Precision rectification of high resolution satellite imagery without ephemeris data

The huge capability of high resolution satellite imageries (HRSI), that includes spatial, spectral, temporal and radiometric resolutions as well as stereoscopic vision introduces them as a powerful new source for the Photogrammetry, Remote Sensing and GIS communities. High resolution data increases the need for higher accuracy of data modeling. The satellite orbit, position, attitude angles and interior orientation parameters have to be adjusted in the geometrical model to achieve optimal accuracy with the use of a minimum number of Ground Control Points (GCPs). But most high resolution satellite vendors do not intend to publish their sensor models and ephemeris data. There is consequently a need for a range of alternative, practical approaches for extracting accurate 2D and 3D terrain information from HRSI. The flexibility and good accuracy of the alternative models demonstrated with KFA-1000 and the well-known SPOT level 1A images. A block of eight KFA-1000 space photos in two strips with 60% longitudinal overlap and 15% lateral sidelap and SPOT image with rational function, DLT, 2D projective, polynomials, affine, conformal, multiquadric and finite element methods were used in the test. The test areas cover parts of South and West of Iran. Considering the quality of GCPs, the best result was found with the DLT method with a RMSE of 8.44 m for the KFA-1000 space photos.     

PASS PROCESSING AND EXTRAPOLATION OF SPOT IMAGE GEOMETRY

A mathematical model for pass processing of SPOT imagery is formulated. It is based on the fact that during one pass, the image data stream from each of the instruments in SPOT forms one single very long image. The geometry of this extended image can thus be rectified with as few control points as for only one scene if orbital constraints and attitude measurements are properly taken into consideration. SPOT imagery is, however, not available as this single long image, but only sectioned into scenes. This creates problems which are accounted for in the solution. The possibility of gaps in the sequence of scenes is also taken into consideration. Extrapolation over gaps is of special interest and, by investigating attitude variability, it is shown that extrapolation is successful over multiple scene gaps which is also verified in a real data test.     

Resolution vs. image quality in pre-tsunami imagery used for tsunami impact models in Aceh,Indonesia

Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Aceh, Indonesia. Previously, a Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30 m) images as well as a combination of 2003 and 2004 higher spatial resolution SPOT (10 m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualties and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using the new LCRs did not perform better than the original one. Particularly casualties models using 2002 LCRs performed better (δAIC > 2) than the more recent Landsat and SPOT counterparts. Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations). Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited.     

Mathematical Modelling and Accuracy Testing of Spot Level 1B Stereopairs

During a project concerned with DEM generation using SPOT stereoscopic imagery, difficulties were experienced when using Level 1B stereopairs for the task. This paper presents a mathematical solution to overcome this problem which has been implemented at the University of Glasgow. Results are included from experimental tests which were carried out over a test field in Jordan using this solution. These tests used five SPOT Level 1B stereopairs together with a single SPOT Level 1A stereopair for comparative purposes. The residual errors at the ground control points and independent check points are given and show that a satisfactory solution was achieved.     

利用MIVIS数据进行遥感图像模拟的研究

本文研究利用机载ＭＩＶＩＳ超光谱成像系统数据,运用光谱模拟,大气改正的方法,定量模拟了ＳＰＯＴ－ＨＲＶ ＸＳ１、ＸＳ２、ＸＳ３的地面反射率图像,并将模拟结果与相应的地面反射率实测值进行了对比。同时对成像系统ＭＴＦ的影响也进行了定量模拟分析。试验结果显示,ＳＰＯＴ图像的模拟值与地面实测值相一致。     

基于SPOT5遥感影像的城市森林叶面积指数反演

本文以上海城市森林为研究对象,采用地面实验与遥感技术相结合方法,开展SPOT5遥感影像在估测城市森林LAI中的应用研究。结果表明,地面实测LAI与三种植被指数均具有很好的线性回归关系,相关系数(r)均大于0.6,其中MSAVI的相关系数最高(r=0.66),其次为MCARI(r=0.64)和NDVI(r=0.62)。说明ND-VI仍受到背景等因素不同程度的影响,而植被指数MSAVI和MCARI,由于能进一步消除土壤背景和叶绿素的影响,对叶面积指数比较敏感,能更好地与叶面积指数建立关系,能更好地用于城市森林叶面积指数的遥感反演。本研究可为快速定量评估城市森林的结构和功能提供依据。     

Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja,Nigeria

This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods. While the pixel-based method was classified with the spectral properties of the images, the object-based approach included an extra layer of land use cadastre data. The classification accuracy results for OBIA show that Landsat 7 ETM, Nigeriasat-1 SLIM and SPOT 5 HRG had overall accuracies of 92, 89 and 96%, respectively, while the classification accuracy for pixel-based classification were 88% for Landsat 7 ETM, 63% for Nigeriasat-1 SLIM and 89% for SPOT 5 HRG. The results indicate that given the right classification tools, the analysis of Nigeriasat-1 data can be compared with Landsat and SPOT data which are widely used for urban land use and land cover analysis.     

