Curvedness feature constrained map matching for low-frequency probe vehicle data

Map matching method is a fundamental preprocessing technique for massive probe vehicle data. Various transportation applications need map matching methods to provide highly accurate and stable results. However, most current map matching approaches employ elementary geometric or topological measures, which may not be sufficient to encode the characteristic of realistic driving paths, leading to inefficiency and inaccuracy, especially in complex road networks. To address these issues, this article presents a novel map matching method, based on the measure of curvedness of Global Positioning System (GPS) trajectories. The curvature integral, which measures the curvedness feature of GPS trajectories, is considered to be one of the major matching characteristics that constrain pairwise matching between the two adjacent GPS track points. In this article, we propose the definition of the curvature integral in the context of map matching, and develop a novel accurate map matching algorithm based on the curvedness feature. Using real-world probe vehicles data, we show that the curvedness feature (CURF) constrained map matching method outperforms two classical methods for accuracy and stability under complicated road environments.     

熔融制样-X射线荧光光谱法测定电气石中12种主次量元素

电气石是一类含硼的铝硅酸盐矿物,化学成分复杂、化学稳定性强,不易湿法分解,B_2O_3含量较高,导致其主次量元素的同时测定存在一定困难。本文采用熔融法制样,建立了X射线荧光光谱法测定电气石Na_2O、MgO、Al_2O_3、SiO_2、P_2O_5、K_2O、CaO、TiO_2、V_2O_5、Cr_2O_3、MnO、TFe_2O_3等主次量元素的分析方法。样品与四硼酸锂-偏硼酸锂-氟化锂(质量比为4.5∶1∶0.4)混合熔剂的稀释比例为1∶10,消除了粒度效应和矿物效应;在缺少电气石标准物质的情况下,选择土壤、水系沉积物及多种类型的地质标准物质绘制校准曲线,利用含量与电气石类似的标准物质验证准确度,测定结果的相对标准偏差小于4.2%。采用所建方法测定四种不同类型电气石实际样品,测定值与经典化学法基本吻合。本方法解决了电气石不易湿法分解和硼的干扰问题,测定结果准确可靠,与其他方法相比操作简便,分析周期短。     

基于面向对象分类的稀土开采区遥感信息提取方法研究

离子吸附型稀土矿是我国宝贵的矿产资源,运用遥感影像分类技术提取稀土开采区可以准确地实现对稀土开采状况的监测,但仅利用光谱信息往往难以保证分类精度。本文以江西寻乌稀土矿区为研究区,以IKONOS影像为数据源,应用面向对象分类方法提取了稀土开采区的遥感信息。针对稀土开采区的分布特点,选择基于边缘的分割算法进行影像分割;结合地形信息、光谱信息及几何信息建立规则集,进行特征提取;最后采用隶属度函数法实现面向对象分类,并与传统的光谱角填图分类进行对比分析。研究结果表明,面向对象分类法提取稀土开采区的总体精度为92.49%,Kappa系数为0.857 6,与传统监督分类方法相比有了很大的提高。     

波浪在珊瑚岸礁礁坪上传播变形的数值研究

波浪的传播变形对珊瑚岛礁附近的营养物质输送以及近岸珊瑚沙运动都起着关键的作用,同时也是礁盘顶部建筑物在设计和施工过程中需要重点考虑的因素,因此,对波浪在礁坪上的传播变形进行研究具有重要意义。利用FUNWAVE 2.0数值模型模拟了不规则波浪在不同形状岸礁上的传播变形过程,讨论了礁前斜坡坡度以及珊瑚底面粗糙程度对波浪在礁坪上传播变形的影响。结果显示,随着礁坡斜率增大,不对称度参数绝对值的增长趋势逐渐变缓,波浪在光滑礁坪上的不对称度绝对值要略大于粗糙底面上的值,而不同地形下计算得到的波浪偏度参数则基本相同。说明礁坡坡度对波浪的不对称度特征具有显著影响,礁坪粗糙度的影响则相对较小,而上述因素对波浪偏度的影响则完全可以忽略。给出了考虑这两个影响因素的礁坪区域内波浪偏度和不对称度经验公式。     

小极距高密度电法在城镇供水管漏水检测中的应用

城市地下供水管破损漏水检测,一般使用听音工具和设备来进行,这种需要漏水点传出声音的检测方式,效果往往并不理想。使用一种新的检测方法,无需利用声音,而是通过供水管漏水造成地层电性变化这一特征,使用小极距高密度电法查明管道漏水点位置。该检测方式不仅解决了常规方法难以查明的供水管漏水问题,而且拓展了小极距高密度电法的应用空间。     

