Combined Method of Datum Transformation Between Different Coordinate Systems

The similarity transformation model between different coordinate systems is not accurate enough to describe the discrepancy of them.Therefore,the coordinate transformation from the coordinate frame with poor accuracy to that with high accuracy caanot guarantee a high precision of transformation.In this paper,a combined method of similarity tranformation and regressive approximating is presented.The local error accumulation and distortion are taken into consideration and the precision of coordinate system is improved by using the recommended method.     

The study on automatic registration of InSAR images

Interferometric Synthetic Aperture Radar (InSAR) allows production of high resolution DEM and detection of small earth motions using multiple pass SAR data sets obtained by remote sensing satellite. But the whole process has not yet reached sufficient robustness to warrant automated DEM production as commonly produced by stereovision with optical images. The automatic algorithm for precision registration is one of the bottlenecks in InSAR data processing. In this paper, an automatic approach with multi-step image matching algorithm is presented. All procedures are automatically implemented. The experiment is carried out successfully with SIR-C/L-band InSAR data. The triangular piecewise rectification is also advanced in reducing local distortion between the images and processing the large scene image. The primary result has prospect in the precision registration for the repeat-track InSAR data and reveals the potential of the presented automatic strategy.     

Neural network based on rough sets and its application to remote sensing image classification

This paper presents a new kind of back propagation neural network(BPNN) based on rough sets,called rough back propagation neural network (RBPNN).The architecture and training method of RBPNN are presented and the survey and analysis of RBPNN for the classification of remote sensing multi-spectral image is discussed.The successful application of RBPNN to a land cover classification illustrates the simple computation and high accuracy of the new neural network and the flexibility and practicality of this new approach.     

应用FY-1D气象卫星监测雾(英文)

FY-1D is the second national operation meteorological satellite of China, and is much better compared to monitoring fog. However, research on monitoring fog using FY-1D is very few. In this paper, based on the typical FY-1D data, a fog＇s spectral characteristics in the different channels are analyzed using the histogram analysis method, and a method of monitoring fog using FY-1D is suggested. The results indicate that the 1st and 4th channels are the representative channels of FY-1D for the identification of fog. In the 1st channel, the fog is with uniform veins, smooth top, and clear-cut boundary, and its albedo is 20%-48%. In the 4th channel, the fog＇s brightness and temperature is 272-289K, and the difference value between the fog＇s and the ground surface＇s is not more than 6K.     

An Urban Open Space Extraction Method： Combining Spectral and Geometric Characteristics

This paper introduces an advanced method based on remote sensing and Geographic Information System for urban open space extraction combining spectral and geometric characteristics. From both semantic and remote sensing perspectives, a hybrid hierarchy structure and class organization of open space are issues and mapped from one to another. Based on per-pixel and segmentation mechanism separately, two classification approaches are performed. Owing to prior of spatial aggregation and spectral contribution, the segmentation-based classification exhibits its superiority over a pixel-based classification. Finally a GIS-based post procedure is hired to eliminate some unsuitable open space components in both spatial and numerical constraints on the one hand, and separate open space some fabrics from fused remote sensing classes by defining their Shape Index on the other hand. The case study of Beer Sheva based on ASTER data proves this method is a feasible way for open space extraction.     

Image relaxation matching based on feature points for DSM generation

In photogrammetry and remote sensing, image matching is a basic and crucial process for automatic DEM generation. In this paper we presented a image relaxation matching method based on feature points. This method can be considered as an extention of regular grid point based matching. It avoids the shortcome of grid point based matching. For example, with this method, we can avoid low or even no texture area where errors frequently appear in cross correlaton matching. In the mean while, it makes full use of some mature techniques such as probability relaxation, image pyramid and the like which have already been successfully used in grid point matching process. Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.     

Study on gis data directly integrated into image processing

The basic properties to be dealt with ,when considering initially the research needs related to the integration of remote sensing (RS) information into a geographic information system (GIS),are many-sided.The primary combination of remote sensing and GIS is mainly realized by the transforms of data structure .Because of its own limitations,there is an urgent need to investigate the integration of RS and GIS in higher levels.In this paper,we discuss the different types of combinations of RS with GIS,and propose that GIS data should be directly brought into image processing from the beginning.A tentative idea of how to use the method of granularity to study the common processing unit of RS and GIS is described.The example for the determination of granularity of spatial data processing related to run-length-code line is also given.     

Production of high-resolution remote sensing images for navigation information infrastructures

This paper introduces the image fusion approach of multi-resolution analysis-based intensity modulation (MRAIM) to produce the high-resolution multi-spectral images from high-resolution panchromatic image and low-resolution multi-spectral images for navigation information infrastructure. The mathematical model of image fusion is derived according to the principle of remote sensing image formation. It shows that the pixel values of a high-resolution multi-spectral images are determined by the pixel values of the approximation of a high-resolution panchromatic image at the resolution level of low-resolution multi-spectral images, and in the pixel valae computation the M-band wavelet theory and the d trous algorithm are then used. In order to evaluate the MRAIM approach, an experiment has been carried out on the basis of the IKONOS 1 m panchromatic image and 4 m multi-spectral images. The result demonstrates that MRAIM image fusion approach gives promising fusion results and it can be used to produce the high-resolution remote sensing images required for navigation information infrastructures.     

