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地球信息科学学报 >

2017 , Vol. 19 >Issue 3: 407 - 416

DOI: https://doi.org/10.3724/SP.J.1047.2017.00407

遥感科学与应用技术

海上丝绸之路起点——泉州港岸线变化的遥感动态研究

  • 施婷婷 , 1 ,
  • 徐涵秋 , 1, * ,
  • 王帅 1 ,
  • 方灿莹 1 ,
  • 林中立 1 ,
  • 王美雅 1 ,
  • 唐菲 2
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  • 1. 福州大学环境与资源学院/福州大学遥感信息工程研究所,福建 福州 350116
  • 2. 国家海洋局海岛研究中心,福建 平潭 350400
*通讯作者：徐涵秋（1955-）,男,江苏射阳人,博士,教授,博士生导师,主要从事环境资源遥感应用研究。E-mail:

作者简介：施婷婷（1993-）,女,福建平潭人,博士生,主要从事环境资源遥感应用研究。E-mail:

收稿日期: 2016-09-12

  要求修回日期: 2016-10-14

  网络出版日期: 2017-03-20

基金资助

国家科技支撑项目(2013BAC08B01-05)

福建省教育厅重点项目（JA13030）

国家自然科学基金项目（41501469）

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Remote Sensing Study of Coastline Dynamics of Quanzhou Port:Starting Point of the Ancient Maritime Silk Road

  • SHI Tingting , 1 ,
  • XU Hanqiu , 1, * ,
  • WANG Shuai 1 ,
  • FANG Canying 1 ,
  • LIN Zhongli 1 ,
  • WANG Meiya 1 ,
  • TANG Fei 2
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  • 1. College of Environment and Resources; Institute of Remote Sensing Information Engineering; Fuzhou 350116, China
  • 2. Island Research Center, SOA, P.R.C; Pingtan 350400, China
*Corresponding author: XU Hanqiu, E-mail:

Received date: 2016-09-12

  Request revised date: 2016-10-14

  Online published: 2017-03-20

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《地球信息科学学报》编辑部 所有
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摘要

泉州港作为古代海上丝绸之路的起点,今天又成为21世纪“一带一路”的新起点。本文以泉州港1990-2014年共6期的Landsat TM/OLI遥感影像为数据源,综合应用遥感和GIS技术提取了泉州港的海岸线及海域变化信息,从海岸线的长度、变化速率、分形维数、海域变化面积和海域利用类型5个方面进行海岸线变化及其驱动力分析。研究表明：近24年来,泉州港海岸线长度增加了37.78 km,海岸线的形状总体稳定,但在局部有明显变化。海岸线变化导致的海域变化面积为68.02 km2,其中,建设用地(城市和港口建设)占用的比例最大,围海养殖也是一个重要的利用类型。但泉州港围填海新增面积的利用率不高,超过一半的围填海面积尚未被合理地开发利用。总的来看,新城区建设、临港工业产业兴起和农渔业发展导致了泉州港海岸线的变化。

关键词： 遥感; GIS; 海岸线变化; 驱动力; 海上丝绸之路; 泉州港

本文引用格式

施婷婷 , 徐涵秋 , 王帅 , 方灿莹 , 林中立 , 王美雅 , 唐菲 . 海上丝绸之路起点——泉州港岸线变化的遥感动态研究[J]. 地球信息科学学报, 2017 , 19(3) : 407 -416 . DOI: 10.3724/SP.J.1047.2017.00407

