全极化SAR影像多特征分类的海岸线提取方法北大核心CSCD

快速准确地提取海岸线对研究海岸带和海岸带演变具有重要的意义。针对目前利用SAR影像提取海岸线的精度和自动化程度不能达到一个平衡这一问题,提出了一种结合多特征选择和随机森林分类算法的海岸线提取方法。并以高分三号(GF-3)全极化影像为研究数据,以黄河三角洲地区为研究区,成功提取了黄河三角洲地区的海岸线。该方法结果与OTSU阈值分割方法所提取的海岸线做了对比。结果显示,在40 m分析精度下,该方法海岸线提取结果质量均在90%以上,其提取结果光滑连续且精度可靠,优于直接阈值法提取的结果。     

海岸线遥感信息提取的元胞自动机方法及其应用

从遥感资料中准确提取海岸线信息,是海岛海岸带遥感调查与海岸带综合管理的重要内容。为了对多类型海岸线进行准确提取,基于"自下而上"演化的元胞自动机方法,结合遥感图像方向信息权重,构建了一种新的岸线提取算法,并在Matlab环境下开发实现包括均值平滑、海陆分离、离散地物去除和目标追踪的功能。以Landsat ETM+遥感影像作为数据源,分别对人工海岸上海市长兴岛-横沙岛和淤泥质海岸上海市崇明东滩岸线进行了检测,验证了该岸线信息提取的元胞自动机算法。研究表明,基于元胞自动机的岸线提取方法,能够以较高精度提取人工海岸和淤泥质海岸的岸线信息。     

基于遥感技术的大亚湾海岸线的变迁研究

利用Landsat卫星数据,经边缘检测、彩色合成图像处理方法,分析大亚湾海岸的岸相特征,提取海岸线,研究大亚湾海岸近20 a来1987年~2005年）的变化特征。结果显示,大亚湾海岸线变化主要受人为因素影响,岸线变迁最大的是泥质海岸带,沙质和基岩海岸的变化较小。岸线变化主要集中在西岸和北岸,以养殖开发、工业用地、城镇和港口建设用地开发为主。
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基于ETM遥感影像的海岸线提取与验证研究

利用ETM遥感数据,以黄河三角洲为研究区域,运用边缘检测方法中的Soble算法和修复归一化水体指数法（MNDWI）两种方法对该地区的两种海岸线类型--人工海岸和淤泥质海岸进行海岸线提取研究,并验证评价海岸线提取效果。结果表明,Soble算法提取的海岸线准确度更高,在淤泥质海岸提取中表现更为明显,相对误差由0.025%降低为0.018%。     

基于潮汐规律修正的海岸线遥感监测

针对海岸线研究提取时难以去除潮汐的影响的问题,提出了利用潮汐规律修正海岸线的方法。以青岛地区为例,基于Landsat数据利用修正归一化水体指数提取了水边线,分析了潮汐规律对海岸水边线信息提取的影响,结合海岸高程数据提出了潮位校正方法。最后基于提取的长时间序列海岸线分析了青岛地区1979—2019年海岸线时空格局变化。结果表明,利用潮汐规律进行潮位校正的方法可行且精度较高;近40年间青岛地区海岸线共向海洋推进158km2,变化活跃区域呈现由胶州湾向青岛南部转移的趋势。     

基于Landsat TM数据的江苏海岸带土地利用/覆被变化检测方法比较研究

土地利用/覆被变化是全球环境变化研究的核心问题之一,选择适当的变化检测方法在江苏海岸带土地利用/覆被变化研究工作中具有重要意义。本研究选取江苏海岸带具有典型代表性的大丰市作为变化检测方法比较研究的试验区,采用1992年和2002年两期Landsat TM影像,分别运用主成分分析法、混合变化检测法和变化矢量分析法进行变化检测,提取土地利用/覆被变化信息,并对每种变化检测方法进行定量分析和综合比较。研究表明,主成分分析法对于试验区的土地利用/覆被变化研究具有检测速度快、检测精度高等优点,适合试验区以及整个江苏海岸带的土地利用/覆被变化的检测。最终,综合运用主成分分析法和分类后比较法获得了5期近30年江苏海岸带土地覆被分类图,证明了主成分分析法可有效应用于江苏海岸带的变化检测。     

