A comparison of atmospheric phase delay estimated by ASAR and MERIS over the Campania area

Propagation delay through the atmosphere is a key problem in coherent processing of synthetic aperture radar (SAR) data. Modern multitemporal interferometric techniques compensate the atmospheric phase delay contribution by analysing a stack of data. However, assessment of the achieved accuracy of the retrieved atmospheric component is still an open issue. In this work we report the results of an experiment carried out over a wide area aimed at comparing the zenith delay (ZD) estimated by radar and multispectral sensors. In particular, we refer to the instruments onboard the Envisat satellite and specifically to the Advanced Synthetic Aperture Radar (ASAR) and Multispectral Medium Resolution Imaging Spectrometer (MERIS) sensors that simultaneously acquire data along the same orbit. The study is preliminary to the possible exploitation of the MERIS water vapour product for compensating the atmospheric phase delay signals in a long series of acquisitions used in the multipass differential interferometric synthetic aperture radar (DInSAR) techniques to achieve higher accuracy and/or to extend the applicability of the technique to emergency situations, as well as to the possible use of SAR interferometry in meteorological applications.     

重轨星载InSAR测量中的大气校正方法综述

随着合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar,InSAR)技术在地形测绘及地表形变监测等领域应用日益广泛,提高其测量精度成为该技术领域近期研究的热点之一。而InSAR测量过程中的大气效应是限制其测量精度提高的主要误差源之一,如何经济有效地消除大气效应引起的延迟位相(即大气校正)是InSAR技术应用中亟待解决的问题。详细介绍了InSAR测量中现有的大气校正方法,并评述了各自的优缺点及适用条件。最后对InSAR大气校正研究中仍就存在的问题进行了概括并提出展望。     

ENVISAT-ASAR数据处理介绍

ASAR(Advanced Synthetic Aperture Radar)作为当今最先进的合成孔径雷达数据于2006年1月在国内实现共享,由于其处理困难限制了它在国内的应用推广.本文介绍了欧空局开发的雷达处理工具包软件BEST(Basic Envisat Sar Toolbox),该软件可以实现某些雷达数据处理功能,具有简单实用的特点.并且使用ASAR WSM数据与MODIS图像进行了融合.作为国内率先共享的两种数据,ASAR与MODIS组合使用将会发挥更大的作用.     

Remote sensing for the identification of coastal plumes: case studies of Delaware Bay

Two Delaware coastal plume events are studied using various remote sensing data. Satellite images obtained from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) are processed and enhanced to identify coastal plumes from Delaware Bay. Both visible band and infrared sensors give similar results in terms of the plume boundary. The gradient images of both types of sensors show the twin‐front structure near Cape Henlopen, which is also captured in a Synthetic Aperture Radar (SAR) image. Six consecutive SST images are used to track plume variability due to tidal forcing and the features of the plume front are found to be different between ebb and flood tides. Five consecutive SST images taken during a pronounced upwelling‐favourable wind event show the plume widened and separated offshore, while cooler water upwelled onshore of the separated plume.     

High resolution spatio‐temporal water vapour mapping using GPS and MERIS observations

Improved knowledge of atmospheric water vapour and its temporal and spatial variability is of great scientific interest for climate research and weather prediction. Moreover, the availability of fine resolution water vapour maps is expected to reduce significant errors in applications using the Global Positioning System, GPS, or radar interferometry. Several methods exist to estimate water vapour using satellite systems. Combining radiances as measured in two spectral bands of the Medium Resolution Imaging Spectrometer (MERIS) results in an Integrated Water Vapor (IWV) product with high spatial resolution, up to 300 m, but a limited temporal resolution of about three days, in case of cloud free conditions. On the other hand, IWV estimates can be derived from the zenith total delays as observed by continuous GPS networks. The GPS IWV estimates have a higher temporal resolution of typically 1 hour, but, even in Western Europe, inter‐station distances are at least tenths of kilometres. Here we describe how to obtain IWV products with high spatio‐temporal resolution by combining GPS and MERIS IWV estimates. For this purpose an analysis is made of MERIS and GPS based IWV data, retrieved at the same day over Western Europe. A variance–covariance analysis is performed and is subsequently applied to produce time series of combined high‐resolution water vapour maps using Kriging. The research presented here is a first step towards near real‐time fine resolution water vapour products.     

