A novel mathematical morphology based algorithm for shoreline extraction from satellite images

Abstract

Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.     

基于CA模型的佛山市建设用地动态变化研究

元胞自动机具有能模拟复杂动态系统的强大能力,本文采用了多约束条件的元胞自动机模型,以广东佛山市2000年、2006年和2012年建设用地的变化为例,从自然、社会经济发展等方面综合考虑选取了高程、坡度、人口密度、道路交通、水系等对城市建设用地发展变化起决定作用的诸多因子,利用马尔科夫概率矩阵计算2000年~2006年建设用地变化,推算建设用地转移总量。结合Logistic-CA模型和决策树-CA模型,预测模拟了2012年的建设用地分布并与实际相比较,分析其整体精度和误差来源。结果显示基于CA模型的建设用地动态发展模拟具有良好的效果,可以为城市的发展规划,过程演变提供虚拟的实验手段和科学依据。     

磁铁矿采空区处理施工工艺与技术方法探讨

文章系统地介绍了采用地质钻机成孔,高压注浆机进行充填注浆的施工方法。为了将水泥砂浆及水泥粉煤灰浆填入采空区,采用能施加高压的输送泵及高压注浆设备、铸铁注浆管、水泥封孔的注浆工艺处理采空区铁路路基。在信息化施工过程中,通过试验不断地调整设计方法、改进施工工艺,在处理巨型磁铁矿采空区工程实践中达到了预期的目标。施工中,在控制充填边界、封孔方法及施工工艺等方面有一定的创新。提出的采空区施工技术控制、质量检测与评价方法,对同类工程勘察、设计及施工具有一定的参考价值。     

利用实时路况数据聚类方法检测城市交通拥堵点

 城市交通拥堵严重制约其网络总体效率。开展检测交通拥堵点可有效识别网络瓶颈,以整治交通拥堵现象。对此,本文提出一种新的城市交通时空拥堵点检测的方法:即采用实时路况数据,通过定义时空关联,检测时空意义上长期性、规律性交通拥堵点。本文基于DBSCAN(Density-Based Spatial Clustering of Applications with Noise)算法,以成都市为试验区,实现了这种拥堵点检测方法。试验表明,该方法可快速、有效、准确地检测出城市道路严重拥堵路段,并确定其拥堵时空范围,为交通管理、交通拥堵机理分析、交通拥堵预测等提供参考。     

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.     

建筑垃圾填埋场周边地下水化学组分来源解析

建筑垃圾是城市市政垃圾的重要组成部分,对其堆填处理可能造成场地及周围一定范围内的地下水污染。传统观念认为,建筑垃圾中多为惰性或无害成分,对地下水影响有限,缺乏关于建筑垃圾堆填对地下水水质造成影响的研究。选取2处建筑垃圾堆填场地,通过对场地周围地下水采样分析,得到场地周边地下水化学指标空间分布特征,并利用正定矩阵因子分解法(PMF)识别研究区地下水化学组分来源,从而定量评价建筑垃圾填埋对周边地下水水质变化的贡献。结果表明,建筑垃圾填埋会显著影响周边区域地下水组分的浓度和质量,尤其是TDS、TH、Ca2+、SO42-等组分显著受到影响,填埋时间越长、填埋体量越大,影响程度越深。两场地区域范围内Na+、Ca2+、Mg2+、SO42-和TDS 5个组分或指标的空间分布整体变化趋势较一致,均表现为垃圾填埋场附近沿地下水流下游方向的点位浓度较高,其他点位浓度较低,验证了建筑垃圾填埋对区域地下水质量的影响。PMF来源解析确定两场地周边地下水化学组分来源有建筑垃圾填埋、岩石风化溶解、水岩相互作用和农业活动,在场地一来源贡献占比分别为29.2%、21.6%、24.2%和15.1%,在场地二贡献占比分别为15.6%、23.2%、28.4%和18.2%。两场地周围地下水质量受人类活动影响程度较深,人为污染源正在成为地下水中离子组分的重要来源。     

GPS技术在高层建筑施工三维测控中的应用

垂直度控制和标高控制是确保高层和超高层建筑施工质量的关键,传统的高层或超高层建筑施工垂直度控制和标高控制方法存在着工作过程繁琐、效率低、精度难尽人意等若干问题,为了克服传统法的缺陷,提出了利用GPS技术进行高层或超高层建筑施工垂直度与标高控制的新思路,高层或超高层建筑施工垂直度与标高的GPS控制摆脱了传统方法对地面控制点的过度依赖,实现了对施工垂直度与标高的快速、高效、高精度控制,确保了施工质量。结合工程实例叙述了利用GPS技术控制高层或超高层建筑施工垂直度与标高的工作过程。     

基于特征提取的目标变化检测方法研究

针对不同时相遥感影像中特定目标的变化,研究了基于特征提取的目标变化检测方法。该方法首先根据目标的几何特征进行检测与提取,然后对提取出的两目标影像进行比较,得到特定目标的变化。实验结果表明该方法对特定目标的变化检测有较好的效果。     

南四湖湖内浅槽工程施工对水环境的影响及控制措施

南四湖湖内工程是沂沭泗河洪水东调南下续建工程的单项工程,工程区位于山东省省级自然保护区内;挖泥船施工将对湖内水环境产生一定影响。本文从排泥场回水污染物、生产废水和生活污水三个方面阐述了工程施工对水环境的影响程度,并且提出了相应的控制措施。     

利用地质雷达探测青岛港木质高桩码头承台完整性

利用EKKO－100型探地雷达对青岛港木质高桩码头承台完整性进行探测，结合现场钻探、孔内波速测试、岩样分析测试，进一步对码头的工程性状进行了分析和评价。