Typhoon eye extraction with an automatic SAR image segmentation method

Spaceborne microwave synthetic aperture radar (SAR), with its high spatial resolution (10–100 m), large area coverage, and day/night imaging capability, has been used as an important tool for typhoon monitoring. Since the microwave signal can penetrate through clouds, SAR images reveal typhoon morphology at the sea surface. Within the region of a typhoon eye, wind speed and the associated sea surface roughness are usually low. Therefore, the typhoon eye can be well distinguished as dark areas in SAR images. However, automatic typhoon eye extraction from SAR images is hampered by SAR image speckle noise and other false-alarm dark features contained in an image. In this study, we propose an image processing approach to extract typhoon eyes from SAR images. The three-step image processing includes: (1) applying an extended non-local means image denoizing algorithm to reduce image speckle noise; (2) applying a top-hat transform to denoized imagery to enhance the contrast; and (3) using a labelled watershed to segment the typhoon eye. Experimental results from analysing three Environmental Satellite SAR typhoon images show that our approach provides fast and efficient SAR image segmentation for typhoon eye extraction. Typhoon eyes are segmented correctly, and their edges are well detected. Our experimental results are comparable to manually extracted typhoon eye information. Fine-tuning of this approach will provide an automatic tool for typhoon eye information extraction from SAR images.     

Evaluating the calibration of MTSAT‐1R infrared channels using collocated Terra MODIS measurements

The calibration of four MTSAT‐1R infrared channels was evaluated by comparing MTSAT measurements with Terra/MODIS inferred MTSAT‐equivalent brightness temperatures during August 2005 and August 2006. Theoretical relationships converting MODIS brightness temperatures to MTSAT‐equivalent values were obtained and used for the comparison. Results indicate that MTSAT two split window channels are well calibrated, and no serious systematic errors or biases are found; and the MTSAT water‐vapour channel shows a good linear relationship but with a warm bias up to 2 K. The significant cold bias of MTSAT 3.7 µm channel about ?6.7 K in August 2005 is found to be much removed in August 2006, after correction of the electrical crosstalk between MTSAT‐1R SWIR channel and WV channel starting from March 2006. Since then, calibration performances of MTSAT‐1R split window channels and shortwave IR channel seem to be comparable with MODIS calibration, while the water‐vapour channel shows more uncertainties up to 2 K of bias.     

A method for cross‐calibrating geostationary and polar orbiting satellite sensors in the infrared windows

The forward radiative transfer routine has been used to remove the artefact caused by modulation on meteorological satellite‐sensor responses. This paper describes a direct method where images observed by the infrared channels aboard the Multi‐functional Transport Satellite (MTSAT‐1R) and Fengyun‐2C (FY‐2C) geostationary satellites are compared with those by the Advanced Very High Resolution Radiometer (AVHRR) sensor aboard the National Oceanic and Atmospheric Administration (NOAA) polar‐orbiting satellites. The calibration differences between the polar orbiting and the geostationary satellites are found to be within 1 K of each other.     

Discrimination potential of X-band polarimetric SAR data

In anticipation of X-band polarimetric Synthetic Aperture Radar (SAR) data from future sensors, we investigated the potential of X-band fully polarimetric data for discriminating between the principal classes present in a study site near Avignon, France. Decomposition and analysis techniques have been applied to a dataset acquired by the ONERA airborne RAMSES (Radar Aéroporté Multi-Spectral d'Etude des Signatures) SAR. Results show that X-band provides some discrimination capability. The polarimetric parameters, entropy and α-angle, show clearly that these signature classes are grouped into five clusters corresponding to physical scattering characteristics. The introduction of the anisotropy parameter does not increase our ability to distinguish between different classes whose clusters are in the same entropy/α-angle zone. The correlation observed between the radar signal and the surface roughness over bare soils is very low.     

Mesoscale surface current fields in the Baltic Sea derived from multi-sensor satellite data

We demonstrate the use of multi-sensor satellite images for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper by enhancing and combining image-processing techniques. The sequential satellite images were acquired by the Thematic Mapper (TM), the ERS-2 Synthetic Aperture Radar (SAR), the Wide-Field Scanner (WiFS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) during extensive cyanobacterial blooms in July 1997 and in July/August 1999. We also used a pair of Advanced SAR (ASAR) images from May 2005 showing imprints of singular oil spills in the Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface were taken as tracers for the local motion of the sea surface. Data from sensors working at different electromagnetic bands (e.g. TM and SAR) were used to apply high-speed feature-matching (cross-correlation) techniques for motion detection. The sufficiently short time lags between the multiple image acquisitions (from less than 1 h to approximately 1 day) and the high spatial coverage allowed for the calculation of optical flow (i.e. surface motion) fields, which include small-scale turbulent structures that are not resolved by operational numerical models. Our computed surface currents range from 4 to 35 cm s^?1 and are generally larger than those provided by the numerical models for the same dates and areas. We attribute this difference to local wind forcing, causing higher drift velocities at the very sea surface, which is seen from space, but which is not resolved by the numerical models.     