Multi-patch and centre-expansion algorithms for phase unwrapping of large InSAR images with dense residues

To recover original full phase values in inherently wrapped output, phase unwrapping has been one of the key techniques in digital image processing. However, to unwrap the phase of a large interferogram with dense residues, a conventional path-following algorithm may produce retrieval errors caused by placing long branch cuts and repetitive connection of residues. In this paper, two unwrapping algorithms, the method of multiple patches connecting opposite residues and the method of centre expansion searching opposite residues, are presented. Some examples of Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) datasets demonstrate improvement compared to conventional methods in Interferometric Synthetic Aperture Radar (InSAR) data processing.     

Assessment of the ASAR sensor radiometric quality in comparison to ERS‐2 and RADARSAT‐1 SAR data

The estimation of geophysical parameters from Synthetic Aperture Radar (SAR) data necessitates well‐calibrated sensors with good radiometric precision. In this paper, the radiometric calibration of the new Advanced Synthetic Aperture Radar (ASAR‐ENVISAT) sensor was assessed by comparing ASAR data with ERS‐2 and RADARSAT‐1 SAR data. By analysing the difference between radar signals of forest stands, the results show differences of varying importance between the ASAR on the one hand, and the ERS‐2 and the RADARSAT‐1 on the other. For recent data acquired at the end of 2005, the difference varies from ?0.72 to +0.72 dB, with temporal variations that can reach 1.1 dB. For older data acquired in 2003 and 2004, we observe a sharp decrease in the radar signal in the range direction, which can attain 3.5 dB. The use of revised calibration constants provided recently by the European Space Agency (ESA) significantly improves the results of the radiometric calibration, where the difference between the ASAR and the other SARs will be lower than 0.5 dB.     

The 26 December 2003, Bam,Iran earthquake: surface displacement from Envisat ASAR interferometry

On 26 December 2003 a 6.5?Mw earthquake took place near the city of Bam, in south‐eastern Iran. In order to detect the surface displacement field due to the Bam earthquake, we used satellite sensor images from the new European C‐band Envisat Advanced Synthetic Aperture Radar (ASAR). The displacement pattern from InSAR (SAR Interferometry) is well defined. It evidences a north–south high fringe gradient stream located 4?km west of the Bam fault. This result represents an important contribution to knowledge of the rupture process of this event and can be useful for improving and revising the interpretations of geological, geodetic and seismological data.     

A semi‐empirical backscattering model for estimation of leaf area index (LAI) of rice in southern China

Most paddy rice in southern China grows in warm, humid and rainy areas where it is hard to acquire optical remote sensing data. In this study, a semi‐empirical backscattering model was proposed to estimate leaf area index (LAI) of rice in the area using ENVISAT Advanced Synthetic Aperture Radar (ASAR) alternating polarization data. Ground measurements of LAI, water content and height of rice in the test site were collected and the model fitted at the same time as the acquisition of ASAR data. LAI estimated from the model was compared with ground measurements to evaluate the accuracy of the model. The results showed that the model provides a promising alternative to optical remote sensing data for predicting LAI of rice in southern China.     

基于SAR数据的山地冰川表面运动速度分析

合成孔径雷达(SAR)因其可全天时、全天候工作且不受云、雨的影响而成为遥感应用的前沿领域。SAR干涉测量(Inteferometry)利用SAR数据的相位信息可获得大地表面厘米级的形变而成为冰川表面流速监测广泛使用的手段;SAR图像相关方法(SRFT)能克服干涉测量方法因失相干严重而难以产生清晰的干涉条纹以及可见光图像质量由于云遮、雪盖限制的不足而成为目前山地冰川表面流速遥感监测的首选方式。为深入探讨SAR图像相关方法的适用性,以天山科契卡尔巴西冰川为研究区域,分析使用不同时间基线的ALOS PALSAR数据与ENVISat ASAR C-band 的图像相关方法估计冰川的表面流速,并使用实地测杆的DGPS(Differential GPS)测量流速进行对比验证,发现在冰川表碛覆盖区域使用图像相关方法测量的值与实测值有很好的一致性,而在裸露冰区域或坡度较大区域,误差比较大。比较长时间基线的SAR数据对特征识别的结果发现：时间基线为1 a的冬季获取的数据对估计值与实测值在表碛覆盖区域比较一致,这可能是由于前后两次获取图像时天气或地面状况比较接近。比较ALOS PALSAR 数据与ENVISat ASAR数据发现：波长较长的L-band(23.5 cm) 比C-band (5.7 cm)SAR数据更适合山地冰川的表面流速估计;另外在运用SAR数据特征匹配方法时也可能是极化方式的差异使得ALOS PALSAR (HH极化)数据比ENVISat ASAR(VV极化)数据更适合冰川研究。     

