the African Plate relative to the Earth’s equator, i.e., as a result of the northward drift of Africa in space and time. For instance, it is probable that during the late Eocene or Oligocene the Earth’s equator was located at the current-day latitudes of Chad and Sudan. This geometry would have produced pluvial conditions throughout North Africa. With increasing drift in space and time during the Miocene, Pliocene, and Pleistocene, the source points shifted. New valleys were formed and old ones were abandoned, and the length of the main stream of the Nile increased.

Sub-canopy soil moisture inversion using repeat pass Shuttle Imaging Radar C polarimetric Synthetic Aperture Radar interferometric data

The advances in polarimetric synthetic aperture radar (SAR) interferometry techniques provide a promising way to extract sub-canopy surface parameters using processed SAR images. In this paper, we evaluate the fully maximum likelihood decomposition model of polarimetric SAR interferometry for sub-canopy soil moisture estimation. We further propose a methodology for sub-canopy soil estimation using repeat pass space-borne SIR-C (Shuttle Imaging Radar C) L-band polarimetric SAR interferometric data. The comparison of the inversion results with the field measurements and the climate data of Hotan region from 1951 to 2006 suggests good inversion potential of the proposed method.

Optical-radar-DEM remote sensing data integration for geological mapping in the Afar Depression, Ethiopia

The advantages of integrating optical (Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) and radar (Shuttle Imaging Radar (SIR) – C, X-band Synthetic Aperture Radar (SAR) and RADARSAT-1) remote sensing data, and digital elevation models (DEMs) (Shuttle Radar Topography Mission (SRTM)) for geological mapping in arid regions such as the Afar Depression in Ethiopia are demonstrated. The Afar Depression in NE Africa is a natural laboratory for studying processes of sea-floor spreading and the transition from rifting to true sea-floor spreading. It is ideal for geological remote sensing because of its vastness, remoteness and inaccessibility together with almost continuous exposure, and lack of vegetation and soil cover. Optical-radar-DEM remote sensing data integration is used for: (1) Distinguishing spatial and temporal distribution of individual lava flows in the Quaternary Erta ‘Ale Volcanic Range in the northern part of the Afar Depression, by integrating band-ratios of ASTER thermal infrared (TIR) data with Landsat ETM+ visible and near infrared (VNIR) and SIR-C/X-SAR L-band ( λ = 24 cm) data with horizontally transmitted and horizontally received (HH) polarization. (2) Visualizing and interpreting extensional imbrication fans that constitute part of the Dobe Graben in the central part of the Afar Depression by integrating Landsat ETM+ VNIR data with RADARSAT C-band ( λ = 6 cm) data with HH polarization and SRTM DEMs. These imbrication fans were developed as layer-parallel gravitational slip of the border fault hanging-wall towards the graben center. (3) Mapping morphologically defined structures in rhyolite flows exposed on the flanks of the Tendaho Rift by merging ASTER VNIR and short wave infrared (SWIR) with RADARSAT C-band data with HH polarization. The Tendaho Rift constitutes part of the Tendaho-Gobaad Discontinuity that separates the southern and the central eastern parts of the Afar Depression. Optical-radar-DEM data integration proved to be an effective approach for aiding geological mapping and structural analysis in arid regions such as the Afar Depression.

The Sensitivity of SIR-C Backscatter to Fire-Related Forest Spatial Patterns

This research investigates the use of Shuttle Imaging Radar (SIR-C) data to analyze spatial patterns in forests experiencing different fire histories between 1943 and 1994. C-HH, C-HV, L-HH, and L-HV band data were used to calculate mean backscatter (σ°) and several landscape metrics (e.g., largest patch index, mean patch size, edge density, and patch richness). We assessed the relationship between σ° and fire history, as well as spatial patterns and fire history. Significant (p < 0.05) results were obtained for landscape metrics derived from σ° and several fire history variables, although we did not find significant relationships (p < 0.05) between mean backscatter and fire occurrence.

