利用多光谱卫星遥感和深度学习方法进行青藏高原积雪判识     

阚希  张永宏  曹庭  王剑庚  田伟 《测绘学报》2016,45(10):1210-1221

青藏高原积雪对全球气候变化十分重要,针对已有积雪遥感判识方法中普遍采用的可见光与红外光谱数据易受复杂地形与高海拔影响,导致青藏高原地区积雪判识精度较低的问题,提出了一种基于多光谱遥感与地理信息数据特征级融合的积雪遥感判识方法:以风云三号卫星可见光与红外多光谱遥感资料与多要素地理信息作为数据源,由地面实测雪深数据与现有积雪产品交叉筛选出样本标签,构建并训练基于层叠去噪自编码器(SDAE)的特征融合与分类网络,从而有效辨识青藏高原遥感图像中的云、积雪以及无雪地表。经地面实测雪深数据验证,该方法分类精度显著高于使用相同数据源的FY-3A/MULSS积雪产品,略高于国际主流积雪产品MOD10A1与MYD10A1,并且年均云覆盖率最低。试验结果表明该方法可有效地减少云层对积雪判识的干扰,提升分类精度。  相似文献   

历史数据和强化学习相结合的低频轨迹数据匹配算法     

孙文彬  熊婷 《测绘学报》2016,45(11):1328-1334

针对低频(采样间隔大于1min)轨迹数据匹配算法精度不高的问题,提出了一种基于强化学习和历史轨迹的匹配算法HMDP-Q,首先通过增量匹配算法提取历史路径作为历史参考经验库;根据历史参考经验库、最短路径和可达性筛选候选路径集;再将地图匹配过程建模成马尔科夫决策过程,利用轨迹点偏离道路距离和历史轨迹构建回报函数;然后借助强化学习算法求解马尔科夫决策过程的最大回报值,即轨迹与道路的最优匹配结果;最后应用某市浮动车轨迹数据进行试验。结果表明:本文算法能有效提高轨迹数据与道路匹配精度;本算法在1min低频采样间隔下轨迹匹配准确率达到了89.2%;采样频率为16min时,该算法匹配精度也能达到61.4%;与IVVM算法相比,HMDP-Q算法匹配精度和求解效率均优于IVVM算法,16min采样频率时本文算法轨迹匹配精度提高了26%。  相似文献   

思维导图方法的教学实践     

刘智敏  独知行  于胜文  韩晓冬 《测绘科学》2016,41(9):186-190

思维导图在国内外已有多项研究证明思维导图在促进学生创新思维发展上有作用。在测绘类学科的高校教学中引入思维导图这种学习和工作方法,用在测绘本科教学改革中的讲座责任制授课模式上,通过在测绘本科教学方法改革的需求分析、应用实践和学生调查统计,得出结论:思维导图用于测绘类高校教学中,有利于提高学生创新思辨和自主学习能力,有助于达到以"能力"为核心的测绘专业人才培养目标。  相似文献   

基于MOOC集结思想的地图学自主学习模式探讨     

李东颖  焦永清  闫浩文  王莉霞  杨军义 《测绘科学》2016,41(11):206-210,170

大型开放型网络课程(MOOC)是国际高等教育发展的新趋势,对高校课程学习的影响极大。该文对MOOC深入剖析之后发现其集结思想可以运用到高等教育教学中,并以地图学课程教学为例,针对目前地图学课程教学存在的问题,借助MOOC集结思想改进地图学教学,以学生自主学习促进地图知识掌握,以天水师范学院地理科学专业学生为教学对象进行了教学实践,制订了详细的教学计划和实践环节。在实施过程中发现,该方法提高了学生对地图学的学习兴趣,得到了较好的效果。  相似文献   

Grid pattern recognition in road networks using the C4.5 algorithm   总被引：1，自引：0，他引：1  

Jing Tian  Fei Gao  Feng Zhao 《制图学和地理信息科学》2016,43(3):266-282

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.  相似文献   

Temporal replication of the national land cover database using active machine learning     