Envisat-ASAR数据的特点及其在多云多雨地区的应用前景

Envisat是由欧空局发射的一颗先进的极轨对地观测卫星,载有10种传感器,其中有先进的合成孔径雷达ASAR(Advanced Synthetic Aperture Radar)。ASAR工作在C波段,具有主动相控天线系统,5种成像模式,7种成像条带及交替极化成像功能。以获得的广东肇庆地区的ASAR交替极化模式精确分辨率图像为实例,介绍了ASAR数据的特点,分析ASAR图像中建筑物、河流、农田、船舶、林地等几种典型地物的后向散射系数值。结果表明ASAR数据可以广泛应用于多云多雨地区的土地覆盖分类,农作物估产,船只探测和海洋等领域。     

合成孔径雷达干涉测量大气改正研究综述

随着InSAR技术的飞速发展,大气影响对其应用的限制越发明显。近些年,国内外对InSAR大气改正的方法进行了大量的研究。本文在分析InSAR测量中的大气影响及其误差的基础上,对当前利用GPS、MODIS、MERIS、FY等外部数据,进行InSAR大气改正的主要方法进行了详细介绍,并对几种方法进行了综合比较和评价,分析了每种方法的优势和不足,最后对今后进一步研究的多星协同的综合大气改正方法进行了展望。     

Simultaneous non‐linear retrieval of atmospheric profiles and surface skin temperature from MODIS infrared radiances in Taiwan Strait

A non‐linear iterative physical algorithm that simultaneously retrieves atmospheric temperature, water vapour distribution and surface skin temperature from Moderate Resolution Imaging Spectroradiometer (MODIS) longwave infrared radiances is presented. The retrieval algorithm uses clear‐sky radiances measured by MODIS in Taiwan Strait for both day and night, and shows that it is capable of retrieving medium‐scale atmospheric temperature and water vapour. Sea surface temperature is retrieved with an accuracy similar to that achieved by MOD07 products. Evaluation of retrieval total precipitable water vapour (TPW) is performed by comparisons with retrievals from MOD07 products and data from a ground‐based sunphotometer. These show that MODIS retrieval of TPW, in general, agrees with other sounder retrievals of TPW. The total totals index (TTI) distribution retrieved from MODIS data is similar to that from MOD07 products.     

Use of satellite images of chlorophyll fluorescence to monitor the spring bloom in coastal waters

This article demonstrates a successful application of fluorescence line height (FLH) images from the Medium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagers and provides a strong argument for making more widespread use of FLH in monitoring surface phytoplankton in coastal waters. In the present example, MERIS and MODIS FLH images show the start of the spring bloom in coastal waters of the Strait of Georgia in British Columbia, Canada. The images clearly show a recurring pattern in five of the eight years from 2003 to 2010 covered by MERIS, which suggests seeding of the early spring bloom from narrow coastal inlets. Such seeding has been suggested before, but never observed. FLH images show the blooms more clearly than images of surface chlorophyll based on the ratios of water-leaving radiances in the blue and green spectral range (440–560 nm). FLH images used here have been derived with no atmospheric correction. Alternative products based on the blue/green ratio require atmospheric correction, which is difficult in coastal areas. Such products also tend to be more significantly confused with other constituents of coastal waters.     