Rock unit discrimination on Landsat TM, SIR-C and Radarsat images using spectral and textural information

The paper presents results for spectral and textural analysis of the rock units in Landsat Thematic Mapper (TM) images, dual-band (L and C) and dual-polarization (HH and HV) Shuttle Imaging Radar (SIR)-C images, and C-band HH polarization Standard Beam 4 and Extended High Incidence Beam 3 Radarsat images from a study area between California and Arizona, USA. Fractal dimension, lacunarity and grey-level co-occurrence matrix (GLCM) textural feature images were created from the SIR-C and Radarsat images. Fractal dimensions were calculated using a differential box counting method and lacunarity measures were obtained using a new grey-scale lacunarity estimation method for 36 sample images extracted from the SIR-C and Radarsat images. The fractal dimension and lacunarity curves and class signature separability analysis show that, for rock unit discrimination using image textural features in the study area, the SIR-C L-HH image is more suitable than other SIR-C images and Radarsat images, and that co-polarization (HH) generally provides more textural information than cross-polarization (HV) in the study area. The study also shows that lacunarity measures can reveal the scaling properties of radar image textures for rock units. The combination of spectral information from Landsat TM images and textural information from radar images improves the image classification accuracy of rock units in the study area.

Documenting drainage evolution in Bir Kiseiba, southern Egypt: Constraints from ground‐penetrating radar and implications for Mars

Ground‐penetrating radar (GPR) helps to constrain the origin of relict and largely buried fluvial channels in the Bir Kiseiba region of southern Egypt. Our results indicate that the trunk channel to a tributary system identified in Shuttle Imaging Radar data is incised 10–12 m into bedrock, was southwest draining in its final configuration and laterally migrating toward the northwest, and accentuated relief along the nearby Kiseiba escarpment. Alluvium partially filling the main channel likely reflects effects of increasing aridity and bed load combined with less frequent, flashier precipitation. In contrast to defining channel margins, radar data do not indicate subtle stratigraphic changes in bedding related to fluvial aggradation, but do highlight local reflections likely corresponding to relict alluvial bedforms. Our results support the contention that an impulse GPR system, currently under development, could be deployed on a future Mars rover and assist in defining the regional evolution of the landscape and specific targets for sampling.

Assessing Relationships between Forest Spatial Patterns and Fire History with Fusion of Optical and Microwave Remote Sensing

In this paper, we tested the use of active and passive sensor fusion for relating forest fire history to landscape spatial patterns. Principal Components Analysis (PCA) was implemented to combine Landsat Thematic Mapper (TM) and Shuttle Imaging Radar (SIR-C) data from October 1994. Resulting PCs were converted to landscape patch maps. Plots with known fire history were delineated using a fire atlas of the study area. These plots came from four fire history categories: unburned (nine plots), once burned (three plots), twice burned (three plots), and multiple burned (three plots). Landscape metrics were calculated for each plot, including a shape index, mean patch size, Shannon's Diversity Index, and Shannon's Evenness Index. Spearman's Rank Correlation Analysis was used to compare the patch map‐derived landscape metrics to fire history characteristics, such as average fire‐free interval and number of fire‐free years in different time periods. Results showed that landscape patterns derived from fused data were significantly (p < 0.05) related to fire history and typically performed better than SIR-C data (a greater number of significant correlations), but not as well as TM data.

Target decomposition analysis of sir-c imagery for characterization of scattering mechanisms and their dependence on observation parameters

Multitemporal Shuttle Imaging Radar C (SIR-C) images taken over the Sarobetsu test site were analyzed using target decomposition to characterize the scattering mechanisms and relate them with the target conditions. Analysis results indicate a change in the dominant scattering mechanism with a change in the observation parameters, which is reasonably related with the surface conditions estimated from aerial photographs.

Noise estimation in remote sensing imagery using data masking

Estimation of noise contained within a remote sensing image is essential in order to counter the effects of noise contamination. The application of convolution data-masking techniques can effectively portray the influence of noise. In this paper, we describe the performance of a developed noise-estimation technique using data masking in the presence of simulated additive and multiplicative noise. The estimation method employs Laplacian and gradient data masks, and takes advantage of the correlation properties typical of remote sensing imagery. The technique is applied to typical textural images that serve to demonstrate its effectiveness. The algorithm is tested using Landsat Thematic Mapper (TM) and Shuttle Imaging Radar (SIR-C) imagery. The algorithm compares favourably with existing noise-estimation techniques under low to moderate noise conditions.