SAR影像海岸线提取方法对比及效果评价

利用合成孔径雷达(SAR)影像提取海岸线是当前遥感研究的热点之一,近年来基于边缘检测法、区域生长法、阈值分割法、水平集法、面向对象分类法、支持向量机分类法等系列SAR影像海岸线提取研究各自取得了一定的进展,但至今尚无对上述典型方法的全面研究与综合对比分析。为此,该文以基岩海岸、淤泥质海岸等2种常见类型海岸线的提取进行了实验,并提出一种海岸线提取精度定量评价的新指标——偏移误差,基于该指标定性定量对比分析了不同算法的优劣及适用性。实验表明,对基岩岸线,面向对象的分类法最优,边缘检测最劣;对淤泥质岸线,水平集最优,区域生长法最劣。     

海岸线卫星遥感提取方法研究进展

海岸线是划分海洋与陆地管理区域的基准线。不同海岸地貌的海岸线划分依据各不相同,因此,它们在卫星图像上的解译标志与提取方法也存在差异。论述了利用遥感进行海岸线动态监测的优势与海岸线的基本特点及其分类,明确了在各个领域中对海岸线的不同定义,指出了不同类型海岸的遥感解译标志。详细论述了不同种类卫星图像中的海岸线成像机理,介绍了使用卫星遥感图像提取各类海岸线的算法及其发展过程,并对遥感图像中的海岸线提取算法的发展方向做出了分析。     

不同空间尺度下石臼陀岛海岸线提取的遥感应用研究

空间尺度作为地学研究的基础,对于海-陆-气三相交互作用的海岸线的研究具有重要科学和实用意义。基于QuickBird、SPOT5和Landsat5等多源遥感影像提取石臼陀岛海岸线,构建了基于像元数的精度评价模型。依据分形理论,通过尺度转换模型,研究了海岸线遥感信息分维的尺度效应。在空间尺度校正的前提下分析了尺度效应造成的海岸线提取精度差异,以更加接近实际地对石臼坨岛海岸线的动态变化特征进行分析。研究表明:①石臼陀岛整体海岸线的分形维数为1.0111;②海岸线尺度效应随海岸类型不同而有所差异,该岛人工海岸线和粉砂淤泥质海岸线分形维数分别为1.0123和1.0089,前者较后者略大;③尺度转换后海岸线理论长度变化量表现出随尺度增加而增大的“边际效应”。     

不同水体指数提取淤泥质海岸线的分析与比较

水体指数是快速、准确提取大范围区域中海岸线的有效方法。但水体指数对以淤泥质岸线提取海岸线的适用性有待检验。本文以上海市的部分淤泥质海岸为研究区,以三幅Landsat影像为数据源,采用NDWI、MNDWI、AWEInsh、AWEIsh等四种水体指数提取海岸线,使用遥感影像进行目视解译的海岸线作为参考,探究上诉四种水体指数提取海岸线的差异。结果表明:MNDWI指数提取的海岸线能得到最佳提取效果;在120 m范围内,各种水体指数的海岸线提取精度均高于50%。     

Coastline extraction from SAR images using spatial fuzzy clustering and the active contour method

Coastline extraction from synthetic aperture radar (SAR) data is difficult because of the presence of speckle noise and strong signal returns from the wind-roughened and wave-modulated sea surface. High resolution and weather change independent of SAR data lead to better monitoring of coastal sea. Therefore, SAR coastline extraction has taken up much interest. The active contour method is an efficient algorithm for the edge detection task; however, applying this method to high-resolution images is time-consuming. The current article presents an efficient approach to extracting coastlines from high-resolution SAR images. First, fuzzy clustering with spatial constraints is applied to the input SAR image. This clustering method is robust for noise and shows good performance with noisy images. Next, binarization is carried out using Otsu’s method on the fuzzification results. Third, morphological filters are used on the binary image to eliminate spurious segments after binarization. To extract the coastline, an active contour level set method is used on the initial contours and is applied to the input SAR image to refine the segmentation. Because the proposed approach is based on an active contour model, it does not require preprocessing for SAR speckle reduction. Another advantage of the proposed method is the ability to extract the coastline at full resolution of the input SAR image without degrading the resolution. The proposed approach does not require manual initialization for the level set method and the proposed initialization speeds up the level set evolution. Experimental results on low- and high-resolution SAR images showed good performance for coastline extraction. A criterion based on neighbourhood pixels for the coastline is proposed for the quantitative expression of the accuracy of the method.     

