一种改进的APAP影像匹配算法     

张冬梅  卢小平  苗沛基  周雨石  马靓婷 《测绘通报》2020,(3):123-128

针对无人机影像匹配时易出现影像重影、透视失真和耗时较长等问题，本文提出了一种改进的APAP算法。该算法首先利用SIFT算法选取特征点，通过改进RANSAC算法去除误匹配点；然后根据APAP算法对影像进行网格划分，求每个网格的单应性矩阵，并对单应性矩阵进行线性化；最后根据线性化的单应性矩阵进行影像匹配，单应性矩阵的线性化不仅对影像匹配时产生的重影现象有较好的削弱作用，而且能减少非重叠区域的透视失真。试验结果表明，本文方法在匹配效率和匹配效果方面效果显著。  相似文献   

植被光合有效辐射吸收比率遥感研究进展     

田定方  范闻捷  任华忠 《遥感学报》2020,24(11):1307-1324

植被光合有效辐射吸收比率FPAR（Fraction of absorbed Photosynthetically Active Radiation）反映了植被冠层的光学特性，是表征植被光合作用水平和生长状态的重要参量，因此成为全球变化研究中多种过程模型的重要输入参数。随着定量遥感研究的深入和新型传感器的使用，从区域到全球尺度上的FPAR遥感估算方法不断提出，多样化的遥感FPAR产品越来越多地应用于碳循环、能量循环、生产力估算及作物估产等研究领域。本文梳理了遥感估算的植被光合有效辐射的相关概念和算法，并着重对过去十年间遥感估算FPAR的新进展进行了系统总结和探讨。研究表明，近年来FPAR遥感的研究工作一方面聚焦于对现有算法的改进与各类型产品的验证，更多的研究则侧重于FPAR概念体系的拓展，叶片、叶绿素水平的FPAR估算，直射光、散射光的FPAR建模等新方向逐渐成为研究热点。  相似文献   

模拟退火算法在室内定位中的应用     

杨志龙 《北京测绘》2020,(3):356-360

随着室内定位技术的广泛应用,如何高效、精准、低成本地实现室内定位尤为重要。本文分析了现有室内定位算法的不足,结合室内定位问题与模拟退火算法的特点,通过室内定位问题的数学抽象与建模,提出一种基于模拟退火算法的室内定位方法,给出了可行解邻域的选取方式与二范数的目标函数。实验结果表明该算法可实现高效、精准、低成本的定位效果,并且具有较好的鲁棒性和平差效果。  相似文献   

倾斜摄影实景模型悬空地物处理方法   总被引：1，自引：1，他引：0  

王哲奇  徐柳华  俞志强 《测绘通报》2020,(5):111-114

为更好解决传统倾斜摄影实景模型悬空地物处理过程中对三维采编环境的过度依赖，本文提出了一种基于倾斜摄影三角网络分析的实景模型悬空地物处理技术方法。该技术方法将三维三角网进行降维处理，通过分析降维后二维三角网节点上边线的辐射特性，快速定位地物边缘点，同时结合聚类分析算法、最小凸边提取等技术方式，实现对悬空地物边界的快速定位、消除。试验选取植被这类悬空地物作为研究对象，验证了文中的技术方法对倾斜摄影实景模型悬空地物处理具有较好的适用性，能极大降低倾斜摄影实景模型数据处理中对三维环境的要求，降低数据处理的难度。  相似文献   

利用三维激光点云重构建筑物模型     

周贻港 《测绘通报》2020,(3):109-112

随着三维激光点云数据获取能力的提升，基于三维激光点云进行建筑物模型重建与立面测绘成为工程应用中常用的方法。三维激光点云数据能够体现建筑物丰富和直观的细节信息，然而海量数据处理给建筑物模型构建带来了极大挑战。本文通过对建筑物的三维激光点云数据进行横切得到建筑物轮廓点，并采用基于遗传算法的TSP算法对轮廓点进行处理以获取建筑物各立面的方程系数，最终实现建筑物模型的构建和获取详细的建筑物立面数据。试验结果表明，此方法可以较好地实现LOD1级建筑物模型的构建，进而为更高（LOD3）级别的建筑物模型构建提供依据。  相似文献   

对渐进三角网点云数据滤波算法的改进     

凌晓春 《测绘通报》2020,(10):43-47

针对渐进三角网滤波算法（PTD）进行拓普康LiDAR点云数据处理过程中易将地物点误判为地面点的缺陷，本文提出两种改进方法。一种是采用局部坡度拟合法对PDT算法进行改进，将点云数据按高程值与拟合坡面法求解的拟合高程值的差由小到大进行排序，将为地面点可能性更大的点优先判定，从而获取更加精确的TIN；另一种是引入薄板样条曲线（TPS）插值法，对PTD算法进行改进，将PTD中候选点判断参数改为TPS法中的弯曲能量增长值，从而减少误判。结果表明，使用以上两种改进算法，综合考虑第1类误差和第2类误差影响，在大部分地形特征下比传统PTD算法表现更优，对低矮植被、桥、斜坡等特殊地物的滤波效果更佳。  相似文献   

Crop classification from full-year fully-polarimetric L-band UAVSAR time-series using the Random Forest algorithm     