Land Cover Classification Models Using Shuttle Imaging Radar (SIR‐C) Data: A Case Study In New Hampshire, U.S.A.

Spaceborne synthetic aperture radar (SAR) systems have the ability to provide high resolution information on land cover characteristics under adverse conditions such as darkness or cloud cover. The use of multiple frequencies and multiple polarizations yields better classification accuracies. The results of various land cover classification algorithms using Shuttle Imaging Radar (SIR‐C) SAR data as applied to a site in Suncook, New Hampshire, are described in this paper. Three classification models were developed and tested: minimum distance classification, maximum a posteriori probability classification, and neural network classification. Using the available ground truth information, land cover was classified into five distinct regions: water, swamp, sand, trees, and grass. All three methods were applied to the same site and results compared. The maximum a posteriori probability approach yielded the highest overall classification accuracy on a pixel‐by‐pixel basis. Although the minimum distance approach was simpler than the maximum a posteriori approach, its performance was not as good as the latter since it did not use the covariance information between the data channels. The neural network approach performed well and its results were comparable to the maximum a posteriori approach when the variance of the data was small; however, its performance degraded rapidly when the variance of the data was high.

Characterization of Forests in Western Sayani Mountains, Siberia from SIR-C SAR Data

This paper examines the use of space-borne radar data to map forest types and logging in the mountainous Western Sayani area in central Siberia. L- and C- band HH-, HV-, and VV-polarized images from the Shuttle Imaging Radar–C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery, and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a digital elevation model improved classification results but required reducing the synthetic aperture radar resolution to match the digital elevation model. Using ratios of synthetic aperture radar channels that include cross-polarization improved classification and had the advantages of eliminating the need for a digital elevation model and preserving the full resolution of the synthetic aperture radar data.

Amazon floodplain water level changes measured with interferometric SIR-C radar

The authors find that interferometric processing of repeat-pass L-HH-band shuttle imaging radar (SIR-C) data reveals centimeter-scale changes in the elevations of water surfaces within flooded vegetation. Because radar pulses reflect specularly from the water surface, interferometric observations of open water are incoherent. However, within flooded forests and inundated shrubs, the L-band radar pulse penetrates the vegetation canopy and follows a double-bounce travel path that includes the water and vegetation-trunk surfaces. In these environments, the returned radar energy and associated phase coherence are both stronger than the surrounding nonflooded terrain, permitting determination of the interferometric phase. Phase errors related to atmospheric water vapor are usually longer in wavelength and spatially distinct from phase signatures related to stage changes in tributaries and floodplain lakes. The interferometrically measured stage decreases match gauge data, providing further verification. Water level changes across 150 m to 2.75 km-wide water bodies containing inundated vegetation can be reliably measured. The authors' results suggest that if future interferometric L-HH-band SAR missions are implemented with short temporal baselines, it is possible to measure the hydrologic response of wetlands and inundated floodplains to changes in mainstem water level.

Integrating multisensor data and RADAR texture measures for land cover mapping

This study evaluated multisensor spaceborne data from Landsat Thematic Mapper (TM) and Shuttle Imaging Radar (SIR-C) for East African landscapes including settlements, natural vegetation, and agriculture. An extensive landscape that has been difficult to accurately map with spaceborne remote sensing has been subtropical areas of savanna or woodland, especially when mixed with scattered agricultural practices. These varied vegetation communities are often very difficult to spectrally differentiate with optical data. This study examines the utility of radar to accurately locate areas of natural vegetation, scattered agricultural, and settlements. Radar data were able to accurately map these features with approximately the same accuracy as TM. In addition to comparing these two sensor types, four different geospatial manipulations of the radar data were examined. Those manipulations included measures of texture, the size of the texture window, data filtering prior to extraction of texture values, and post-classification smoothing. The variance (2nd order) measure of texture provided the best classification accuracies. The optimum window size for texture was a 13×13 pixel array and both pre- and post-classification filtering of the radar data significantly improved results.