Validation of active forest fires detected by MSG‐SEVIRI by means of MODIS hot spots and AWiFS images

The detection of forest fires and the determination of their parameters have been usually carried out by polar‐orbit sensors: AVHRR, (A)ATSR, BIRD, and MODIS mainly. However, their time resolution prevents them from operating in real time. In contrast, the new geostationary sensors have very appropriate capacities for the observation of the Earth and monitoring of forest fires, as is being proved. GOES, MSG, and MTSAT are already operative, and they have led the international community to think that the global observation network in real time may become a reality. The implementation of this network is the aim of the Global Observations of Forest Cover and Land Cover Dynamics (GOFC/GOLD) FIRE Mapping and Monitoring programme, focused internationally on taking decisions concerning the research of the Global Change. In this Letter, the operation in real time by the MSG‐SEVIRI sensor over the Iberian Peninsula is studied. On the other hand, the reliability of validation results by means of polar sensors, with a finer spatial resolution, is difficult to analyse due to errors caused by confused location of fires. This Letter shows that fires detected by means of MSG‐SEVIRI can be an useful option in order to estimate burnt areas at global scale, considering a spatial resolution of 40 km.     

Monitoring and analysis of mining 3D time-series deformation based on multi-track SAR data

Accurate monitoring of the developing process of a surface subsidence basin is the basis of building damage assessment and surface deformation prediction. In this paper, the Synthetic Aperture Radar (SAR) data of three different imaging geometries, TerraSAR, Radarsat-2, and Sentinel-1A, were exploited. Firstly, two-dimensional (2D) time-series deformation of the surface subsidence basin caused by 15,235 working face mining was obtained based on Multidimensional Small Baseline Subset (MSBAS) technology from 19 December 2015 to 5 March 2016. By comparing vertical deformation with levelling data, it is shown that the root-mean-square error of vertical deformation is 3.2 mm and the standard deviation is 1.9 mm when the ascending-descending track SAR data is available. Otherwise, the root-mean-square error of vertical deformation is 18.1 mm and the standard deviation is 11.6 mm. Because of the low precision of the north–south horizontal movement monitored by the SAR sensor, the vertical deformation acquired by MSBAS technology and the rules of the mining subsidence (horizontal movement is proportional to tilt) were combined to obtain the north–south horizontal movement which was proven to be reliable by comparing the 2D time-series deformation obtained by MSBAS technology. Then, the deformation of the railway in the surface subsidence basin was analysed based on the three-dimensional (3D) time-series deformation. The results show that the subsidence, tilt, and horizontal movement strongly influence the railway in the monitoring period, but will not affect the normal traffic. This experiment lays a technical foundation for preventing the occurrence of mining disasters and verifies the ability to monitor the deformation of buildings and structures by interferometry synthetic aperture radar technology.     

基于变系数Gardner方程的海洋内波研究

本文主要是基于同时含有二阶和三阶非线性项的变系数Gardner方程对海洋内孤立波的传播特性开展研究。在吕宋海峡海域,展示了下降型海洋内波的传播特性及其在SAR图像上的信号特征,并着重分析讨论了耗散项和微扰项对海洋内波所引起的表层流速变化的影响。     

区域GMM聚类的SAR图像分割

高斯混合模型(GMM)聚类算法近年来广泛应用于图像分割领域。但在SAR图像分割中,由于忽略了图像像素间的空间相关性,使其对相干斑噪声十分敏感。提出一种基于区域的GMM聚类算法,它将空间相关性引入聚类分类中,利用分水岭分割得到基本同质区域,计算区域的灰度均值作为GMM聚类算法的输入样本,将聚类特征从像素水平提升到区域水平,减少了噪声对分割结果的影响;并将自身反馈机制引入期望最大化(EM)算法中,进一步提高了GMM模型参数估计的精度。还对合成图像和真实SAR图像进行了分割实验,结果表明新算法可有效地提高分割的     

Assessment of an analytical model for sea surface wind speed retrieval from spaceborne SAR

An analytical model based on radar backscatter theory was utilized to retrieve sea surface wind speeds from C-band satellite synthetic aperture radar (SAR) data at either vertical (VV) or horizontal (HH) polarization in transmission and reception. The wind speeds were estimated from several ENVISAT Advanced SAR (ASAR) images in Hong Kong coastal waters and from Radarsat-1 SAR images along the west coast of North America. To evaluate the accuracy of the analytical model, the estimated wind speeds were compared to coincident buoy measurements, as well as winds retrieved by C-band empirical algorithms (CMOD4, CMOD_IRF2 and CMOD5). The comparison shows that the accuracy of the analytical model is comparable to that of the C-band empirical algorithms. The results indicate the capability of the analytical model for sea surface wind speed retrieval from SAR images at both VV and HH polarization.     

