A new technology of passive millimeter-wave aperture synthetic camera is an imaging technology that can receive the radiation from observed objects and does not require a millimeter-wave source and have potential applications. It offers very significant advantages of simpler system, lower cost, real-time imaging, higher reso- lution and near-all-weather capability etc. as well as has arisen attentions of scientific and military surveillance. In this paper, aimed at circumstances of earth observations of airborne, the principles of passive millimeter-wave aperture synthetic imaging are introduced, the results of simulated computation show that: (a) In cases of 10000 meter height, 100 MHz width of frequencies and±300 field of view, the emitted power from terrain is 9.0 watt for 8 mm waveband and 68.0 watt foe 3mm waveband respectively. Such a radiation power is suffi- cient for airborne remote sensing. (b) The coverage of visibility function and angle resolution foe Y-type of an- tenna arrays is better than T-type of antenna arrays. The results of this paper are helpful for design of systems for passive millimeter-wave aperture synthetic imaging of airborne.
Today' s object recognition systems has become very good at recognition isolated objects. However, recognition in scenes with multiple objects is still problematic. Teeming objects consist of a number of similar sub-objects with definite distribution. In this paper, a promising recognition algorithm is presented for a kind of teeming objects in aerial images. The recognition is a three-stage process. First, a group of texture features are selected for figure ground separation. With these features, the raw aerial images are segmented using maxi- mum likelihood classification method and the regions of interest are extracted. Finally, the distribution features are used to locate and recognize the teeming targets. We present a new pruning algorithm to locate the teeming targets based on its distribution features, which consuming less time than other algorithms. Experiment results review that the selected texture features can differentiate the sub-objects from nature background effectively. Recognizing experiments based on a set of aerial images indicate that the algorithm can recognize the teeming targets from complex natural scene effectively and efficiently.
The statistical separability is used to explore the scale effect of remote sensing data classification and to determine optimal resolution in this paper. The Landsat TM image with 30m spatial resolution is up-scaled to different spatial resolutions. The stratified random sampling method was used to select the training samples at 30m resolution, and the location of training samples were saved as masks to take training samples for up-scaled images so that training samples for images at every resolution are at same location. The transformed divergence and J-M distance of training samples at every resolution were calculated for every class pair, and were plotted versus the spatial resolution. The landscape metrics of the land cover in the study area were calculated Analysis to these plots showed that, for different pair of classes, the change pattern of statistical separability with spatial resolution is quite different. The spatial pattern between pair of classes has significant effect on the statistical separability pattern of change with spatial resolution and can be used to explain the underlying reasons for the change patterns. For our experimental data, the average statistical separability reached to the maximum at the 60m spatial resolution, which means that finer spatial resolution not necessary lead to high separability. :
With the development of airborne SAR, especially the deep research of high resolution and InSAR, it is very necessary for airborne SAR to use the information of precise 3D position, velocity, acceleration and atti-tude for motion compensation. And all data need precise synchronization. High precision dynamic GPS can sup-ply the information well. So high precision dynamic GPS becomes one of the important department of airborne new pattern SAR. The article mainly discusses the application of high precision dynamic GPS in the advanced irborne new pattern SAR . The research is useful to the practical development of the airborne SAR. Key words:
Coastline detection in Synthetic Aperture Radar (SAR) images plays a significant role in marine appli-cations, such as autonomous navigation, geographic mapping, etc. Level set algorithm is an edge detectionmethod, based on visual characteristic of human being. Level set algorithm has been attracting much attention of research and application in coastline detection due to its detection effectiveness and quality of anti-noise.However, when applied to high resolution image, the level set algorithm will cost a lot of time to detect the con-tour because of its complicated iterative manner. In this paper, we present an improved method based on levelset algorithm used especially in SAR images. Firstly, the coarse detection procedure is processed using level setalgorithm in a low resolution image to obtain the contours closing to the real coastline of the image. Then, thecoarse contour in the low resolution image is projected to the high resolution image and the coastline detectioncontinued by level set algorithm in a finely way to obtain the final fined results. Experimental result usingRadarsat Scan SAR image indicates that this novel improved method based on level set algorithm can enhancethe detection speed, compared with the original level set algorithm, without the loss of detection effectiveness.
