利用高程信息结合彩色遥感航空影像提取建筑物目标

利用地物的高程信息结合对应的真彩色遥感影像,通过面向对象的方法对试验区建筑物目标信息进行提取。结果表明,基于以面向对象分类技术为核心的eCognition能够较快速准确地完成图像中非建筑物影响因子的剔除,以及建筑物的提取。解译总体精度达到了79.1%,与人工目视解译相比大幅度提高了解译效率,相对于传统分类方法大幅度提高了解译精度。

遥感技术在优化地震测线部署中的应用

复杂地区由于其特殊性,往往信噪比很低,数据处理难度大,而提高数据信噪比,重点应放在野外数据采集阶段。以准噶尔盆地南缘霍10井山地三维地震测线部署为例,论述了利用高精度遥感技术提供的精细地质信息、数字高程信息、地貌信息、地表岩性等信息优化地震部署,可以改善地震资料品质,提高施工效率,降低勘探成本。

基于GIS系统DEM数据的雷达地杂波建模与仿真

根据雷达建模与仿真需求,提出了一种基于地理信息系统(GIS)数字高程(DEM)数据的地杂波建模方法。针对GIS的DEM 数据分辨率不满足雷达分辨率要求这一难点,由 GIS的DEM 数据计算雷达波束照射区域的起伏度和粗糙度,将地形分为平原、森林、丘陵和高山四种地貌,而后针对不同地貌分别采用平均分布、Weibell分布、LogNormal分布和 Pareto分布对相应的地貌建模,所产生随机序列的幅度按照地貌起伏范围设定、长度依照雷达分辨率和波束覆盖区域确定。地貌的后向散射系数采用“修正 Morchin 模型计算”。分别采用实际DEM地貌数据和仿真地貌数据计算地杂波,实验结果验证了该方法的有效性。

Scale-Dependent Representations of Relief Based on Wavelet Analysis

Automatic generalization of geographic information is the core of multi_scale representation of spatial data,but the scale_dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale_dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.

Distributed Modeling of Extraterrestrial Solar Radiation Over the Rugged Terrains of Pakistan

In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripheral national territories,little or no solar radiation data,non-satisfactory sunshine hours data,and low quality of ground observed cloud cover data create a situation in which the spatial modeling of Extraterrestrial Solar Radiation(ESR) and its ground parameterization got sufficient scope.The Digital Elevation Model (DEM) input into Geographic Information System (GIS) is a compatible tool to demonstrate the spatial distribution of ESR over the rugged terrains of the study domain.For the first time,distributed modeling of ESR is done over the rugged terrains of Pakistan,based on DEM and ArcGIS..Results clearly depict that the complex landforms profoundly disrupt the zonal distribution of ESR in Pakistan.The screening impact of topography is higher on spatial distribution of ESR in winter and considerably low in summer.The combined effect of topography and latitude is obvious.Hence,the model was further testified by plotting Rb (ratio of ESR quantity over rugged terrain against plane surface) against azimuth at different latitudes with different angled slopes.The results clearly support the strong screening effect of rugged terrain through out the country especially in Himalayas,Karakoram and Hindukush (HKH),western border mountains and Balochistan Plateau.This model can be instrumental as baseline geospatial information for scientific investigations in Pakistan,where substantial fraction of national population is living in mountainous regions.

Orthorectification of IKONOS and Impact of Different Resolution DEM

IKONOS image has been wildly used in city planning, precision agriculture and emergence response. However, the accuracy of IKONOS Geo product is limited due to distortion caused by terrain relief. Orthorectification was performed to remove the distortion and the impact of different DEM on orthorectification were evaluated. 38 ground control points (GCPs) and 25 independent check points (ICPs) were collected. DEMs were generated from 1∶10 000 and 1∶50 000 topographic maps. Results show that RMS error at the check points is 1.554 0 m using DEM generated from 1∶10 000 topographic map, which can meet the accuracy requirement of IKONOS Precision product (1.9 m RMSE). While RMS error is 2.572 4 m using DEM generated from 1∶50 000 topographic map.

A COM-based Framework for Management,Analysis and Visualization of Large Scope Digital Elevation Models

This paper presents a component object model (COM) based framework for managing, analyzing and visualizing massive multi-scale digital elevation models (DEMs). The framework consists of a data management component (DMC), which is based on RDBMS/ORDBMS, a data analysis component (DAC) and a data render component (DRC). DMC can manage massive multi-scale data expressed at various reference frames within a pyramid database and can support fast access to data at variable resolution. DAC integrates many useful applied analytic functions whose results can be overlaid with the 3D scene rendered by DRC. DRC provides view-dependent data paging with the support of the underlying DMC and organizes the potential visible data at different levels into rendering.

基于稀疏表示的失真卫星立体图像全参考质量评价

针对建筑物检测特定应用,提出一种基于稀疏表示的失真立体图像全参考质量评价方法。首先构建了一种新的失真卫星立体图像数据库,使用角点检测和数字表面模型的高程信息进行建筑物检测,并根据失真图像检测角点变化,提出检测准确率指标来表示图像的失真程度;然后提出一种基于稀疏表示的客观评价模型,其分别提取原始图像和失真图像的尺度不变特征转换和二进制稳健不变尺度特征进行字典学习;利用稀疏表示测量原始图像和失真图像之间的相似性,得到4个质量分数;最后通过支持向量回归融合4个质量分数得到最终的客观评价值。在构建的数据库上进行测试,实验结果表明,皮尔逊线性相关系数值高于0.90,斯皮尔曼等级相关系数值高于0.87,与现有的评价方法相比,所提方法能更好地反映卫星立体图像的质量。