Quality Assessment Of Digital Surface Models Generated From IKONOS Imagery

The growing applications of digital surface models (DSMs) for object detection, segmentation and representation of terrestrial landscapes have provided impetus for further automation of 3D spatial information extraction processes. While new technologies such as lidar are available for almost instant DSM generation, the use of stereoscopic high-resolution satellite imagery (HRSI), coupled with image matching, affords cost-effective measurement of surface topography over large coverage areas. This investigation explores the potential of IKONOS Geo stereo imagery for producing DSMs using an alternative sensor orientation model, namely bias-corrected rational polynomial coefficients (RPCs), and a hybrid image-matching algorithm. To serve both as a reference surface and a basis for comparison, a lidar DSM was employed in the Hobart testfield, a region of differing terrain types and slope. In order to take topographic variation within the modelled surface into account, the lidar strip was divided into separate sub-areas representing differing land cover types. It is shown that over topographically diverse areas, heighting accuracy to better than 3 pixels can be readily achieved. Results improve markedly in feature-rich open and relatively flat terrain, with sub-pixel accuracy being achieved at check points surveyed using the global positioning system (GPS). This assessment demonstrates that the outlook for DSM generation from HRSI is very promising.     

Hyper Redundancy for Accuracy Enhancement in Automated Close Range Photogrammetry

A generic network design in close range photogrammetry is one where optimal multi-ray intersection geometry is obtained with as few camera stations as practicable. Hyper redundancy is a concept whereby, once the generic network is in place, many additional images are recorded, with the beneficial impact upon object point precision being equivalent to the presence of multiple exposures at each camera position within the generic network. The effective number of images per station within a hyper redundant network might well be in the range of 10 to 20 or more. As is apparent when it is considered that a hyper redundant network may comprise hundreds of images, the concept is only applicable in practice to fully automatic vision metrology systems, where it proves to be a very effective means of enhancing measurement accuracy at the cost of minimal additional work in the image recording phase. This paper briefly reviews the network design and accuracy aspects of hyper redundancy and illustrates the technique by way of the photogrammetric measurement of surface deformation of a radio telescope of 26 m diameter. This project required an object point measurement accuracy of σ  = 0·065 mm, or 1/400 000 of the diameter of the reflector.     

旅游生态环境容量的经济学探讨

在总结旅游环境容量研究进展的基础上，提出了研究旅游环境容量意义及其概念体系，并就影响旅游环境容量的关键性因子－旅游生态环境容量进行了分析，运用经济学的理论和方法，提出了引起旅游生态环境容量的深层原因是外部不经济性，最后就为了实现资源环境的可持续发展，应该从法律、行政，经济、社会等角度对社会各利益加以协调，构建了有效的制度平台和相应的措施，使外部成本内部化，并提出了解决这些问题的具体对策和建议。     

高精度推求正高的两种方法

论述了高精度推求正高的两种方法 ,并对正高精度的推估及其在模型上的试算也作了讨论 ,对于海拔为 5 0 0 0m的高山 ,正高的误差一般不超过± 1 0cm ,这与距青岛水准原点达数千公里的西部高山 (原 )处正常高的精度也比较接近     

缺少控制点的卫星遥感对地目标定位

从单线阵推扫式传感器的成像机理出发，利用6个卫星轨道开普勒参数和3个传感器姿态角建立了推扫式卫星遥感影像坐标与其地面点在地心坐标系下的坐标关系式，即构像方程。按照所建立的构像方程，对某地区一景SPOT-5影像进行对地目标定位，获得了实地上83．392m的平面精度；利用单个地面控制点对卫星轨道开普勒参数和传感器姿态实施调整后，目标定位精度提高到14．217m。试验证实，所建立的构像方程是正确的,在卫星遥感对地目标定位中有较好的应用前景。     

地图数字化数据处理的相关平差与精度分析

根据地图数字化坐标转换方法、转换所得地面坐标平差方法 ,得到数字化数据处理的几种方案 ,对不同方案的计算结果进行比较 ,讨论了相关性对平差结果的影响 ,并对数字化数据的精度评定进行了分析     

遥感数据的遗传-超平面分割算法

在传统的采用超平面作为判别边界的分割方法中，使用统计学的方法确定类判别界面，当区域间的统计值大于区域内的统计值时，就会出现类判决界面难于确定的问题。遗传算法的特点是进行全局优化搜索，利用这种算法优势可以解决传统算法难以解决的超平面空间定位问题，从而解决类判决界面的确定问题。通过EOS／MODIS图像数据的分割对该方法作了详细的介绍，其分类精度明显高于统计学分类方法。     

给定内插高程异常值的精度时对GPS水准网格间距的考虑

在已布设GPS水准网的地区，若需内插其中任意一点的高程异常值时，应该了解该内插值的精度。导出了该内插点高程异常值的精度评定方法，并具体给出在我国C级GPS水准网中，该内插点高程异常推估值精度和该地区的地形和栅格重力异常分辨率的数学关系式和实例。在给定内插点高程异常值精度的局域大地水准面时，按不同地形和栅格重力异常分辨率的密度，根据这些数学关系式，可以设计间距合理的B级或C级GPS水准网。     

地形图扫描数字化精度分析

本文分析了地形图扫描数字化的误差来源，讨论了误差控制方法及质量控制指标，探讨了成果数据相对于地形原图的位置精度，具有一定实用价值。     

A statistical approach to evaluating distance metrics and analog assignments for pollen records

The modern analog technique typically uses a distance metric to determine the dissimilarity between fossil and modern biological assemblages. Despite this quantitative approach, interpretation of distance metrics is usually qualitative and rules for selection of analogs tend to be ad hoc. We present a statistical tool, the receiver operating characteristic (ROC) curve, which provides a framework for identifying analogs from distance metrics. If modern assemblages are placed into groups (e.g., biomes), this method can (1) evaluate the ability of different distance metrics to distinguish among groups, (2) objectively identify thresholds of the distance metric for determining analogs, and (3) compute a likelihood ratio and a Bayesian probability that a modern group is an analog for an unknown (fossil) assemblage. Applied to a set of 1689 modern pollen assemblages from eastern North America classified into eight biomes, ROC analysis confirmed that the squared-chord distance (SCD) outperforms most other distance metrics. The optimal threshold increased when more dissimilar biomes were compared. The probability of an analog vs no-analog result (a likelihood ratio) increased sharply when SCD decreased below the optimal threshold, indicating a nonlinear relationship between SCD and the probability of analog. Probabilities of analog computed for a postglacial pollen record at Tannersville Bog (Pennsylvania, USA) identified transitions between biomes and periods of no analog.