Automatic interpretation of synthetic aperture radar (SAR) images is one of the most interesting andimportant application fields in image processing. Focusing on the medium resolution SAR images and combiningwith the previous algorithms, a novel technique to detecting ship targets from coastal regions in a fully automat-ic way is proposed in this paper. This paper presents current progress made on the detection model. In thismethod, sea regions and land regions were detected firstly according to the corresponding decimation algorithmand thresholding technique. Then the land regions can be masked out from the SAR image based on mappingprinciple of the image datas. And In order to obtain a high reliability and robustness, the processed processingchain detects possible targets by first searching in parallel for bright spots, i.e. potential ship bodies. There-fore, the sea image with ship targets is processed with maximum entropic algorithm, and we can extract the re-gions of interest which contain candidate ship targets. And the authentic ship targets were eventually detectedby utilizing the method of feature matching. Finally, for later classification and recognition we calculate the fea-ture parameters of every ship. Experimental results on 50 different SAR images are given to demonstrate thatthis method can automatically detect ship targets from SAR images with high efficiency.
Change detection with Synthetic Aperture Radar (SAR) image has wide application prospect, but anaccurate registration is a very important precondition for most of the present change detection methods. Howev-er, the technology of image registration is still a hard work in the area of image processing especially for SARimage, so it is rather difficult to find a good SAR image registration method which should have both strongadaptability and high accuracy. This will restrict the application of change detection for SAR image to some ex-tent. Thinking of the problem of registration accuracy for the present change detection methods, and accordingto the characteristics of man-made target in SAR image, a new change detection method with SAR image ispresented in this paper, which is based on target detection. In this method, the change detection process is di-vided into two steps. First, the man-made targets in the images will be detected; second, we will compare thesimilarity between the relative position relationships of the man-made targets which have been detected from thetwo images, then the change of images will be decided from this result. As the change detection process ismainly dependent on the relative position relationships of the detected targets, the requirement to the accurateregistration can be greatly reduced. The experimental result shows that this method is capable of detecting im-age changes with rough registration accuracy.
8-day composite MODIS temperature product MOD11A2 and 16-day composite MODIS NDVI prod-uct MOD13A2 were combined to construct Ts-NDVI space from which the TVDI(Temperature VegetationDryness Index) was obtained. Every 16-day soil moisture in August and September in XinJiang was retrievedby using the TVDI. When compared with the topsoil moisture measured simultaneously with satellite in thefield, we found that TVDI and soil moisture were correlated strongly, and TVDI could reflect the topsoil mois-ture status. Based on the information got by the remote sensing,, we then analyzed the spatial and temporalvariations of soil moisture in XinJiang. It was found that the spatial distribution of soil moisture accorded withthe distribution of the annual precipitation and annual average relative humidity in XinJiang and the area withlower soil moisture was increasing during the August to the September.
The data of satellite remote sensing is a good Way to acquire information of the earth' s surface.In thewetland research in Shangri-la county ,Yunnan Province, the water information extraction has been studied byanalyzing spectral characters of Landsat ETM+ digital image and spectral models are established in the article.As the study area is one part of the plateau falling and rising in great distance,there exist quite a lot dark moun-tain shadow on the image that make it more difficult to extract water information.To do this,three methods arerespectively applied to separate water information from background with landsat ETM+ digital image: thresh-old method, combination of difference and threshold method, combination of multispectral relation and thresh-old method. The results show that threshold method could hardly distinguish water from shadows ,becausetheir spectral characters are alike on some bands,the water information extracted varies greatly according to dif-ferent selected threshold.Water information extracted by combining difference and threshold method is more ac-curate, but some dark mountain shadows has also been extracted. Comparatively,spectral relation methods aremore accurate by applying the principle that the water reflect green strongly and absorbs infrared strongly,aalgrithm such as band2 +and3 and band4 + band5 can increase the difference between shadows and water, socombination of multispectral relation and threshold method eliminate the shadow effectively and extract waterinformation accurately.
Decision tree classification algorithms have significant potential for remote sensing data classification.In this paper, taking TM 1-7 bands as datum, Applying decision tree classification to Peking land cover.Firstly, the reflective characteristics of primary land-use types in this area on this image are studed. Secondly,this paper discussed how to build a decision tree to differentiate lawn, woodland, water bodies, bare land ,Resi-dential area and road step by step. The classified precision can reach 93.3%. The results of this researchshowed that decision trees have several advantages for rmeote sensing applications by virtue of their relativelysimple, explicit, and intuitive classification structure. In addition, this method is flexible and robust with re-spect to general classifications among input features and class labels.Key words:
This paper mainly discusses the ability of information fusion by ETM2～4 band and PAN band fromETM+ images. The fusion images have the high spatial resolution characteristics from the Pan band image andthe spectral information from ETM2-4 band images. The spatial resolution of the fusion result images is lessthan 15 meter, but better than 17.3 meter by comparison with zooming ASTER image at the same region. Thefusion image can have 73% spectral resolution ability also by comparing the NDVIs from ASTER and fusionimages. It is also pointed that the fusion result images depend on he fusion methods also.