Abstract

As the starting point of China’s ancient Maritime Silk Road, Quanzhou Port has become a new starting point of “One Belt and One Road” in the 21st century. Quanzhou Port has a winding coastline running northward from Weitou Bay to Meizhou Bay. This paper studied the coastline dynamics of Quanzhou Port during 1990 to 2014. A total of six scenes of Landsat TM/OLI (1990, 1994, 2000, 1994, 2009 and 2014) were utilized for this study. The modified normalized difference water index (MNDWI) was used to enhance water information of the remote sensing images. The enhanced water images were then used to extract the coastlines from the images by setting a threshold. The extracted coastlines were later vectorized and integrated in ArcGIS to analyze their dynamics. The study of the coastline change in Quanhou Port was based on five aspects: coastline length, length changing rate, coastline fractal dimension, changed sea areas, and the use type of changed sea areas. Results showed that the coastline lengths of Quanzhou Port increased continually in the 24-study years, which was 418.19 km in 1990 and 455.97 km in 2014, an increase of 37.78 km during the period. The coastline shape of Quanzhou Port was generally stable. Nevertheless, intensive coastline changes do occur in some areas due to tide-land reclamation. This has locally led to the seaward advance of the shoreline and the simplification of the shoreline from winding to straight. The related sea area change due to the coastline modification was 68.02 km2, of which built-up land and port land occupied the largest proportion. However, the reclamation area is not highly used and more than half of the reclamation area has not yet been developed. This remote sensing based study has detected four large reclamation areas, which are located in Nanpu of western Meizhou Bay (7.33 km2 in area), Dongqiao of southwestern Meizhou Bay (34.85 km2 in area), western entrance of Quanzhou Bay (4.88 km2 in area), and eastern Jinjiang coast (5.17 km2 in area). Among them, only eastern Jinjiang coast is an enclosed tideland reclaimed for agriculture and fishery, whereas the other three are mainly the lands reclaimed for built-up land and port land. For example, the landfill in the western entrance of Quanzhou Bay is now the seat of Quanzhou Government. On the whole, the new town construction, nearshore industrial and agricultural fishery development led to the coastline changes of Quanzhou Port.

Key words： remote sensing; GIS; coastline change; driving force; Ancient Maritime Silk Road; Quanzhou Port

1 引言

2013年,中国政府提出共同建设21世纪海上丝绸之路和丝绸之路经济带的合作倡议[1]。泉州作为古代海上丝绸之路最重要的起点城市之一,以其浓厚的历史底蕴及优越的地理区位,又成为“一带一路”的新起点。泉州港地处福建东南部,与台湾地区隔海相望,港阔水深,岸线绵长,是海峡西岸港口群中重要的出海口,也是进出口贸易中重要的港口之一[2]。
由于海岸带是海洋和陆地的特殊交接地带,自然因素及人类活动的影响使其生态环境极为敏感、脆弱[3-4];在经济快速发展,各类用地压力徒增的情况下,填海造陆、围海养殖等开发利用活动使海岸线发生了显著变化,对海岸线变化的监测也成为了当今的一项重要任务。近年来,遥感以其高效、快速、实时等优点在海岸线变化研究中得到广泛的应用[5-10]。目前对海岸线变化研究主要集中在以下3个方面：① 不同数据源下的海岸线提取的方法与技术,包括自动、半自动与目视解译3种技术。例如,Petropoulos等[11]研究希腊Axios和Aliakmonas河流三角洲地区TM影像的岸线变化,对目视解译和支持向量机两种岸线提取方法进行了比较,结果表明支持向量机方法明显优于常用的目视解译;王李娟等[12]基于Sobel算子和MNDWI水体指数对黄河三角洲地区TM影像的岸线进行提取。② 对不同空间范围的海岸线变化过程进行动态监测及海岸线基本特征分析。例如,Misra等[13]利用卫星影像研究了印度古吉拉特邦1990-2014年土地覆盖及海岸线变化;Kuleli等[14]基于多时相Landsat影像和数字岸线分析系统的自动图像分析技术,分析了1989-2009年土耳其拉姆萨尔海岸带湿地岸线变化速率特征;徐进勇等[15]从岸线变化强度及分形维数变化来分析2000-2012年中国北方岸线长度及形态的时空变化特征;高志强等[16]从海岸线长度变化、变迁程度、变迁面积和变迁方向4个方面,对中国沿海地区30年来海岸线变迁原因进行分析。③海岸线变化的影响因素及影响效应分析。例如,Hapke等[17]探索美国加利福利亚州的岸线变化与海蚀崖变化的相关关系及内部影响机制;Schupp等[18]利用卡方检验、交叉相关分析及数字海岸线分析系统等方法,探讨美国北卡罗莱纳州外滩群岛沙坝、近岸沉积物与海岸线变化的关系;孙晓宇等[19]利用遥感技术,提取并分析渤海湾2000-2010年岸线时空变化特征,同时以岸线长度及新增的陆地面积为主要指标对海岸线的变化过程进行定量研究,结合社会经济数据阐述了渤海湾岸线变化的主要驱动因子。
总体看来,海岸线变化研究正向定量研究、深层次特征分析及机理机制探索等方向发展[20]。 本文利用遥感对地观测信息技术来监测泉州港近20年来海岸线变化,探讨引起海岸线变化的社会 经济驱动机制,及时掌握海岸带地区土地开发利用情况,为泉州致力打造21世纪海上丝绸之路先行区、建设国际港口枢纽城市提供科学依据,同时也为其它海岸带地区的综合管理和可持续发展提供参考。

