eCognition在土地利用项目中的应用

主要介绍了eCognition对高分辨率卫星影像进行地物分类的技术方法。并以深圳铁岗水库附近地区为例,说明该技术在土地利用分类中应用的可行性和潜力,为高分辨率卫星影像在地物分类中的有效应用提供了新的技术手段。     

遥感自动提取海岸线方法

利用遥感技术确定海岸线位置的问题受到关注由来已久,就其在国内外的研究现状做了介绍,利用小波边缘检测算子提取出黄河三角洲河口区2004年Landsat TM图像的海岸线位置;在分析小波算子与传统边缘提取方法相比的优点的同时,并就其存在的不足提出了今后的研究重点。     

顾及光谱畸变的高分辨率图像融合方法研究

使用高分辨率遥感图像进行像素级图像融合,在图像小波分解时,通过计算不同分解层数下得到的融合图像的熵来决定图像的小波分解层数;在图像小波重建时,引入局部相关系数,并在不同的分解层上设置不同的阈值进行有选择的高频系数替换,实现图像的像素级融合。并使用Quickbird全波段与多光谱数据进行试验,得到了分辨率高、光谱畸变微小的彩色融合图像。     

SAR图像对地定位的严密共线方程模型

SAR图像对地定位是解决SAR遥感信息在哪里的根本问题,它是遥感应用和处理的重要步骤。作者在分析现有几种SAR图像对地定位模型的基础上,根据SAR成像的严格几何关系导出SAR图像对地定位的严密共线方程模型。首先根据斜距图像的近地点斜距和远地点斜距推导中心投影等效焦距的计算公式,然后详细推导并给出斜距图像转化成严密中心投影图像时涉及的图像改化公式,最后根据实际星载SAR图像定位的精度对比,证明严密共线方程模型是可行的,而且其定位精度要明显优于传统的近似共线方程模型。     

IKONOS影像生产1∶10 000地理信息产品的研究

简要介绍了IKONOS卫星遥感影像适用于地理信息产品生产的特点,然后通过试验生产,并与传统的航片相比较,详细分析了利用IKONOS影像作为数据源生产1∶10000基础信息产品在精度、生产流程、工作效率、生产周期、外业工作量和价格等方面的情况。     

Design of high precision horizontal control network for large-scale hydropower project

IntroductionThe design of high precision horizontal controlnetwork for large-scale hydropower project toconstruct control network and measure deforma-tion of monitoring network.It can be also divid-ed into horizontal control network and verticalcontrol ne…     

半参数模型稳健估计及其应用

在半参数模型估计中,均假设观测误差服从正态分布。当观测量含有粗差时,粗差对参数和非参数估计的影响是不可忽略。基于此,首先在总结线性参数模型稳健估计基本理论的基础上,论述了M估计权因子的确定方法。然后提出了半参数模型稳健估计方法,并导出半参数模型(广义)补偿最小二乘稳健估计的基本公式。最后通过两个模拟算例验证了其估计方法的有效性。     

机载WIDAS数据的Landsat卫星反照率初步验证

随着精细化监测的需求,中高空间分辨率的地表反照率产品逐渐成为气候模型的主要输入。目前,中高空间分辨率反照率产品的验证主要基于地表站点的通量塔观测数据,区域机载飞行数据的验证依然相对较少。因此,本文基于区域机载数据验证Landsat反照率产品。针对内蒙古自治区根河森林试验区所获取的机载红外广角双模式成像仪(WIDAS)多角度反射率数据,应用BRDF原型反演算法估算其反照率,分析了应用机载数据验证中高空间分辨率反照率产品的潜力。2016年内蒙古根河森林试验区机载WIDAS飞行多角度观测的可用多角度范围为25°,以前的研究表明BRDF原型反照率反演算法表现出对小观测角度的反照率反演结果的鲁棒性。因此,机载WIDAS反照率在一定程度可用于星载反照率的验证。首先,基于核驱动模型和各向异性平整指数(AFX)提取了试验区4种MODIS二向性反射分布函数(BRDF)原型;然后,将其作为先验知识应用到根河森林WIDAS机载数据的反照率反演中;最后,用WIDAS反照率和单个地面通量塔观测的反照率对Landsat卫星数据的反照率进行初步验证。验证结果表明Landsat反照率与WIDAS反照率结果较为一致,但略有低估,总体均方根误差(RMSE)约为0.02,偏差为0.0057。在多角度观测范围较小时,BRDF原型的反照率反演算法可为星载地表反照率的验证提供了一种有效的验证手段。     

An improved building detection approach using L-band POLSAR two-dimensional time-frequency decomposition over oriented built-up areas

The objective of this study is to efficiently extract detailed information about various man-made targets in oriented built-up areas using polarimetric synthetic aperture radar (POLSAR) images. This paper develops an improved approach for building detection by utilizing Two-Dimensional Time-Frequency (2-D TF) decomposition. This method performs outstandingly in distinguishing between man-made and natural targets based on the isotropic behaviors, frequency-sensitive responses, and scattering mechanisms of objects. The proposed method can preserve the spatial resolution and exploit the advantages of TF decomposition; specifically, the exact outlines of buildings can be effectively located, and more types of features (e.g., flat roofs, roads, and walls that are oblique to the radar illumination) can be distinguished from forests in complex built-up areas by 2-D TF decomposition. The coarser-resolution subaperture images that are produced in the azimuth direction, which correspond to different looking angles, are beneficial for detecting man-made structures with main scattering centers oriented at oblique angles with respect to the radar illumination. In the range direction, the obtained subaperture images, which correspond to various observation frequencies, can be helpful in distinguishing flat roofs and roads from forests. This method was successfully implemented to analyze both NASA/JPL L-band AIRSAR and L-band EMISAR data sets. The building detection results of the proposed method exhibit a significant improvement over those of other methods and reach an overall accuracy over 80%, with approximately 20% higher than the accuracies of K-means clustering and the entropy/alpha-Wishart classifier and approximately 10% higher than the accuracy of the support vector machine method. Moreover, building details can be precisely detected, obliquely oriented buildings can be identified, and the distinction between buildings and forests is significantly improved, as both visually and statistically indicated. This method is highly adaptable and has substantial application value.     

基于kernel分析方法的河南省城镇密集区研究

基于kernel城镇集聚区密度的计算方法,借助于ArcGIS软件的计算和空间分析功能,分析河南省城镇密集区的历史演变和空间变化,进一步探讨河南省城镇密集区和中原城市群的关系。