Assessment of SPOT 5 and QuickBird remotely sensed imagery for mapping tree cover in savannas

The relative abundance and distribution of trees in savannas has important implications for ecosystem function. High spatial resolution satellite sensors, including QuickBird and IKONOS, have been successfully used to map tree cover patterns in savannas. SPOT 5, with a 2.5 m panchromatic band and 10 m multispectral bands, represents a relatively coarse resolution sensor within this context, but has the advantage of being relatively inexpensive and more widely available. This study evaluates the performance of NDVI threshold and object based image analysis techniques for mapping tree canopies from QuickBird and SPOT 5 imagery in two savanna systems in southern Africa. High thematic mapping accuracies were obtained with the QuickBird imagery, independent of mapping technique. Geometric properties of the mapping indicated that the NDVI threshold produced smaller patch sizes, but that overall patch size distributions were similar. Tree canopy mapping using SPOT 5 imagery and an NDVI threshold approach performed poorly, however acceptable thematic accuracies were obtained from the object based image analysis. Although patch sizes were generally larger than those mapped from the QuickBird image data, patch size distributions mapped with object based image analysis of SPOT 5 have a similar form to the QuickBird mapping. This indicates that SPOT 5 imagery is suitable for regional studies of tree canopy cover patterns.     

SPOT影像像点位移的研究

简要描述了 SPOT卫星影像的有关知识 ,详细研究了地形起伏造成的垂直摄影与倾斜摄影的 SPOT影像的像点位移 ,推导了具体的计算公式 ,并列表给出了地形起伏引起的 SPOT像点位移化算到 1∶ 5 0 0 0 0比例尺上的值 ,概括介绍了纠正 SPOT影像的多项式法与数字微分法 ,最后提出了一种不利用 DEM而能纠正地形起伏较大区域以及具有较大成像视角的 SPOT影像的新方法 ,并给出此方法的实验结果     

基于卫星参数约束条件的SPOT5影像纠正方法

讨论了SPOT5影像的成像模型和纠正方法,提出了成像模型和卫星参数约束条件联合解算的纠正方法,实现了某地区基于卫星参数约束条件的SPOT5影像的纠正。     

西宁市城区扩展对比中遥感影像处理技术的探讨

根据西宁市城区扩展监测对遥感信息提取的需要,采用多种方法将具有较高空间分辨率的SPOT遥感图像和具有多波谱的ETM 遥感图像进行增强及融合试验,结果表明:对ETM 影像先进行锐化处理,再将SPOT影像与锐化后的ETM 信息融合,然后对融合后的影像进行去霾处理得到的影像质量最好。     

SPOT5卫星影像在土地变更调查中的应用

SPOT5因为具有很高的分辨率,在土地变更调查中有着广泛的应用。对于不同的用地类型,SPOT5的分辨能力也不同,本文利用SPOT5影像室内判读发现的变化图斑与实际变化情况进行对比,介绍了SPOT5卫星影像在北京大兴区土地变更调查实际应用中的具体方法。     

Urban land use change detection using sequential aerial photographs and spot image case study: Chiangmai,Thailand

In most of the developing countries, cities are expanding due to urbanization. To cope-up with problem, planners/decision makers need up-to-date physical data base for proper planning and management of the cities. Such data base can be generated quickly through aerial/satellite remote sensing techniques. In this ‘Case Study’ of Chiangmai, Thailand, sequential aerial photographs and SPOT image were used for urban landuse change studies. A comparison was also made for the growth studies of SPOT and aerial photographs. The analysis of study revealed that maximum agriculture land was converted to urban landuse. Urban growth of the city found to be 3.5 times less in case of SPOT results compared to aerial photographs. Urban landuse change was observed all around the city.     

SPOT5城区影像几何精校正点位和面积精度研究

为深入研究二维多项式校正SPOT5城区影像(2.5m)的点位和面积精度,本文分别使用不同精度(GPS点和1∶10000地形图获取的点),不同数量(25和6)的地面控制点校正影像。并利用另外的10个GPS点作为检核点分别检核四种校正结果的点位和面积精度。     