2 研究区与数据源

2.1 研究区

泉州港地处福建省东南沿海,为晋江下游的滨海港湾,其海岸线南起围头湾莲河（118°21′05″E, 24°34′56″N）,北至湄洲湾内澳（118°52′23″E, 25°14′39″N）（图1）。泉州港资源优越,是福建省三大港之一。泉州港地势低平,以多海湾的曲折海岸线为主体,主要包括湄洲湾、泉州湾、深沪湾和围头湾4个湾。泉州港属正规半日潮,平均高潮位为4.83 m,平均低潮位为0.31 m,平均潮差4.52 m。
Fig. 1 Location of Quanzhou Port

图1 泉州港地理区位示意图

2.2 数据源及预处理

为了保证提取的水陆边界线更接近真正意义上的“海岸线”,本研究特地选用海岸线处于高潮位或中高潮位的Landsat TM和OLI遥感影像作为数据源,以避免潮汐水位的变化对海岸线鉴别的影响,分别获取了1990-07-20、1994-05-12、2000-06-29、2006-09-18、2009-06-06和2014-09-08共6个时相的覆盖泉州港地区的遥感影像数据。所选影像具体参数如表1所示。
Tab. 1 Parameters of six used remote sensing scenes

表1 6个时相卫星遥感数据参数

序号 卫星 传感器 空间分辨率/m 成像日期 农历 成像时间(UTC+8) 潮汐位
1 Landsat 5 TM 30 1990-07-20 闰五月二十八 09:53 高潮位
2 Landsat 5 TM 30 1994-05-12 四月初二 09:52 中高潮位
3 Landsat 5 TM 30 2000-06-29 五月二十八 10:09 高潮位
4 Landsat 5 TM 30 2006-09-18 闰七月二十六 10:27 中高潮位
5 Landsat 5 TM 30 2009-06-06 五月十四 10:21 高潮位
6 Landsat 8 OLI 30 2014-09-08 八月十五 10:33 高潮位
由于研究的时间跨度大以及卫星和气候等原因,需要对所选取的影像数据进行统一标准化预处理。首先对6期影像进行辐射校正,Landsat TM影像采用集成Chander[21]和Chavez[22]算法的IACM大气校正模型[23]将原始影像的灰度值转换为传感器处反射率,Landsat OLI影像根据Landsat 8官方网站提供的公式进行辐射校正;其次对6期影像进行几何校正,配准精度均小于0.5个像元;最后裁剪出覆盖泉州港海岸线的研究范围。

3 研究方法

本研究的研究方法包括4个方面：海岸线信息提取、海岸线变化速率计算、海岸线分形维数计算和海岸线变化海域信息提取。研究方法与技术路线如图2。
Fig. 2 Flowchart of the study techniques

