Environmental Satellite Advanced Synthetic Aperture Radar Research Articles

Mechanisms of SAR Imaging of Shallow Water Topography of the Subei Bank

In this study, the C-band radar backscatter features of the shallow water topography of Subei Bank in the Southern Yellow Sea are statistically investigated using 25 ENVISAT (Environmental Satellite) ASAR (advanced synthetic aperture radar) and ERS-2 (European Remote-Sensing Satellite-2) SAR images acquired between 2006 and 2010. Different bathymetric features are found on SAR imagery under different sea states. Under low to moderate wind speeds (3.1~6.3 m/s), the wide bright patterns with an average width of 6 km are shown and correspond to sea surface imprints of tidal channels formed by two adjacent sand ridges, while the sand ridges appear as narrower (only 1 km wide), fingerlike, quasi-linear features on SAR imagery in high winds (5.4~13.9 m/s). Two possible SAR imaging mechanisms of coastal bathymetry are proposed in the case where the flow is parallel to the major axes of tidal channels or sand ridges. When the surface Ekman current is opposite to the mean tidal flow, two vortexes will converge at the central line of the tidal channel in the upper layer and form a convergent zone over the sea surface. Thus, the tidal channels are shown as wide and bright stripes on SAR imagery. For the SAR imaging of sand ridges, all the SAR images were acquired at low tidal levels. In this case, the ocean surface waves are possibly broken up under strong winds when propagating from deep water to the shallower water, which leads to an increase of surface roughness over the sand ridges.

A-Differential Synthetic Aperture Radar Interferometry analysis of a Deep Seated Gravitational Slope Deformation occurring at Bisaccia (Italy)

This paper presents the results of an investigation on a Deep Seated Gravitational Slope Deformation (DSGSD), previously only hypothesized by some authors, affecting Bisaccia, a small town located in Campania region, Italy. The study was conducted through the integration of conventional methods (geological-geomorphological field survey, air-photo interpretation) and an Advanced-Differential Interferometry Synthetic Aperture Radar (A-DInSAR) technique. The DSGSD involves a brittle lithotype (conglomerates of the Ariano Irpino Supersynthem) resting over a Structurally Complex Formation (Varycoloured Clays of Calaggio Formation). At Bisaccia, probably as a consequence of post-cyclic recompression phenomena triggered by reiterated seismic actions, the rigid plate made up of conglomeratic sediments resulted to be split in five portions, showing different rates of displacements, whose deformations are in the order of some centimeter/year, thus inducing severe damage to the urban settlement.A-DInSAR techniques confirmed to be a reliable tool in monitoring slow-moving landslides. In this case 96 ENVIronmental SATellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) images, in ascending and descending orbits, have been processed using SUBSOFT software, developed by the Remote Sensing Laboratory (RSLab) group from the Universitat Politècnica de Catalunya (UPC). The DInSAR results, coupled with field survey, supported the analysis of the instability mechanism and confirmed the historical record of the movements already available for the town.

Multi-sensor monitoring of Ulva prolifera blooms in the Yellow Sea using different methods

The massive Ulva (U.) prolifera bloom in the Yellow Sea was first observed and reported in summer of 2008. After that, the green tide event occurred every year and influenced coastal areas of Jiangsu and Shandong provinces of China. Satellite remote sensing plays an important role in monitoring the floating macroalgae. In this paper, U. prolifera patches are detected from quasisynchronous satellite images with different spatial resolution, i.e., Aqua MODIS (Moderate Resolution Imaging Spectroradiometer), HJ-1A/B (China Small Satellite Constellation for Environment and Disaster Monitoring and Forecasting), CCD (Charge-Coupled Device), Landsat 8 OLI (Operational Land Imager), and ENVISAT (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) images. Two comparative experiments are performed to explore the U. prolifera monitoring abilities by different data using detection methods such as NDVI (Normalized Difference Vegetation Index) with different thresholds. Results demonstrate that spatial resolution is an important factor affecting the extracted area of the floating macroalgae. Due to the complexity of Case II sea water characteristics in the Yellow Sea, a fixed threshold NDVI method is not suitable for U. prolifera monitoring. A method with adaptive ability in time and space, e.g., the threshold selection method proposed by Otsu (1979), is needed here to obtain accurate information on the floating macroalgae.

Estimation of internal wave velocity in the shallow South China Sea using single and multiple satellite images

This paper presents results on the estimation of the phase velocity of internal waves (IWs) in the shallow waters of the South China Sea in terms of the water depth using satellite data. To calculate the phase velocity, two methods are considered. The first is based on the different positions of IW images acquired by Environmental Satellite-advanced synthetic aperture radar (ASAR) and Terra–Moderate Resolution Imaging Spectroradiometer (MODIS) in a very short time interval, and the second method uses the images of several packets of IWs associated with semidiurnal tidal period in either a single ASAR or MODIS image. The former is termed as the multitemporal images (MTI) method, and the latter is referred to as the tidal period images (TPI) method. The results show that the wave velocities estimated by the MTI method have strong correlation with those derived from a depth-dependent IW propagation theory, while those by the TPI method have moderate correlation. Both the methods can be used to estimate the IW phase velocity but with reduced accuracy by the TPI method. The main reason of this reduced accuracy is the long tidal period during which the characteristics of IWs change as they propagate over long distance in the water of variable currents and/or bottom topography.