Deformation mapping in three dimensions for underground mining using InSAR – Southern highland coalfield in New South Wales,Australia

This article presents 3D surface deformation mapping results derived from satellite synthetic aperture radar (SAR) data acquired over underground coal mines. Both ENVISAT Advanced Synthetic Aperture Radar (ASAR) and Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data were used in this study. The quality of the 3D deformation mapping results due to underground mining is mainly limited by two factors. (1) Differential interferometric synthetic aperture radar (DInSAR) is less sensitive to displacement along the north–south direction in the case of the current SAR satellite configurations. (2) The mining-induced displacement is continuous and nonlinear; and the accuracy of the 3D DInSAR measurement is severely affected by the similar but non-identical temporal overlaps of the InSAR pairs. The simulation and real data analyzes have shown that it would be more practical to use DInSAR pairs with the assumption of negligible northing displacement to derive the displacements in the easting and vertical directions. The northing displacement could then be estimated from the residuals. This limitation could be overcome in the future with the launch of more radar satellites, which would provide better viewing geometry.     

Coastally trapped atmospheric gravity waves on SAR,AVHRR and MODIS images

Alternative dark–bright patterns on two ENVISAT Advanced Synthetic Aperture Radar (ASAR) images of the east coast of the Korean Peninsula acquired on 18 and 19 May 2004 are interpreted as atmospheric gravity waves (AGWs) on the basis of simultaneous multi‐satellite observations and atmospheric gravity wave theory. The AGWs appeared in the form of a wave packet containing several waves located between 50 and 200 km offshore. The wavelengths were ranging from 13 to 20 km. The lengths of AGW crests were from 20 to 150 km. An NOAA‐17 pass was received about 30 min after the ASAR pass. Its channel 4 infrared (IR) image clearly shows wave‐like moisture patterns. However, the sea surface temperature (SST) image derived after applying nonlinear calibration and split‐window atmospheric correction shows no wave patterns. A daytime true‐colour MODIS image taken about 14 h later still shows a cloud band of same AGWs, indicating the lifespan of the standing AGWs can be over half a day. Although oceanic internal waves (IWs) may also cause similar wave patterns imaged by spaceborne SAR as they modulate the ocean surface roughness, we provide evidence to eliminate this possibility in this case. The characteristics of satellite observed AGWs are in good agreement with these simulated by a linear coastal AGW model.     

Envisat multi‐polarized ASAR data for flood mapping

During the August 2002 Elbe river flood, different satellite sensor data were acquired, and especially Envisat Advanced Synthetic Aperture Radar (ASAR) data. The ASAR instrument was activated in Alternating Polarization (AP) and Image (IM) modes, providing high resolution datasets. Thus, the comparison with a quasi‐simultaneous ERS‐2 scene enables the evaluation of the contribution of polarization configurations to flood boundary delineation. This study highlights the increased capabilities of the Envisat ASAR instrument in flood mapping, especially the benefit of combining like‐ and cross‐polarizations for rapid mapping within a crisis context.     

Predicting winter wheat condition,grain yield and protein content using multi‐temporal EnviSat‐ASAR and Landsat TM satellite images

Since optical and microwave sensors respond to very different target characteristics, their role in crop monitoring can be viewed as complementary. In particular, the all‐weather capability of Synthetic Aperture Radar (SAR) sensors can ensure that data gaps that often exist during monitoring with optical sensors are filled. There were three Landsat Thematic Mapper (TM) satellite images and three Envisat Advanced Synthetic Aperture Radar (ASAR) satellite images acquired from reviving stage to milking stage of winter wheat. These data were successfully used to monitor crop condition and forecast grain yield and protein content. Results from this study indicated that both multi‐temporal Envisat ASAR and Landsat TM imagery could provide accurate information about crop conditions. First, bivariate correlation results based on the linear regression of crop variables against backscatter suggested that the sensitivity of ASAR C‐HH backscatter image to crop or soil condition variation depends on growth stage and time of image acquisition. At the reviving stage, crop variables, such as biomass, Leaf Area Index (LAI) and plant water content (PWC), were significantly positively correlated with C‐HH backscatter (r = 0.65, 0.67 and 0.70, respectively), and soil water content at 5 cm, 10 cm and 20 cm depths were correlated significantly with C‐VV backscatter (r = 0.44, 0.49 and 0.46, respectively). At booting stage, only a significant and negative correlation was observed between biomass and C‐HH backscatter (r = ?0.44), and a saturation of the SAR signal to canopy LAI could explain the poor correlation between crop variables and C‐HH backscatter. Furthermore, C‐HH backscatter was correlated significantly with soil water content at booting and milking stage. Compared with ASAR backscatter data, the multi‐spectral Landsat TM images were more sensitive to crop variables. Secondly, a significant and negative correlation between grain yield and ASAR C‐HH & C‐VV backscatter at winter wheat booting stage was observed (r = ?0.73 and ?0.55, respectively) and a yield prediction model with a correlation coefficient of 0.91 was built based on the Normalized Difference Water Index (NDWI) data from Landsat TM on 17 April and ASAR C‐HH backscatter on 27 April. Finally, grain protein content was found to be correlated significantly with ASAR C‐HH backscatter at milking stage (r = ?0.61) and with Structure Insensitive Pigment Index (SIPI) data from Landsat TM at grain‐filling stage (r = 0.53), and a grain protein content prediction model with a correlation coefficient of 0.75 was built based on the C‐HH backscatter and SIPI data.     