Remote sensing of coastlines: detection,extraction and monitoring

This paper reviews the current status of the use of remote sensing for the detection, extraction and monitoring of coastlines. The review takes the US system as an example. However, the issues at hand can be applied to any other part of the world. Visual interpretation of airborne remote sensing data is still widely and popularly used for coastal delineation. However, a variety of remote sensing data and techniques are available to detect, extract and monitor the coastline. The developed techniques have reached a level of maturity such that they are applied in operational settings.     

Study on Mangrove Species Classification based on ZY-3 Image

A hybrid mangrove forest extraction and species classification model for large coastal region was proposed using a ZY-3 (ZiYuan-3) image in the eastern part of Beibu Gulf (located at the junction of Guangdong and Guangxi).Firstly,the coastline was extracted according to the spectral features of ZY-3 image.Secondly,the buffer zone along with the coastline was generated as the suitable area of mangrove distribution.Mangrove forests and non-mangrove areas were then further classified using threshold method based on object-based image classification in these areas.Finally,Mangrove forests were classified at specie level using three pixel-based supervised classification methods,k-Nearest Neighbor,Bayes,and Random Forest.The classification results and accuracies were also compared and discussed.The results indicated that object-based threshold method can extract the coastline accurately and map the mangrove forests effectively.The pixel-based random forest classifier can obtain satisfactory results (the overall accuracy of 82.24%) of mangrove species classification than the other classifiers.In summary,the hybrid mode proposed in this paper is suitable for mangrove forests mapping and species classification in a large region.It is also validated the feasibility application of ZY-3 image in coastal mangrove research.     

基于深度学习的海岸线边缘检测网络模型

海岸线的动态监测对海岸带的规划管理具有非常重要的意义。由于海陆环境错综复杂,遥感影像中海陆边界光谱特征不明显,导致提取的海岸线定位不准确。提出一种融合语义分割网络和边缘检测网络的深度卷积神经网络模型(EWNet)。该模型包含2个分支流：语义分割流负责提取分层语义信息并用来指导边缘检测流获取岸线语义信息;边缘检测流通过语义分割流完善边缘语义信息。在“高分一号”遥感图像上的实验结果表明,与几种最新网络模型相比,EWNet获得了更精确的海岸线边界提取结果。     

Utilizing DEMs derived from LIDAR data to analyze morphologic change in the North Carolina coastline

By using digital elevation model (DEM) data derived from light detection and ranging (LIDAR) data, an approximately 70-km stretch of the southern North Carolina coastline was studied. The coastline consists of five barrier islands located between Masonboro Island at the southern extent and Topsail Island at the northern extent. The high-resolution DEM data allowed for a comprehensive visual/quantitative investigation into the spatial patterns of morphologic change that occurred to the barrier islands' oceanfront beaches between 1997 and 2000. This study also demonstrated the usefulness of using laser altimetry to examine barrier islands' response to level of tropical activity, and showed that the coastal process of overwash was recognized as an integral component of barrier island landward migration. Means of net volumetric change per unit area (m³/m²) for study areas of different beach management practices, characterized as developed, undeveloped, and nourished beaches on a yearly basis for the period between 1997 and 2000 were derived. t-Test of the means has been conducted, and results showed that beaches differed statistically if different management practices were applied to them, and the differences were minimized or disappeared if sequential hurricanes or storms affected the beaches.     

基于面向对象—深度学习的闽东南低海拔海岸带地区湿地动态遥感分析

海岸带湿地具有重要的生态价值和经济开发价值,明确其时空变化特征与影响因素对于维持区域生态系统平衡和可持续发展具有重要意义。以Landsat TM/ETM+/OLI影像为基本数据源,综合利用面向对象与深度学习分类方法对1985~2015年闽东南低海拔海岸带地区的湿地信息进行提取,以揭示其时空演变特征与驱动力因素。结果表明：基于面向对象—深度学习分类方法对湿地进行信息提取,整体分类精度可达93%以上,分类结果整体性好;1985~2015年自然湿地面积呈减少趋势,人工湿地面积呈增加趋势,分别减少和增加250.31 km²和251.36 km²;湿地二级类型中,30 a间河口/浅海水域和淤泥质海滩面积减少最大,盐田/水产养殖场面积增加最大;1985~2015年湿地变化类型多样,且2000~2015年较1985~2000年湿地变化更为剧烈;湿地变化是人类活动和自然环境变化共同作用的结果,其中人类活动是影响湿地变化的主要原因。该方法及研究结果可为海岸带湿地监测与保护管理提供技术支持和决策参考。     