Investigation of Image Fusion Between High—Resolution Image and Multi—Spectral Image

On the basis of a thorough understanding of the physical characteristics of remote sensing image,this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm.The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China The experimental results show that a perfect image fusion can be built up by using the image analytical solution and reconstruction in the image frequency domain based on the physical characteristics of the image formation.The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.     

Quasi-quantitative relationship between soil moisture and polarization characteristics

Besides amplitude, frequency and phase, the polarization is another basic property of the electromagnetic wave. In the remote sensing field, the polarization is mainly applied in active detection systems of radar and lidar. This paper presents the quantitative relationship between soil moisture and polarization signatures in a certain type of soil in a farm. And this relationship is expected to be introduced on agriculture and hydrology ultimately. The experiments were performed both in the laboratory and the field. Soil samples with different moisture contents were measured at three wavebands on visible spectrum, and at several viewing angles in the plane of incidence. The polarization signature was indicated by the multi-band and multi-angle degree of linear polarization (DOLP) in this paper. The soil moisture were divided into five levels according to the properties of DOLP curves, namely, the quasi-quantitative relationship between soil moisture and its polarization signature were established. The percentages of soil moisture of the five levels are: ≤10%, 10%-20%, 20%-40%, 40%-56% and 56%, respectively. Although this division for soil moisture is on a rather large scale, it will meet the precision of application agricultural and hydrologic remote sensing.     

CBERS-02B卫星WFI成像在轨MTF估算与图像MTF补偿

基于高分辨率图像对比法, 利用同一卫星平台上空间分辨率19.5m的CCD相机图像对CBERS-02B卫星上空间分辨率为258m的 WFI成像仪图像进行在轨MTF(modulate transfer function)测量, 获得WFI(wide field imager)相机沿轨、跨轨与45o方向的MTF曲线, 并计算出3个方向的线扩展函数LSF(line spread function), 获得3个方向的有效半带宽。结果表明WFI相机红波段跨轨、沿轨与45o方向的有效半带宽, 即有效瞬时视场, 分别为1.188, 1.165与1.281个像元, 近红外波段为1.258, 1.195与1.326个像元。基于获得的MTF, 利用维纳滤波法对WFI图像进行补偿, 部分恢复了WFI图像的细部信息。     

渤海近岸水体漫衰减系数Kd(490)遥感反演模型

Irrigated land is one of the most important parts in land cover classification system, but until now it has seldom been reported about extracting it from remote sensing data and monitoring its dynamic change. The existing researches are focused on the land use-cover change (LUCC) and the irrigated area mapping, so the study on extracting irrigated land is much more important. On the basis of close relationship between water deficit index (WDI) and soil water content, this paper firstly combines two neighbor NDVI and the surface-air temperature (Ts-Ta) and conforms one Vegetation Index Temperature (VIT). It makes the timely incomparable WDI comparable and then computes the change of WDI during the monitored period. Secondly it infers the change of soil water. Thirdly it removes the rainfall’s influence under some assumption and extracts the irrigated land of the survey area. Results show that comparing with census data all the deviation is below 7% in the survey area except Shanxi province, which means that the extracted results are comparable with census data. Extracted irrigated land mainly distributes around rivers, lakes, and reservoirs or on the irrigated regions and oasises. The results are consistent with the centralized region which has abundant irrigated land known before. The results are checked elementarily using TM images. All the precisions are above 70% except in Shanxi province. The precision in Xinjiang municipality is the highest.     

基于CBERS-02卫星数据的参数定量反演算法及软件设计

针对中巴资源(CBERS-02)卫星数据的定量化处理技术进行比较概括的阐述.在中国卫星应用中心已有的产品体系基础上,考虑CBERS卫星多波段摄像机、宽视场成像仪及红外多光谱扫描仪数据定量化的特点,建立了CBERS-02卫星数据定量化产品体系.并对其中的主要定量化过程与产品反演算法进行描述,具体包括CBERS-02数据的场地辐射定量标和交叉辐射定标结果、云监测算法、大气校正算法、地表反射率和反照率以及以此为基础的得到的植被指数等相关定量化产品算法.介绍了定量化处理CBERS-02卫星数据的软件,为CBERS-02数据的应用提供了技术支撑.     