Atmospheric correction of ENVISAT/MERIS data over case II waters: the use of black pixel assumption in oxygen and water vapour absorption bands

The Medium Resolution Imaging Spectrometer (MERIS) sensor, with its good physical design, can provide excellent data for water colour monitoring. However, owing to the shortage of shortwave-infrared (SWIR) bands, the traditional near-infrared (NIR)–SWIR algorithm for atmospheric correction in inland turbid case II waters cannot be extended to the MERIS data directly, which limits its applications. In this study, we developed a modified NIR black pixel method for atmospheric correction of MERIS data in inland turbid case II waters. In the new method, two special NIR bands provided by MERIS data, an oxygen absorption band (O₂ A-band, 761 nm) and a water vapour absorption band (vapour A-band, 900 nm), were introduced to keep the assumption of zero water-leaving reflectance valid according to the fact that both atmospheric transmittance and water-leaving reflectance are very small at these two bands. After addressing the aerosol wavelength dependence for the cases of single- and multiple-scattering conditions, we further validated the new method in two case lakes (Lake Dianchi in China and Lake Kasumigaura in Japan) by comparing the results with in situ measurements and other atmospheric correction algorithms, including Self-Contained Atmospheric Parameters Estimation for MERIS data (SCAPE-M) and the Basic ERS (European Remote Sensing Satellite) & ENVISAT (Environmental Satellite) (A)ATSR ((Advanced) Along-Track Scanning Radiometer) and MERIS (BEAM) processor. We found that the proposed method had acceptable accuracy in the bands within 560–754 nm (MERIS bands 5–10) (average absolute deviation (AAD) = 0.0081, average deviation (AD) = 0.0074), which are commonly used in the estimation models of chlorophyll-a (chl-a) concentrations. In addition, the performance of the new method was superior to that of the BEAM processor and only slightly worse than that of SCAPE-M in these bands. Considering its acceptable accuracy and simplicity both in principle and at implementation compared with the SCAPE-M method, the new method provides an option for atmospheric correction of MERIS data in inland turbid case II waters with applications aiming for chl-a estimation.     

Atmospheric correction over land for MERIS

A three-stage atmospheric correction is proposed for the Medium Resolution Imaging Spectrometer (MERIS) from a validated formulation of the signal. We correct first for the gaseous transmittance. Assuming the ozone correction is well defined, we illustrate the need to include a correction for water vapour continuum which covers most of the MERIS bands. The water vapour transmittance can be computed from the water vapour content obtained from a twoband ratio at 900nm and 890nm. We demonstrate that a direct association between the transmittance in a given band and the two band ratio is more accurate due to the removal of the coupling between absorption and scattering. Secondly, the Rayleigh correction depends on the barometric pressure determined here from a two band ratio method with the oxygen A band. Good accuracy is obtained for the pressure when accounting for the coupling between scattering and gas absorption, which mostly depends on the surface reflectance. The Rayleigh reflectance is computed from a Fourier series decomposition in which primary scattering is corrected for multiple scattering by a multiplicative factor which is derived from a polynomial regression versus the optical thickness. A similar formulation of the signal is proposed for the aerosol reflectances from 12 predefined aerosol models. The aerosol correction relies on a characterization of the aerosol over Dense Dark Vegetation for which an identification criteria is proposed along with standard reflectance values in the blue and in the red.