Galen J. Maclaurin 《地理信息系统科学与遥感》2016,53(6):759-777

Regional and national level land cover datasets, such as the National Land Cover Database (NLCD) in the United States, have become an important resource in physical and social science research. Updates to the NLCD have been conducted every 5 years since 2001; however, the procedure for producing a new release is labor-intensive and time-consuming, taking 3 or 4 years to complete. Furthermore, in most countries very few, if any, such releases exist, and thus there is high demand for efficient production of land cover data at different points in time. In this paper, an active machine learning framework for temporal updating (or backcasting) of land cover data is proposed and tested for three study sites covered by the NLCD. The approach employs a maximum entropy classifier to extract information from one Landsat image using the NLCD, and then replicate the classification on a Landsat image for the same geographic extent from a different point in time to create land cover data of similar quality. Results show that this framework can effectively replicate the land cover database in the temporal domain with similar levels of overall and within class agreement when compared against high resolution reference land cover datasets. These results demonstrate that the land cover information encapsulated in the NLCD can effectively be extracted using solely Landsat imagery for replication purposes. The algorithm is fully automated and scalable for applications at landscape and regional scales for multiple points in time.  相似文献   

Student Perceptions of a Recreation Trail Assignment as a Valuable Learning Experience for Geography Undergraduates     

Jo Beth Mullens 《The Journal of geography》2016,115(6):244-255

Charging undergraduate geography students with the task of designing a recreational trail in their local community offers an engaging experiential opportunity with potential to advance geographic learning in a real-world setting. This article presents an assignment in which students were asked to develop a recreational trail proposal for an undeveloped local conservation area and the results of a survey that asked the students to reflect and report upon the educational value of this experience one year later. Results of the survey validated the assignment's lasting value to the students across the cognitive, psychomotor, and affective learning domains.  相似文献   

一种开源软件集成的空间矢量数据在线采集方法     

洪安东  黄泽纯  井燕武  张倩宁  张瑞芳 《地理信息世界》2016,(2):97-100

空间数据是GIS应用的基础,经济高效地从网络获取空间数据具有重要意义。文章主要研究了网络地图环境下利用Web GIS技术和开源软件实现空间矢量数据在线采集和数据库存储的方法和技术。并且使用Google Map API、Ajax技术和Apache、My SQL开源软件开发一个基于Web平台的原型系统,实现了基于网络地图的矢量数据的在线获取、数据库存储、在线显示和数据库访问服务接口等功能,为获取空间数据提供了一种新方法。  相似文献   

Prediction of Seaward Slope Recession in Berm Breakwaters Using M5' Machine Learning Approach     

Alireza Sadat Hosseini  Mehdi Shafieefar 《海洋工程》2016,(1):19-32

In the design process of berm breakwaters, their front slope recession has an inevitable rule in large number of model tests, and this parameter being studied. This research draws its data from Moghim’s and Shekari’s experiment results. These experiments consist of two different 2D model tests in two wave flumes, in which the berm recession to different sea state and structural parameters have been studied. Irregular waves with a JONSWAP spectrum were used in both test series. A total of 412 test results were used to cover the impact of sea state conditions such as wave height, wave period, storm duration and water depth at the toe of the structure, and structural parameters such as berm elevation from still water level, berm width and stone diameter on berm recession parameters. In this paper, a new set of equations for berm recession is derived using the M5'' model tree as a machine learning approach. A comparison is made between the estimations by the new formula and the formulae recently given by other researchers to show the preference of new M5'' approach.  相似文献   

基于CART算法的三维成矿预测研究——以安徽白象山矿区为例          下载免费PDF全文

李志辉  赵萍  李晓晖  袁峰  周宇章 《地质科学》2018,(4):1314-1326

把地质大数据和人工智能技术引入矿产资源定量评价及成矿预测体系中,提高了海量地质数据的有效信息挖掘,弥补了传统方法的不足。本文基于白象山矿区基础地质资料和物化探成果资料,利用三维地质体建模技术和三维空间分析技术,量化三维控矿因素,建立了一种基于CART 算法的三维成矿预测模型。通过在白象山矿区的实验表明：该模型能较好的定位已知矿体,并且预测出在已知矿体北部、东部、东北部、西部、南部和东南部具有较高的成矿概率,可圈定找矿靶区。该模型将地质大数据应用于找矿勘探工作,具有纯数据驱动、预测精度高、预测结果可靠等优点。研究发现,该模型的预测效果与训练数据集的数量、矿控因素提取、决策树深度等有关。  相似文献