Spot Revisited: Accuracy Assessment, Dem Generation and Validation from Stereo Spot 5 Hrg Images

SPOT 5 HRG Level 1A and 1B stereo scenes covering Zonguldak testfield in north-west Turkey have been analysed. They comprise the left and right image components with base to height ratio of 0·54. The pixel size on the ground is 5 m. The bundle orientation was executed by the PCI Geomatica V9.1.4 software package and resulted in 3D geopositioning to sub-pixel accuracies in each axis provided that at least six control points were used in the computation. Root mean square error (rmse) values and vectors of residual errors for Levels 1A and 1B are similar, even for different control and check point configurations. Based on the scene orientation, Level 1A and 1B digital elevation models (DEMs) of the testfield have been determined by automatic matching and validated by the reference DEM digitised from the 1:25 000 scale topographic maps, interferometric DEMs from Shuttle Radar Topography Mission (SRTM) X- and C-band SAR data and the GPS profiles measured along the main roads in the testfield. Although the accuracies of reference data-sets are too similar to the generated SPOT DEMs, these are the only high quality reference materials available in this area. Sub-pixel height accuracy was indicated by the comparison with profile points. However, they are in favourable locations where matching is always successful, so such a result may give a biased measure of the accuracy of the corresponding DEMs.     

基于影像匹配的自发地理信息道路精度评价与改善

针对无矢量参考数据自发地理信息道路精度难以评价的问题,提出了一种基于影像匹配的道路精度评价方法。首先提取影像与自发地理信息中的道路交叉口作为控制点,并将对应的交叉口进行匹配,以同名控制点的均方根误差作为自发地理信息的道路精度;然后以两组控制点分别构建Delaunay三角网,利用两组控制点的对应关系对每个三角网进行仿射变换,从而实现对自发地理信息道路的几何纠正,以提高其精度。最后以郑州市的Open Street Map道路数据进行试验,结果表明本文算法能够有效提高自发地理信息的道路精度。     

Urban DEM generation,analysis and enhancements using TanDEM-X

This paper analyzes the potential of the TanDEM-X mission for the generation of urban Digital Elevation Models (DEMs). The high resolution of the sensors and the absence of temporal decorrelation are exploited. The interferometric chain and the problems encountered for correct mapping of urban areas are analyzed first. The operational Integrated TanDEM-X Processor (ITP) algorithms are taken as reference. The ITP main product is called the raw DEM. Whereas the ITP coregistration stage is demonstrated to be robust enough, large improvements in the raw DEM such as fewer percentages of phase unwrapping errors, can be obtained by using adaptive fringe filters instead of the conventional ones in the interferogram generation stage. The shape of the raw DEM in the layover area is also shown and determined to be regular for buildings with vertical walls. Generally, in the presence of layover, the raw DEM exhibits a height ramp, resulting in a height underestimation for the affected structure. Examples provided confirm the theoretical background. The focus is centered on high resolution DEMs produced using spotlight acquisitions. In particular, a raw DEM over Berlin (Germany) with a 2.5 m raster is generated and validated. For this purpose, ITP is modified in its interferogram generation stage by adopting the Intensity Driven Adaptive Neighbourhood (IDAN) algorithm. The height Root Mean Square Error (RMSE) between the raw DEM and a reference is about 8 m for the two classes defining the urban DEM: structures and non-structures. The result can be further improved for the structure class using a DEM generated with Persistent Scatterer Interferometry. A DEM fusion is thus proposed and a drop of about 20% in the RMSE is reported.     

基于资源三号测绘卫星DSM的精度评估研究

作为我国首颗民用立体测绘卫星数据产品,ZY-3 DSM对于我国地学分析具有极其重要的作用。本文在顾及地貌情况前提下,选取云南省高海拔山区为试验区,辅以1∶10 000野外实测地形图DEM为参考值,将分辨率为15 m的ZY-3 DSM与90 m的SRTM DEM从高程精度和地形精度进行较为全面的数据质量比较。结果表明:ZY-3 DSM在高程精度和地形精度均有更好的表现。总体看来,ZY-3 DSM数据质量更高,具有更广泛的利用价值。     

Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor

Bracken fern is an invasive plant that presents serious environmental, ecological and economic problems around the world. An understanding of the spatial distribution of bracken fern weeds is therefore essential for providing appropriate management strategies at both local and regional scales. The aim of this study was to assess the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa. To achieve this objective, the results obtained from Landsat 8 OLI were compared with those derived using the costly, high spatial resolution WorldView-2 imagery. Since previous studies have already successfully mapped bracken fern using high spatial resolution WorldView-2 image, the comparison was done to investigate the magnitude of difference in accuracy between the two sensors in relation to their acquisition costs. To evaluate the performance of Landsat 8 OLI in discriminating bracken fern compared to that of Worldview-2, we tested the utility of (i) spectral bands; (ii) derived vegetation indices as well as (iii) the combination of spectral bands and vegetation indices based on discriminant analysis classification algorithm. After resampling the training and testing data and reclassifying several times (n = 100) based on the combined data sets, the overall accuracies for both Landsat 8 and WorldView-2 were tested for significant differences based on Mann-Whitney U test. The results showed that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy (80.08% and 87.80% for Landsat 8 OLI and WorldView-2 respectively). Additionally, the use of derived vegetation indices as a standalone data set produced the weakest overall accuracy results of 62.14% and 82.11% for both the Landsat 8 OLI and WorldView-2 images. There were significant differences {U (100) = 569.5, z = −10.8242, p < 0.01} between the classification accuracies derived based on Landsat OLI 8 and those derived using WorldView-2 sensor. Although there were significant differences between Landsat and WorldView-2 accuracies, the magnitude of variation (9%) between the two sensors was within an acceptable range. Therefore, the findings of this study demonstrated that the recently launched Landsat 8 OLI multispectral sensor provides valuable information that could aid in the long term continuous monitoring and formulation of effective bracken fern management with acceptable accuracies that are comparable to those obtained from the high resolution WorldView-2 commercial sensor.