Multi-Polarization ASAR Backscattering from Herbaceous Wetlands in Poyang Lake Region, China

Wetlands are one of the most important ecosystems on Earth. There is an urgent need to quantify the biophysical parameters (e.g., plant height, aboveground biomass) and map total remaining areas of wetlands in order to evaluate the ecological status of wetlands. In this study, Environmental Satellite/Advanced Synthetic Aperture Radar (ENVISAT/ASAR) dual-polarization C-band data acquired in 2005 is tested to investigate radar backscattering mechanisms with the variation of hydrological conditions during the growing cycle of two types of herbaceous wetland species, which colonize lake borders with different elevation in Poyang Lake region, China. Phragmites communis (L.) Trin. is semi-aquatic emergent vegetation with vertical stem and blade-like leaves, and the emergent Carex spp. has rhizome and long leaves. In this study, the potential of ASAR data in HH-, HV-, and VV-polarization in mapping different wetland types is examined, by observing their dynamic variations throughout the whole flooding cycle. The sensitivity of ASAR backscattering coefficients to vegetation parameters of plant height, fresh and dry biomass, and vegetation water content is also analyzed for Phragmites communis (L.) Trin. and Carex spp. The research for Phragmites communis (L.) Trin. shows that HH polarization is more sensitive to plant height and dry biomass than HV polarization. ASAR backscattering coefficients are relatively less sensitive to fresh biomass, especially in HV polarization. However, both are highly dependent on canopy water content. In contrast, the dependence of HH- and HV- backscattering from Carex community on vegetation parameters is poor, and the radar backscattering mechanism is controlled by ground water level.

Comparison between Differential SAR interferometry and ground measurements data in the displacement monitoring of the earth-dam of Conza della Campania (Italy)

This paper presents the application of Differential Synthetic Aperture Radar (SAR) interferometry (DInSAR) algorithms for the precise monitoring of earth dams ground deformation. The test site selected for this study is the Conza Dam, located in the southern Apennines (Italy), very close to the epicenter of the big earthquake (Mw=6.9) which took place on November 23th, 1980, striking the Irpinia region. Among the multiple advanced DInSAR techniques developed by the SAR community during the last decade, this work uses the so-called SUBSOFT software, developed by the Remote Sensing Laboratory (RSLab) group from the Universitat Politècnica de Catalunya (UPC), which is based on the use of Coherent Pixels Technique (CPT) algorithm. The analysis is carried out using 51 ENVIronmental SATellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) images, corresponding to the period from 29th of November 2002 to the 30th of July 2010. In this framework, ground displacements recorded by a network of conventional ground-based sensors are also available for the same temporal span. Indeed, the embankment dam is well instrumented to measure internal settlements by means of cross-arms placed in six different cross-sections, and superficial displacements by means of targets for precise leveling. A statistical analysis has been performed to carry out a better comparison between the measurements obtained with the conventional field sensors and the interferometric data. The high agreement between final DInSAR displacements and in-situ instrumental data, demonstrates the reliability of such technique for the precise monitoring of civil infrastructures, and concretely, in dams with a high exposure factor and its consequent risk.

A regional investigation of urban land-use change for potential landslide hazard assessment in the Three Gorges Reservoir Area, People's Republic of China: Zigui to Wanzhou

The near-completion of the Three Gorges Dam has led to the creation of a narrow reservoir that, when completed in 2009, will stretch over 660 km upstream and result in the displacement of approximately 1.2 million people. This reservoir will drown more than 100 towns, some of which have already been lost due to the rising waters, and result in a significant change in land use. New urban areas have been constructed at higher elevations to avoid the rising water but it is feared that some of these settlements may now be exposed to a greater risk of landslides due to slope failure. A geographic information system (GIS) consisting of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat Thematic Mapper (TM), and Environmental Satellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) data has been created and used to monitor the urban changes from before the Dam's construction to the present day as well as changes in landslide susceptibility. To perform this analysis, a new 30 m high-resolution digital elevation model (DEM) was derived by combining an ASTER and Shuttle Radar Topography Mission (SRTM) DEM. Fieldwork was carried out along the Yangtze River, where the urban boundaries were field-checked using GPS to navigate to the satellite-derived checkpoints. The results show that a majority of the new urban areas are in fact located on shallow slopes, but are often positioned below steep slopes, which could pose a future threat of landslide risk to the inhabitants of the new towns.