CBERS-02B卫星遥感影像的区域网平差

针对中巴资源一号卫星(CBERS-02B)卫星遥感影像姿态角误差较大的特点,提出了利用区域网平差方法提高其对地目标定位精度的策略和具体计算过程。首先对参与平差的每景影像选取4个地面控制点进行影像姿态角常差检校,然后采用与地形无关方案解求各自的RPC参数,最后选取带仿射变换项的有理函数模型(RFM)进行多重覆盖影像的区域网平差。对两个地区的0级CBERS-02B单条CCD立体影像对的区域网平差试验表明,对地目标定位的平面和高程精度均达到了±3个像元的水平,且高程精度明显优于平面精度。相对于常规的卫星遥感影像区域网平差方法,平面和高程精度均有明显提升,几乎达到国外同等高分辨率卫星遥感影像的几何定位精度。这说明中国卫星遥感影像亦具有较好的几何定位潜力,在区域网平差之前进行系统误差预改正是必要和可行的。     

鄱阳湖HJ-1A/B卫星CCD影像大气校正研究

以准同步的Terra/MODIS反演的气溶胶为辅助,采用FLAASH模型对2009-10-24鄱阳湖HJ-1A/B卫星CCD影像进行大气校正处理。结果表明,大气影响可以被有效去除,在水体遥感反射率较高的红、绿波段,大气校正精度较高,平均相对误差分别为13.4%和9.8%;而在水体遥感反射率较低的近红外、蓝波段,大气校正精度较低,这可能与波段不同的信噪比和陆地邻近像元效应有关。     

高分辨率卫星遥感影像姿态角系统误差检校

简要介绍高分辨率卫星遥感影像的严格几何处理模型,提出较为严密的影像姿态角系统误差检校模型。通过对SPOT-5、CBERS-02B两种卫星遥感影像的试验证实模型的正确性和方法的有效性。对影像姿态角系统误差进行补偿后,可明显提高卫星遥感影像对地目标定位的精度,且优于影像姿态角常差检校的效果,目标点平面定位精度达到了±(2～3)像素的水平。     

敦煌场地CBERS-02 CCD传感器在轨绝对辐射定标研究

对资源一号卫星02星（CBERS-02）,为深入其定量化分析,定期在敦煌绝对辐射校正场地进行了地面同步测量,开展了更新在轨绝对辐射定标研究。另外,运用地表反射率和大气光学特性参量数据,计算出CBERS-02CCD传感器4个波段的绝对辐射标定系数。同时,利用2004年8月25目的Landsat-5 TM图像数据对CBERS-02 CCD传感器的辐射特性进行交叉定标,验证分析了CBERS-02 CCD传感器场地绝对辐射定标的基本特性及其可靠性。另外,为CBERS后续星的传感器改进,提供了分析参量。     

CBERS-02 WFI的辐射交叉定标及其对植被指数的作用

本文以MODIS作为参考传感器，对CBERS-02星上的WFI传感器进行辐射交叉定标，得到WFI两个波段TOA辐亮度、表观反射率的增益与计数值偏移量，两个波段的计数值偏移量分别为42和21个DN左右。利用定标结果计算图像上另一均匀区的表观反射率。与MODIS反演的表观反射率比较验证。WFI与MODIS第1波段的表观反射率相差3．6％，第2波段相差-3．6％。检验结果说明，本文得到辐射交叉定标系数的精度能满足定量化应用的要求。为了说明辐射定标对植被指数的影响，本文选择5个实验区，比较分析了实验区图像辐射定标前后的NDVI。当WFI的DN值扣除定标得到的数字计数值偏移量后，DN值的NDVI与表观反射率的二次非线性拟合度可达99％。另外。WFI辐射定标前后的NDVI、RVI与MODIS反演的NDVI、RVI的比较分析说明，WFI辐射定标后表观反射率值的植被指数与MODI反演植被指数较接近，而且两个传感器RVI的差异小于NDVI的差异。     

基于CBERS-02B星数据的土地利用/覆被类型监测应用研究

研究了基于CBERS-02B星数据的土地利用/覆被类型监测方法,综合评价了基于像素分类法和面向对象法的应用精度和效果.结果表明,基于像素分类法和面向对象分类法分类精度基本可满足土地宏观监测精度,在保证影像质量和训练样本质量情况下,分类精度可达到 80%以上,研究成果可为土地利用宏观监测提供技术参考.     

CBERS-02B多光谱数据在城市不透水面 估算中的可用性研究

以厦门岛为研究区,以CBERS-02B的CCD影像为数据源,采用基于可变端元的线性光谱混合模型估算了城市不 透水面组分含量,并探讨了该方法的实现过程与优势。通过端元评估确定了研究区的４个典型端元,即高反射不透水 面、低反射不透水面、高反射土壤和植被。在此基础上,以高、低反射不透水面端元的组分含量对城市不透水面含量 进行估算。精度评价结果显示：基于可变端元的方法要优于一般带全约束法;而在混合像元分解过程中加入全色波段 （band5）有助于提高模型估算精度,使得在像元尺度的精度与采用Landsat的已有报道相近,而在土地利用单元尺度实 现了对城市不透水面的无偏估计。研究实例也表明,尽管目前CBERS-02B数据在辐射定标和地理定位等方面还有待改 进,通过采用适当的处理过程和技术手段,依然能利用该数据对城市不透水面进行有效估算。