Submarine groundwater discharge in tidal flats revealed by space-borne synthetic aperture radar

Most space-borne sensors cannot detect subsurface features. Groundwater is a typical subsurface feature, and its discharge to coastal ocean waters plays an important role in transporting terrestrial chemical constituents and providing habitats for various species of fauna and flora. This is the first paper to report observational evidence for submarine groundwater discharge (SGD) in tidal flats using space-borne synthetic aperture radar (SAR). Tidal flats are composed of high-moisture-saturated sediments and water puddles. These shallow water puddles were imaged effectively by using SAR systems. The presence of water puddles is usually indicated by low radar backscatter in SAR images due to specular reflections on the water surface. This effect was proved by comparing radar backscattering coefficients obtained from two space-borne SAR systems, TerraSAR-X and RADARSAT-2, with those obtained from two theoretical scattering models, IEM and Oh model. We observed relatively large, widely distributed water puddles in belt shape along the upper parts of the tidal flat, which were confirmed to be related to the discharge of groundwater. The results of this research suggest that SAR can be a powerful tool for observing and determining the areal distributions of possible groundwater discharge in large tidal flats, which is normally difficult to detect with traditional measurement tools or survey techniques for groundwater discharge. We firmly believe that this technique can reduce significantly the efforts of field work to confirm SGD in tidal flats.     

Ground deformation of Long Valley caldera and Mono Basin,eastern California,mapped by satellite radar interferometry

We have illustrated the key results of the Differential SAR Interferometry (DInSAR) analysis focused on the ground deformation of Long Valley caldera and Mono Basin, eastern California. In particular, we have applied the DInSAR algorithm referred to as Small BAseline Subset (SBAS) approach and processed 21 SAR images, spanning the time interval from 1992 to 2000, acquired from descending arbits by the ERS‐1 and ERS‐2 sensors of the European Space Agency (ESA). The deformation affecting the resurgent dome of Long Valley caldera has been highlighted as well as the previously unreported subsidence of the Pahoa island, located in Mono Lake.     

Capacitive humidity sensors based on a newly designed interdigitated electrode structure

This paper presents a study of capacitive humidity sensors constructed based on a newly designed interdigitated electrode (IDE) structure with a polyimide (PI) sensing layer fabricated using micro-electro-mechanical system (MEMS) technology. The humidity sensors use an IDE with increased height, formed by the surface micromachining of a silicon substrate. The fabricated sensors showed higher sensitivity in variable ambient relative humidity (RH) when compared with the humidity sensors of a conventional IDE since the horizontal electric field lines, generated between the thick electrodes, are confined to the PI sensing layer. The effect of the thickness of the PI layer was also investigated. The fabricated sensors with a 4-μm-thick PI layer showed a higher sensitivity of 37.1 fF/%RH when compared with those of a 2- and 3-μm-thick PI layers, indicating that the properties of the sensors depend on the thickness of the PI layer. This is because the amount of the fringing electric field lines passing through the PI is determined by the PI thickness. In addition, the sensor with the 4-μm-thick PI showed very slight hysteresis with a maximum of 2.87%RH and displayed high stability with a variation range of 0.06 pF.     

Comparison of ERS-2 SAR and Landsat TM imagery for monitoring agricultural crop and soil conditions

Studies over the past 25 years have shown that measurements of surface reflectance and temperature (termed optical remote sensing) are useful for monitoring crop and soil conditions. Far less attention has been given to the use of radar imagery, even though synthetic aperture radar (SAR) systems have the advantages of cloud penetration, all-weather coverage, high spatial resolution, day/night acquisitions, and signal independence of the solar illumination angle. In this study, we obtained coincident optical and SAR images of an agricultural area to investigate the use of SAR imagery for farm management. The optical and SAR data were normalized to indices ranging from 0 to 1 based on the meteorological conditions and sun/sensor geometry for each date to allow temporal analysis. Using optical images to interpret the response of SAR backscatter (σ^o) to soil and plant conditions, we found that SAR σ^o was sensitive to variations in field tillage, surface soil moisture, vegetation density, and plant litter. In an investigation of the relation between SAR σ^o and soil surface roughness, the optical data were used for two purposes: (1) to filter the SAR images to eliminate fields with substantial vegetation cover and/or high surface soil moisture conditions, and (2) to evaluate the results of the investigation. For dry, bare soil fields, there was a significant correlation (r²=.67) between normalized SAR σ^o and near-infrared (NIR) reflectance, due to the sensitivity of both measurements to surface roughness. Recognizing the limitations of optical remote sensing data due to cloud interference and atmospheric attenuation, the findings of this study encourage further studies of SAR imagery for crop and soil assessment.     

Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

Discrimination of vegetation types in alpine sites with ALOS PALSAR-, RADARSAT-2-, and lidar-derived information

Natural vegetation monitoring in the alpine mountain range is a priority in the European Union in view of climate change effects. Many potential monitoring tools, based on advanced remote sensing sensors, are still not fully integrated in operational activities, such as those exploiting very high-resolution synthetic aperture radar (SAR) or light detection and ranging (lidar) data. Their testing is important for possible incorporation in routine monitoring and to increase the quantity and quality of environmental information. In this study the potential of ALOS PALSAR and RADARSAT-2 SAR scenes' synergic use for discrimination of different vegetation types was tested in an alpine heterogeneous and fragmented landscape. The integration of a lidar-based canopy height model (CHM) with SAR data was also tested. A SPOT image was used as a benchmark to evaluate the results obtained with different input data. Discrimination of vegetation types was performed with maximum likelihood classification and neural networks. Six tested data combinations obtained more than 85% overall accuracy, and the most complex input which integrates the two SARs with lidar CHM outperformed the result based on SPOT. Neural network algorithms provided the best results. This study highlights the advantages of integrating SAR sensors with lidar CHM for vegetation monitoring in a changing environment.     

Surface movements in Bologna (Po Plain — Italy) detected by multitemporal DInSAR

We studied the surface deformations affecting the southeastern sector of the Po Plain sedimentary basin, in particular the area of Bologna. To this aim an advanced DInSAR technique, referred to as DInSAR-SBAS (Small BAseline Subset), has been applied. This technique allows monitoring the temporal evolution of a deformation phenomenon, via the generation of mean deformation velocity maps and displacement time series from a data set of acquired SAR images. In particular, we have processed a set of SAR data acquired by the European Remote Sensing Satellite (ERS) sensors and compared the achieved results with optical levelling measurements, assumed as reference. The surface displacements detected by DInSAR SBAS from 1992 to 2000 are between 10 mm/year in the historical part of Bologna town, and up to 59 mm/year in the NE industrial and agricultural areas. Former measurements from optical levelling referred to 1897 show 2-3 mm/year vertical movements. This trend of displacement increased in the second half of the 20th century and the subsidence rate reached 60 mm/year. We compared the more recent levelling campaigns (in 1992 and late 1999) and DInSAR results from 1992 to 1999. The standard deviation of the difference between levelling data, projected onto the satellite Line Of Sight, and DInSAR results is 2 mm/year. This highlights a good agreement between the measurements provided by two different techniques. The explanation of soil movements based on interferometric results, ground data and geological observations, allowed confirming the anthropogenic cause (surface effect due to the overexploitation of the aquifers) and highlights a natural, tectonic, subsidence.     

Detection and tracking of oil slicks on sun-glittered visible and near infrared satellite imagery

The use of the visible and near infrared (VNIR) bands of MODIS and MERIS imaging sensors acquired in sunglint conditions to reveal smoothed regions such as those affected by oil pollution is investigated. The underlying physical mechanism that enables oil slick detection is based on the modification of the surface slope distribution composing the wind-roughened sea due to the action of mineral oils. The role of sunglint as the chief mechanism that allows the imaging of oil slick features with VNIR wavelengths is assessed for selected case studies in the Mediterranean Sea. The high rate of acquisition and the frequent occurrence of MODIS and MERIS imagery affected by sunglint, especially in low-latitude seas, can thus significantly contribute to increase the actual oil slick detection capability offered by synthetic aperture radar (SAR) systems. We also show how the combined observations from any of the microwave and optical sensors permit the slick to be followed during its movement. Finally, a simulation study specific to the Mediterranean Sea was carried out in order to demonstrate the feasibility of such an approach supporting SAR observations.     

TORNADO: omnistereo video imaging with rotating optics

One of the key techniques for vision-based communication is omnidirectional stereo (omnistereo) imaging, in which stereoscopic images for an arbitrary horizontal direction are captured and presented according to the viewing direction of the observer. Although omnistereo models have been surveyed in several studies, few omnistereo sensors have actually been implemented. In this paper, a practical method for capturing omnistereo video sequences using rotating optics is proposed and evaluated. The rotating optics system consists of prism sheets, circular or linear polarizing films, and a hyperboloidal mirror. This system has two different modes of operation with regard to the separation of images for the left and right eyes. In the high-speed shutter mode, images are separated using postimage processing, while, in the low-speed shutter mode, the image separation is completed by optics. By capturing actual images, we confirmed the effectiveness of the methods.