Novel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000

The automatic extraction of information content from remotely sensed data is always challenging. We suggest a novel fusion approach to improve the extraction of this information from mono-satellite images. A Worldview-2 (WV-2) pan-sharpened image and a 1/5000-scaled topographic vector map (TOPO5000) were used as the sample data. Firstly, the buildings and roads were manually extracted from WV-2 to point out the maximum extractable information content. Subsequently, object-based automatic extractions were performed. After achieving two-dimensional results, a normalized digital surface model (nDSM) was generated from the underlying digital aerial photos of TOPO5000, and the automatic extraction was repeated by fusion with the nDSM to include individual object heights as an additional band for classification. The contribution was tested by precision, completeness and overall quality. Novel fusion technique increased the success of automatic extraction by 7% for the number of buildings and by 23% for the length of roads.     

Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series

Satellite data holds considerable potential as a source of information on rice crop growth which can be used to inform agronomy. However, given the typical field sizes in many rice-growing countries such as China, data from coarse spatial resolution satellite systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) are inadequate for resolving crop growth variability at the field scale. Nevertheless, systems such as MODIS do provide images with sufficient frequency to be able to capture the detail of rice crop growth trajectories throughout a growing season. In order to generate high spatial and temporal resolution data suitable for mapping rice crop phenology, this study fused MODIS data with lower frequency, higher spatial resolution Landsat data. An overall workflow was developed which began with image preprocessing, calculation of multi-temporal normalized difference vegetation index (NDVI) images, and spatiotemporal fusion of data from the two sensors. The Spatial and Temporal Adaptive Reflectance Fusion Model was used to effectively downscale the MODIS data to deliver a time-series of 30 m spatial resolution NDVI data at 8-day intervals throughout the rice-growing season. Zonal statistical analysis was used to extract NDVI time-series for individual fields and signal filtering was applied to the time-series to generate rice phenology curves. The downscaled MODIS NDVI products were able to characterize the development of paddy rice at fine spatial and temporal resolutions, across wide spatial extents over multiple growing seasons. These data permitted the extraction of key crop seasonality parameters that quantified inter-annual growth variability for a whole agricultural region and enabled mapping of the variability in crop performance between and within fields. Hence, this approach can provide rice crop growth data that is suitable for informing agronomic policy and practice across a wide range of scales.     

基于ASTER与Sentinel-2A融合数据的云南普朗铜矿化蚀变信息提取

云南普朗铜矿区是我国提高战略性金属矿产铜矿资源的主要潜力地段,该矿区位于多云多雨山地高原区,采用传统地面调查方法开展找矿勘查工作受限较大,而遥感技术可在其中发挥重要作用。鉴于此,本研究选取ASTER和Sentinel-2A多光谱遥感数据,在光谱协同统一两种数据源的地表反射率基础上,采用高通滤波(High-Pass Filtering,HPF)的融合方法兼顾两种数据在短波红外波段和可见光近红外波段的优势,获取了具有高空间分辨率和高光谱保真度的ASTER-Sentinel-2A融合数据集;进而利用"比值+主成分分析法"与"主成分分析+能谱-面积法",开展了普朗铜矿区矿化遥感蚀变信息识别,并通过深入分析及野外验证,提出了对普朗铜矿蚀变信息分布特征及找矿潜力地带的新认识:(1)在原蚀变填图工作中判定为青磐岩化带的东部区域,重新进行了蚀变带的划分;(2)东部区域中新划分的钾化硅化带和绢英岩化带,具有较大找矿潜力。本研究可为普朗铜矿找矿勘查提供参考。     

面向自然资源信息提取的多源异构数据融合技术——以汉江流域NDVI数据为例

高时空分辨率的自然资源指标数据对大尺度自然资源动态观测与趋势评估至关重要。大数据时代下的海量多源数据为数据高效融合利用提供了可能。以重构汉江流域归一化植被指数(Normalized Difference Vegetation Index,NDVI)数据为例,搭建了PostgreSQL自然资源时空大数据处理底层架构,集成了数据级融合法、特征级融合法和决策级融合法,基于机器学习算法构建了一套面向自然资源信息提取的多源异构数据智能融合技术,实现了多源数据的高效利用与特征空间优选。同时,重构了2000—2019年汉江流域NDVI 1 km逐年数据集,全面反映了汉江流域植被动态变化。研究结果可为地球科学时空大数据的高效提取与模拟分析提供科学参考,为定量核算林草资源禀赋规模、探究生态系统时空演变规律提供一种更精准、更便捷的技术手段。