影像融合技术应用于地表分类之探讨

本论文尝试讨论两个主题：主题一为利用主成分分析PCA方法应用于像元阶层资料融合技术的研究。主题二为应用Dempster-Shafer evidence theory方法于特征阶层数据融合技术的研究。在第一个主题中，由于合成孔径雷达的数据具有全偏极特性，在此选取了对植被较为敏感的HV极化合成孔径雷达数据，与具有光谱特性的光学SPOT数据做数据融合处理以利接下来的地物分类。首先，本研究利用小波转换技术来滤除合成孔径雷达斑驳噪声，在接下来融合步骤中，主成分分析出来的第一部分（PCI）是用做完滤除噪声后的合成孔径雷达取代，在数据融合后，进行地物分类是采用最大似然法来分类融合影像。在第二个主题中，利用全偏极雷达数据的极化特性结合SPOT数据的光谱特性，其主要目的是为了增加分类的精确度。首先使用李式滤波器滤除全偏极雷达数据噪声，接下来同样是使用采用最大似然法来分类融合影像，（不同的在于全偏极雷达影像使用Wishart几率分布，在光学影像采用multivariate Gaussian几率分布）将每个类别中每个像元属于某个类别的几率值计算出来，再利用Dempster-Shafer evidence theory来结合这些类别的机率值。最后产生出一张新的分类影像。实验的结果显示分类的精确度比较于未融合的资料都有明显提升的效果，也证明了此两个数据融合方法对于不同数据特性的融合都是很成功的。     

城市绿地信息提取遥感影像尺度效应分析

绿地信息提取精度与影像的空间尺度有关,又与提取目标的特点有关。目前用于绿地信息提取的高分辨率遥感影像主要有QUICKBIRD、IKONOS和SPOT5,不同尺度影像对绿地信息提取精度的影响还缺少相关的研究。本文利用目视解译方法,研究三种尺度遥感影像提取绿地信息的精度。结果表明,三种影像中,由于QUICK-BIRD影像有更详细的空间结构,更适合于城市绿地零星分布特点,在以7层建筑物以下为主的研究区,绿地信息提取精度最高。     

Field-based sub-boundary extraction from remote sensing imagery using perceptual grouping

This study presents an approach for the automatic extraction of dynamic sub-boundaries within existing agricultural fields from remote sensing imagery using perceptual grouping. We define sub-boundaries as boundaries, where a change in crop type takes a place within the fixed geometry of an agricultural field. To perform field-based processing and analysis operations, the field boundary data and satellite imagery are integrated. The edge pixels are detected using the Canny edge detector. The edge pixels are then analyzed to find the connected edge chains and from these chains the line segments are detected using the graph-based vectorization method. The spurious line segments are eliminated through a line simplification process. The perceptual grouping of the line segments is employed for detecting sub-boundaries and constructing sub-fields within the fixed geometry of agricultural fields. Our strategy for perceptual grouping involves the Gestalt laws of proximity, continuation, symmetry and closure. The processing and analysis operations are carried out on field-by-field basis. For each field, the geometries of sub-boundaries are determined through analyzing the line segments that fall within the field and the extracted sub-boundaries are integrated with the fixed geometry of the field.The experimental validation of the approach was carried out on the SPOT4 multispectral (XS) and SPOT5 XS images that cover an agricultural area located in the north-west section of Turkey. The overall matching percentages between the reference data and the automatically extracted sub-boundaries were computed to be 82.6% and 76.2% for the SPOT5 and SPOT4 images respectively. The higher matching percentage of the SPOT5 image is due to the fact that some of the boundaries present in the SPOT5 image were not detected in the coarser resolution SPOT4 image. For the SPOT5 image, of the total 292 fields processed, 177 showed a total agreement between the detected segments and the reference data. For the SPOT4 image, 154 fields showed a total agreement between the detected segments and the reference data.     

SPOT卫星影像的水体提取方法及分类研究

文中分析了水体及其它主要的地物的光谱特征在SPOT曩像中的表征特征，发现大多数地形阴影与水体的光谱特征具有一定的相似性，因而用单一的方法很难有效地提取山区的水体，经过研究，发现用决策树分类方法，在各节点设计不同的分类器，可以有效地提取山区中的水体，由于不同类型的水体其面积，周长，形状等几何特征各有特点，并且与地貌类型有一定的关系，因而可利用水体的空间特征信息，对提取的水体进行分类，其方法也选用决策树分类方法，分类结果令人满意。     

SPOT5与ERS-2卫星影像的联合立体定位

本文将SPOT5与ERS-2卫星影像联立构成一组立体像对,并通过立体定位的方式获取了地面点的三维坐标。根据本文立体像对前方交会的特殊几何图形,推导了立体定位理论精度的计算公式,并利用实验验证了公式的正确性,同时分析了影响立体定位精度的主要因素。实验结果表明,联合具有一定重叠度的SPOT5和ERS-2影像进行立体定位具有很强的可行性,其精度已可以满足部分测绘任务的要求。     

基于SPOT 5卫星影像的空间数据快速更新

介绍了SPOT 5卫星HRG、HRS影像,讨论了SPOT 5影像空中三角测量的方法,以及利用SPOT 5影像进行DEM、DOM、DLG等地理信息产品生产的流程,对比了有、无地面控制纠正SPOT 5影像的精度情况,最后分析了SPOT 5影像在空间数据快速更新中的作用。