基于卫星影像技术的海岸线水域变化高精度检测系统设计

针对目前研究的海岸线水域变化检测系统在检测过程中,存在系统检测精度较低,检测稳定性较差,检测时间较长的问题,设计了基于卫星影像技术的海岸线水域变化高精度检测系统。采用STM32C8T6为主控芯片的主控器,进行高效的数据处理和网关通讯,以多光谱传感器为核心检测设备,通过采集光学数据,生成海岸线水域图像。利用XL1509-5.0芯片为核心的外接电源,供给系统电源设备,以OUTPUT作为电源开关的输出引脚,便于主控器对电源进行控制,完成系统硬件设计。采用卫星影像技术,对采集图形进行滤波处理、降噪处理以及图像二值化计算,嵌入Linux操作系统和MySQL数据库,高精度检测采集图像,完成系统软件设计,实现海岸线水域变化高精度检测。实验结果表明,设计的基于卫星影像技术的海岸线水域变化高精度检测系统的检测稳定性较好,能够有效实现海岸线水域变化高精度检测,缩短海岸线水域变化检测时间。     

Full-polarimetric SAR measurements for coastline extraction and coastal area classification

In this study, full-polarimetric synthetic aperture radar measurements are used for coastline extraction and to provide a rough classification of the inland area close to the extracted coastline according to the dominant scattering mechanisms. Scattering-based parameters, derived from the Freeman–Durden (FD) decomposition, are exploited to both extract the coastline and classify the inland area. With respect to coastline extraction, a challenging scenario that includes sandy beaches is considered and experimental results demonstrate that the FD surface component provides the best performance in terms of accuracy in detecting the sandy beach. With respect to the inland area classification, FD components are shown to provide useful information on the dominant scattering mechanisms that characterize the imaged area. This information, together with the extracted coastline, can be used to generate risk maps that help coastal area management.     

利用4期卫星资料监测1986~2009年浙江省大陆海岸线变迁

以20世纪70年代的地形图为底图,利用1986年和1995年TM、2005年ASTER和2009年HJ 4个时间段的遥感影像数据进行目视解译,对浙江省大陆海岸线多年来的变迁进行连续监测,获取每个时期发生变化岸段、陆地增加面积和分数维情况。结论如下：① 这3种卫星资料能够满足精确、快速监测海岸线变迁的要求;② 浙江省海岸线快速向海洋推进,1986~1995年新增205.24 km²,1995~2005年新增319.85 km²,2005~2009年新增484.75 km²;③ 浙江省海岸线分形维数较小,海岸线复杂程度较低,且最近20多年来分形维数呈现降低趋势。     

Coastline evolution monitoring and estimation—a case study in the region of Nouakchott,Mauritania

Since the construction of a harbour, Port de l'Amitié, an important importation gate for Nouakchott, northwestern Africa in 1987, the previous coast dynamic equilibrium has been destroyed and thus a significant littoral geomorphologic change has occurred, which has produced a severe degradation of the littoral and urban environment. This research is focused on coastline evolution monitoring and its potential change estimation by remote sensing techniques using multi‐temporal Satellite pour l'Observation de la Terre (SPOT) images and Markov chain analysis. It is the objectives of the study to measure and estimate the coastal current hydrodynamics, coastline evolution rates, harbour life‐span and to provide useful reference for the local authorities to make decisions for their future coastal management. The results show that the north beach of the harbour has extended by 0.92 km² (92 ha) from 1989 to 2001 and the accretion will probably reach its maximum limit in about 13 years±6 months (in 2014–2015) while the harbour will gradually arrive at the end of service. The south sandbar has been eroded by 1.34 km² (134 ha) and the coastline has retreated landwards by 362 m at the maximum point. Another 0.91 km² of land will be eroded in the next 10 years from 2001 to 2011. This erosion has caused several inundations to the suburb and urban areas, provoking a deterioration of the urban environment.