Interferometric radar measurements of water level changes on the Amazon flood plain

Measurements of water levels in the main channels of rivers, upland tributaries and floodplain lakes are necessary for understanding flooding hazards, methane production, sediment transport and nutrient exchange. But most remote river basins have only a few gauging stations and these tend to be restricted to large river channels. Although radar remote sensing techniques using interferometric phase measurements have the potential to greatly improve spatial sampling, the phase is temporally incoherent over open water and has therefore not been used to determine water levels. Here we use interferometric synthetic aperture radar (SAR) data, acquired over the central Amazon by the Space Shuttle imaging radar mission, to measure subtle water level changes in an area of flooded vegetation on the Amazon flood plain. The technique makes use of the fact that flooded forests and floodplain lakes with emergent shrubs permit radar double-bounce returns from water and vegetation surfaces, thus allowing coherence to be maintained. Our interferometric phase observations show decreases in water levels of 7-11 cm per day for tributaries and lakes within approximately 20 km of a main channel and 2-5 cm per day at distances of approximately 80 km. Proximal floodplain observations are in close agreement with main-channel gauge records, indicating a rapid response of the flood plain to decreases in river stage. With additional data from future satellite missions, the technique described here should provide direct observations important for understanding flood dynamics and hydrologic exchange between rivers and flood plains.

Effect of Faraday rotation on L-band interferometric and polarimetric synthetic-aperture radar data

Electromagnetic waves traveling through the ionosphere undergo a Faraday rotation of the polarization vector, which modifies the polarization and phase characteristics of the electromagnetic signal. Using L-band (/spl lambda/=24 cm), polarimetric synthetic aperture radar (SAR) data from the shuttle imaging radar C (SIR-C) acquired in 1994, the author simulates the effect of a change in the Faraday rotation angle /spl psi/ on spaceborne interferometric and polarimetric data. In one experiment, it was found that phase coherence is reduced by up to 33% when /spl psi/ changes between successive data acquisitions. If /spl psi/ changes by more than 40/spl deg/, a differential phase signal, which varies from field to field, appears in the interferogram and impairs the mapping of surface topography and/or the detection of ground deformation. This signal is caused by phase differences between horizontal-polarized and vertical-polarized radar signals from intermediate levels of vegetation canopy, similar to the phase difference measured between H-polarized and V-polarized signals on a single date. In a second experiment, data from the Japanese Earth Resources Satellite (JERS-1) L-band radar acquired in an area of active deforestation in Rondonia, Brazil, are compared with SIR-C L-band polarimetric data acquired at the same incidence, two weeks later, but from a lower orbiting altitude. Large differences in scattering behavior are recorded between the two datasets in the areas of slash and burn forest, which are difficult to reconcile with surface changes. A simulation with SIR-C polarimetric data, however, suggests that those differences are consistent with a Faraday rotation angle of about 30/spl plusmn/10/spl deg/ in the JERS-1 data and 0/spl deg/ in the SIR-C data. Based on these two experiments and on Global Positioning System (GPS) records of ionospheric activity, it is concluded that Faraday rotation should not affect the analysis of L-band spaceborne data during periods of low ionospheric activity (solar minima).

Microwave remote sensing of hydrological parameters on the NOPEX area

A research project aimed at evaluating the microwave remote sensing methods for producing some basic parameters of land surfaces which influence the hydrological cycle, on a regular basis, has been conducted within the framework of the European Northern Hemisphere Climate Processes Land-surface Experiment (NOPEX) and Forest-Dynamic and Monitoring (Forest-Dynamo) experiments. In this paper, the sensitivity of the backscattering coefficient at C-and L-bands to soil moisture, surface roughness and herbaceous and arboreous biomass has been investigated by analysing experimental data collected with Synthetic Aperture Radar in Northern Europe by the airborne EMISAR during the European Multisensor Airborne Campaign (EMAC), organised by the European Space Agency and in Italy during the Multisensor Airborne Campaign (MAC-91) and the Shuttle Imaging Radar (SIR-C) experiment, both organised by NASA with the cooperation of the Italian Space Agency. An analysis of SSM/I (Special Sensor Microwave Imager) radiometric satellite images, carried out over several Scandinavian regions, which has shown sensitivity to seasonal changes of vegetation and snow cover of microwave emission, is also reported.