《International Journal of Applied Earth Observation and Geoinformation》2020

Accurate and timely information on the distribution of crop types is vital to agricultural management, ecosystem services valuation and food security assessment. Synthetic Aperture Radar (SAR) systems have become increasingly popular in the field of crop monitoring and classification. However, the potential of time-series polarimetric SAR data has not been explored extensively, with several open scientific questions (e.g. the optimal combination of image dates for crop classification) that need to be answered. In this research, the usefulness of full year (both 2011 and 2014) L-band fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data in crop classification was fully investigated over an agricultural region with a heterogeneous distribution of crop categories. In total, 11 crop classes including tree crops (almond and walnut), forage crops (grass, alfalfa, hay, and clover), a spring crop (winter wheat), and summer crops (corn, sunflower, tomato, and pepper), were discriminated using the Random Forest (RF) algorithm. The SAR input variables included raw linear polarization channels as well as polarimetric parameters derived from Cloude-Pottier (CP) and Freeman-Durden (FD) decompositions. Results showed clearly that the polarimetric parameters yielded much higher classification accuracies than linear polarizations. The combined use of all variables (linear polarizations and polarimetric parameters) produced the maximum overall accuracy of 90.50 % and 84.93 % for 2011 and 2014, respectively, with a significant increase of approximately 8 percentage points compared with linear polarizations alone. The variable importance provided by the RF illustrated that the polarimetric parameters had a far greater influence than linear polarizations, with the CP parameters being much more important than the FD parameters. The most important acquisitions were the images dated during the peak biomass stage (July and August) when the differences in structural characteristics between most crops were the largest. At the same time, the images in spring (April and May) and autumn (October) also contributed to the crop classification since they respectively provided unique information for discriminating fruit crops (almond and walnut) as well as summer crops (corn, sunflower, and tomato). As a result, the combined use of only four acquisitions (dated May, July, August, and October for 2011 and April, June, August, and October for 2014) was adequate to achieve a nearly-optimal overall accuracy. In light of the promising classification accuracies demonstrated in this research, it becomes increasingly viable to provide accurate and up-to-date crops inventories over large areas based solely on multitemporal polarimetric SAR.  相似文献   

基于最大稳定极值区域仿射不变特征的无人机影像匹配算法研究     

陈钟鸿 《测绘与空间地理信息》2020,(3):215-217,220,224

无人机影像匹配是无人机影像技术应用中的一个重要研究领域,对其展开探讨具有十分重要的意义。本文围绕最大稳定极值区域的仿射不变特征,研究一种新式的无人机影像匹配计算方法,经实验验证,应用该算法能够取得良好的影像匹配效果。  相似文献   

A center-based modeling approach to solve the districting problem     

Yunfeng Kong  Yanfang Zhu  Yujing Wang 《International journal of geographical information science》2019,33(2):368-384

This article deals with the districting problem arising in applications such as political districting, police patrol area delineation and sales territory design. The aim of districting is to group basic areal units into geographic districts such that some set of criteria are satisfied, with basic criteria being district balance, compactness and contiguity. This article proposes a center-based mixed-integer linear programming model to solve the districting problem. Given the central units of districts, the model optimizes weighted objectives of district balance and compactness while satisfying contiguous constraints on districts. The performance of the model was tested using three study areas with 297, 324 and 1297 areal units, respectively. Experimentation shows that, using the district centers identified by a multistart weighted K-medoids algorithm, the model instances can be solved optimally or near-optimally. Compared with local search-based algorithms, the center-based approach outperforms metaheuristics such as simulated annealing, variable neighborhood descent, iterative local search and old bachelor acceptance search in terms of solution quality.  相似文献   

Assessing radial transmissivity variation in heterogeneous aquifers using analytical techniques          下载免费PDF全文

Cem B. Avci  A. Ufuk Sahin 《水文研究》2014,28(23):5739-5754

Pumping tests are one of the most commonly used in situ testing techniques for assessing aquifer hydraulic properties. Numerous researches have been conducted to predict the effects of aquifer heterogeneity on the groundwater levels during pumping tests. The objectives of the present work were as follows: (1) to predict drawdown conditions and to estimate aquifer properties during pumping tests undertaken in radially symmetric heterogeneous aquifers, and (2) to identify a method for assessing the transmissivity field along the radial coordinate in radially symmetric and fully heterogeneous transmissivity fields. The first objective was achieved by expanding an existing analytical drawdown formulation that was valid for a radially symmetric confined aquifer with two concentric zones around the pumping well to an N concentric zone confined aquifer having a constant transmissivity value within each zone. The formulation was evaluated for aquifers with three and four concentric zones to assess the effects of the transmissivity field on the drawdown conditions. The specific conditions under which aquifer properties could be identified using traditional methods of analysis were also evaluated. The second objective was achieved by implementing the inverse solution algorithm (ISA), which was developed for petroleum reservoirs to groundwater aquifer settings. The results showed that the drawdown values are influenced by a volumetric integral of a weighting function and the transmissivity field within the cone of depression. The weighting function migrates in tandem with the expanding cone of depression. The ability of the ISA to predict radially symmetric and log‐normally distributed transmissivity fields was assessed against analytical and numerical benchmarks. The results of this investigation indicated that the ISA method is a viable technique for evaluating the radial transmissivity variations of heterogeneous aquifer settings. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献