In this paper, the concept of Curvilinear Synthetic Aperture Radar (CLSAR) is introduced and thereturned chirp signal data model for CLSAR is described. Based on this model, the principle of three dimension-al target reconstruction of CLSAR is analyzed detailedly. The 2D FFT analysis is conducted in the Cross range-Elevation plane of the curvilinear apertures, and the results show that the traditional FFT-based SAR imag-ing method is no longer practical in the curvilinear apertures situation because of the effect of large side lobe. Asthe substitution of the FFT-based imaging method, the 3D target feature extraction method using RELAX al-gorithm based on spectrum estimation is introduced to solve the sidelobe problem. It has already been provedthat the RELAX algorithm can be used efficiently to estimate the dominant scatters' discrete spectrum parame-ters from the noise and clutter' s continuous spectrum if the targets can be divided into several dominant scatter-s. Furthermore, the computer simulation of the ideal full aperture and several specific curvilinear apertures areconducted. The simulation results show the validities and advantages of the RELAX-based 3D target featureextraction method for CLSAR. And the results also show that the parabolic aperture is the relative optimalchoice among the curvilinear apertures we used in the simulation.
Radar altimeter has become one of the most useful microwave sensing instruments for observing theearth in the past three decades, and the results from several successful missions, such as Geosat、ERS1+2 andTopex,has been widely used in many geodesy field, particularly in ocean topography. Error analysis is one ofthe core techniques in the design of Spaceborne Radar Altimeter, because the altimeter data may be impracticalfor some application cases without adequate precision. Amplitude and phase ripples of the RF system are impor-tant error sources in height measurement. This paper deals with the error issue with the help of the well-estab-lished tool——“paired-echo theory”. Firstly, we consider that the ripples have the sinusoid forms, and then wecan convert these ripples into range side lobes. On the other hand, we establish the form of the side lobe andderive the relationship between side lobes and height bias. In this way we can establish the relationship betweenamplitude (phase) ripples and height bias. And finally, applying this method to a practical system, we can getsome quantitative requirements for the amplitude and phase ripples. These requirements are very critical inradar altimeter design.
The synthetic aperture radar (SAR) is an airborne or spaceborne radar mapping technique for gener-ating high-resolution maps of surface target areas and terrain. Its images usually have big size and contain alarge amount of data. So it is a key problem in SAR image data processing that how to compress the image toreduce data amount effectively so that it can be saved or transmitted conveniently. In recent years, wavelettransform is widely used in the field of image compression. The Spatial-Orientation Tree (SOT) Structure playsa very important role in compression of SAR image based on Wavelet transform. Both the Embedded Zero-treeWavelet (EZW) and the Set Partitioning in Hierarchical Trees (SPIHT) coding schemes utilize the parent-chil-dren relationship in SOT. EZW is a simple, yet remarkably effective, image compression algorithm, have theproperty that bits in the bit stream are generated in order of importance, yielding a fully embedded code. SARimage suffer from speckle noise that seriously degrades image quality and compressibility. Removal of specklenoise can enhance correlations of pixels and compressibility of SAR image. As a very efficient structure to inves-tigate the spatial correlations among wavelet coefficients at different resolutions, SOT has not been well used innoise removal.In this paper we proposed a SOT structure based method, which integrated speckle noise removal andEZW algorithm. Results of compression of large numbers of Airborne SAR images validate the proposedmethod is efficient and better than JPEG and EZW algorithm.
Land surface albedo, which is a fundamental component needed for determining the radiation balanceof the Earth-atmosphere system, is the surface hemispherical reflectivity integrated over the solar spectrum.Briefly said, it is the ratio of the total upwelling irradiance to the total downward irradiance. Given the limit ofexperiment field and instrument equipment, it is very difficult to obtain a great deal of surface measured data.Thereof, in our research, from the point of view that surface albedos are the ratio of flux, surface albedos canbe reversed with less calibrated field synchronous observed data.During the conversion process of surface albdeos, the first is to obtain surface reflectance from remotelysensed data, which can be completed by running 6S atmospheric radiative transfer model; the second is to re-verse surface narrowband albedos, which is fulfilled by MODTRAN model. The outputs of MODTRAN simu-lations are upwelling and downwelling irradiance. The sensor spectral response functions are integrated withthese outputs to generate narrowband albedos; the third is to calculate surface broadband albedos, which is fo-cused on determining the converting coefficients from narrowbands to broadbands under the the linear relation-ship between narrowband albedos and broadband albedos. The spectral distribution of solar irradiance at thesurface is set as the weighting function for comverting the narrowband albedos to broadband albedos in the re-search. The conversion of broadband albedos is fulfilled finally. The simplified surface broadband albedo reversemodel is tested for the west of Inner Mongolia using MODIS image data and synchronous observed surface spec-tral data based on the above conversion algorithm. The results show that the method is convenient and feasibleunder a specific surface/atmospheric condition.