Coherence-based land cover classification in forested areas of Chattisgarh, Central India, using environmental satellite—advanced synthetic aperture radar data

In the present work, the potential of synthetic aperture radar (SAR) interferometric coherence in land cover classification is studied over forested areas of Bilaspur, Chattisgarh, India using Environmental Satellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) C-band data. Single look complex (SLC) interferometric pair ASAR data of 24th September 2006 (SLC-1) and 29th October 2006 (SLC-2) covering the study area were acquired and processed to generate backscatter and interferometric coherence images. A false colored composite of coherence, backscatter difference, and mean backscatter was generated and subjected to maximum likelihood classification to delineate major land cover classes of the study area viz., water, barren, agriculture, moist deciduous forest, and sal mixed forests. Accuracy assessment of the classified map is carried out using kappa statistics. Results of the study suggested potential use of ENVISAT-ASAR C-band data in land cover classification of the study area with an overall classification accuracy of 82.5%, average producer's accuracy of 83.69%, and average user's accuracy of 81%. The present study gives a unique scope of SAR data application in land cover classification over the tropical deciduous forest systems of India, which is still waiting for its indigenous SAR system.

Application of multi-temporal ENVISAT ASAR data to agricultural area mapping in the Pearl River Delta

This study investigates a method using multi-temporal, multi-polarization ENVISAT (Environmental Satellite) Advanced Synthetic Aperture Radar (ASAR) data for mapping an agricultural area in a sub-tropical cloud-prone and rainy area of Pearl River Delta in south China. A total of six scenes of HH (radio waves transmitted and received in horizontal polarization) and VV (radio waves transmitted and received in vertical polarization) polarization ASAR data acquired from March to November 2006 were used for land cover classification. Meanwhile, four field surveys of 320 test sites were carried out simultaneously with ASAR image acquisition in May, July, September and November 2006. A decision tree classifier is used to classify seven main types of land cover features including sugarcane, banana fields, lotus ponds, fish ponds, mangrove wetland, seawater and buildings. As a result, a classification map of Nansha Island was generated with overall accuracy of 80% and a kappa coefficient of 77%. The results show that the multi-temporal and multi-polarization ASAR images can have good performance in separating the basic land cover categories in a sub-tropical cloud-prone and rainy area. The decision tree classifier is also approved to work efficiently on satellite SAR images with good classification accuracy. The analysis to get the best combination of radar scenes for the decision tree also proves that multi-temporal radar backscatter information received in the crop growth period is important in improving classification accuracy.

Understanding c-band radar backscatter from wheat canopy using a multiple-scattering coherent model

This paper describes a modeling approach to interpret the C-band synthetic aperture radar (SAR) data from wheat canopies as provided by European Remote Sensing (ERS) satellites, RADARSAT, and the forthcoming Environmental Satellite/Advanced Synthetic Aperture Radar (ENVISAT/ASAR) satellite. At a first step, the results of a first-order modeling were compared to ERS data and scatterometer data over the growing season at two different test sites. The prediction by first-order approach was in disagreement with the data from stem extension stage to soft ripening stage. The first-order approach was found to overestimate the attenuation at vertical (V) polarization, resulting in a predicted backscattering coefficient one order of magnitude lower than that observed by the SAR system. To improve the prediction, a multiple-scattering modeling based on numerical solution of multiple-scattering Foldy-Lax equation was used. The multiple-scattering modeling provides better backscatter estimates at vertical-vertical (VV) polarization for both test sites. Then, the model is used to derive the prevailing interactions mechanisms at horizontal-horizontal (HH) and VV polarizations and 23/spl deg/ and 40/spl deg/ of incidence angle. Finally, the retrieval of crop parameters from C-band SAR data is addressed.

Engineering geology in Canada

This paper presents the results of an investigation on a Deep Seated Gravitational Slope Deformation (DSGSD), previously only hypothesized by some authors, affecting Bisaccia, a small town located in Campania region, Italy. The study was conducted through the integration of conventional methods (geological-geomorphological field survey, air-photo interpretation) and an Advanced-Differential Interferometry Synthetic Aperture Radar (A-DInSAR) technique. The DSGSD involves a brittle lithotype (conglomerates of the Ariano Irpino Supersynthem) resting over a Structurally Complex Formation (Varycoloured Clays of Calaggio Formation). At Bisaccia, probably as a consequence of post-cyclic recompression phenomena triggered by reiterated seismic actions, the rigid plate made up of conglomeratic sediments resulted to be split in five portions, showing different rates of displacements, whose deformations are in the order of some centimeter/year, thus inducing severe damage to the urban settlement.A-DInSAR techniques confirmed to be a reliable tool in monitoring slow-moving landslides. In this case 96 ENVIronmental SATellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) images, in ascending and descending orbits, have been processed using SUBSOFT software, developed by the Remote Sensing Laboratory (RSLab) group from the Universitat Politècnica de Catalunya (UPC). The DInSAR results, coupled with field survey, supported the analysis of the instability mechanism and confirmed the historical record of the movements already available for the town.