Polarimetric synthetic aperture radar (SAR) interferometry, which combines SAR polarimetry withSAR interferometry, can improve the measurement precision of interferometric SAR and enhance the ability toexplain the scattering mechanisms of targets. So it has become an important direction of SAR application devel-opment. In the area coverd by rich vegetations, the confusion of scatting centers induces considerable loss of co-herence, which is an important element of interferometry and tightly related with the quality of interferometry.To reduce the loss of coherence, polarimetric information was induced in SAR interferometry because of its po-tential ability of separating scatting centers. Traditional Pol-InSAR flow worked on this problem during thegeneration of interferometric phase maps. It ignored a question that the loss of coherence can influence the reg-istration as well because the coherence is one of estimate values for registration. As we all know, registration isan important prepositive key step, its quality is crucial for interferometry. All bad factors of registration shouldbe reduced. Considering above, a new method for registration of Pol-InSAR images combined with coherenceoptimization is brought forward. The coherence optimization can separate scatting centers, it will availably re-duced the loss of coherence induced by confusion of scatting centers. An experiment on SIR-C/SLC compleximages demonstrates the validity of this method.
The Advanced Synthetic Aperture Radar (ASAR) instrument on board the ENVISAT satellite ex-tends the mission of the Active Microwave Instrument (AMI) Synthetic Aperture Radar (SAR) instrumentsflown on the European Remote Sensing (ERS) Satellites ERS-1 and ERS-2. ASAR, operating at C-band, en-sures continuity with the image mode (SAR) and the wave mode of the ERS-1/2 AMI. It features enhancedcapability in terms of coverage, range of incidence angles, polarization, and modes of operation. In rainy andcloudy areas in southern china which are the major crop production areas in china, the regular acquisition of op-tical remote sensing data(MODIS,TM) is hampered by frequent cloud cover and rain. We analyzed ASAR dataapplication potential taking Zhao Qing of Guang Dong Province as experimental area in which many kind ofcrop, including rice and banana, are grown. We used two ASAR dataset which are both ASAR alternating po-larization precision image over the area in research. One, acquired on 13 June of 2003, had imaging swath ofIS5 and polarization of HH/HV. The other, acquired on 2 July of 2003, had imaging swath of IS5 and polar-ization of VV/HH. We derived the backscattering coefficients of main ground objects in the images and com-pared them with the provious research results. The result shows that ASAR data can find a wide use in manyfields such as crop growth .monitoring, ocean and ship detection.
This paper is based on the concept and characteristic of Remote Sensing classifications, combining thepredecessors' fruits, then sums up all the methods (including traditional and new classifications, such as: objec-t-oriented, sub-pixel classification etc.), detailed analyzes and evaluates each of them. Afterwards, it attemptsto analyze the methods and the arithmetic of classifications, such as principles, effects, functions and limitedconditions. It also compares the excellence, the defects and adapting conditions of each method, and summa-rizes all of the methods in different views. Finally, summary and prospect are described, in order to give guid-ance to practical work.
The grassland desertification is becoming more serious, caused the fragile grassland ecology to worsenfurther. Under this kind of situation, the author summarizes the definition of desertification, and describes thestudy progress of the desertification remote sensing information in the Chinese and international in recent years.On this basis, the interpreter of the desertification remote sensing information is expatiated in the paper fromthe choice of the data source of remote sensing, the choice of the wave band, the Geometric Correction of theremote sensing image, the information strengthen of remote sensing image, mask technology, separate technol-ogy and image interpreter and so on. And on the basis of summarizing desertification remote sensing evaluationindex in Chinese and international, compare synthetically, the vegetation cover, the bare sand percentage andsoil character are to evaluation index of desertification. The conclusion is it is feasible to separate the type of de-sertification, and their distributing, and their vegetation cover to utilize the remote sensing image. The applica-tion is less about the mix-pixel separate technology in the interpreter of desertification remote sensing informa-tion. The author will extract the desertification information form remote sensing image by the separate technol-ogy and mask technology, and attempt to explore a kind of pattern process method to extract the characteristicof desertification truly. Meanwhile, the idea of the analyzing from mathematical method is less in the researchof desertification remote sensing application at present, that is very meaningful if the figure analyzing is appliedto remote sensing image information analysis of the desertification.This text aims at exploring one kind is reasonable and meeting with the new thinking of land remote sens-ing information analysis of the desertification in the future at present.
A review of microwave remote sensing data and its application of monitoring the snow ice. In this pa-per, monitoring sea ice by the microwave remote sensing is summarized in detail. While the progress is intro-duced by utilizing the technology into studying of the snow ice and freeze/thaw in China. In the end, the au-thor explained the application foreground of microwave remote sensing data