图2 研究技术路线图

3.1 海岸线信息提取

在测绘学、地理学、经济学和政治领域中,有关海岸线的定义不尽相同[5,24]。目前对于海岸线定义多指的是海陆交界线[25],为多年平均大潮高潮时水陆分界的痕迹线,受自然和人为因素影响,海岸线始终处于动态变化中[26]。海岸线的高度动态性决定了现实中并不存在一条固定的“线”,通常根据具体情况采用不同的岸线指标来表征真实岸线的位置[24]。岸线指标分为3大类[5]：① 目视可辨识线,即肉眼可辨别的线要素,如高潮线或干湿分界线; ② 基于潮汐基准的海岸线,即海岸带垂直剖面与利用潮汐参数计算的某一海平面的相交线,如平均高潮线,平均海平面线;③ 基于处理技术提取的海岸线,即利用影像处理技术从数字海岸影像中提取海岸线特征（非人眼可见）。因此,在实际应用中,一般采用较为固定的线要素代替水陆边界线指示海岸线的位置。本文将提取的卫星过境时的陆地与海水的分界线（即瞬时“水边界”）作为海岸线。
本文借鉴前人的研究,采用人机交互的方式进行海岸线提取。首先采用Xu[27]提出的修正归一化差值水体指数MNDWI,分别获得6个时相的MNDWI影像。其数学表达式为：
MNDWI = Green - MIR Green + MIR （1）
式中：MIR和Green分别代表中红外波段和绿光波段的反射率。对于Landsat TM,分别对应的2和5波段;对于Landsat OLI,分别对应3和6波段。
相关文献与实验证明MNDWI指数能够有效地将水体与陆地区分开来提取海岸线[28-29]。因此,可对MNDWI进行二值化处理,获得水陆边界线栅格图,实现海陆分界。然后在ArcGIS软件中将提取的水陆边界线栅格图矢量化,得到水陆边界线矢量数据。为了保证前后2期海岸线位置没有变化的部分保持严格的一致性,将数字化后的1990年海岸线作为最原始的本底数据（后期海岸线以前期海岸线作为本底数据）,对于海岸线变化部分采用经MNDWI指数提取的矢量数据进行动态更新,从而有效地避免了不同时间分辨率下遥感影像进行海岸线动态提取时产生的“双眼皮”现象,保证海岸线变化的准确性。在提取过程中为避免误判,可借助Google Earth高分遥感影像进行判读。

3.2 海岸线变化速率计算

由于监测的时间间隔不相同,为了对海岸线变化的时空差异进行更加客观准确的对比,采用某一时间段内海岸线长度的年均变化来表示海岸线的变化速率[30]。
P = L j - L i j - i （2）
式中：P为第i年至第j年海岸线长度变化速率;Li为第i年海岸线的长度;Lj为第j年海岸线的长度。

3.3 海岸线分形维数计算

海岸线分形维数的计算通常有2种方法：量规法和盒计数法。本研究采用盒计数法计算海岸线的分形维数。盒计数法是采用不同长度的正方形网格（或盒子,设边长为r(N)）连续且不重叠地去覆盖被监测的海岸线,当正方形网格长度r(N)出现变化,则覆盖整条海岸线所需网格数目N会出现相应的变化,根据Mandelbrot定义的分形维数计算公式为[31]：
D = - log N log r ( N ) （3）
式中：D为海岸线的分形维数,其值介于[1,2]之间（直线的分形维数理论值为1,矩形的分形维数理论值为2）,分形维数值越接近2,表示海岸线的弯曲和复杂程度越高;格网尺度r(N)的选取方法参照文献[32]。

3.4 海岸线变化海域信息提取

海岸线变化原因可分为：自然因素和人为因素2个方面。淤积和蚀退是导致海岸线变化的主要自然因素。自然淤积是河流入海携带的泥沙在入海口周边沉积形成淤泥质岸线或沙砾质岸线,同时改变自然岸线的位置和长度;自然蚀退受海潮影响较重,遭侵蚀岸线主要为淤泥质、砂砾质和河口岸线,部分人工岸线也会受影响。人为因素主要是经济建设活动,可能会完全改变原有自然或人工岸线的类型和空间位置。而围填海是人类对海岸线开发利用的最主要表现形式。国家海洋局编制的《海域使用分类》（HY/T 123-2009）[33]对于围填海进一步定义为：填海造地,指筑堤围割海域填成土地,并形成有效岸线的用海方式;围海,指通过筑堤或其他手段,以全部或部分闭合形式围割海域进行海洋开发的用海方式。因此,本文根据《海域使用分类》并结合研究泉州港的实际情况将研究海域进一步细分为淤积、蚀退、建设用地、农业用地、港口用地、未利用地、围海养殖和待利用水面8类（表2）。
Tab. 2 Classification scheme of the sea area

表2 海域分类体系

因素（用海方式） 类型 定义
自然 淤积 指河流入海携带的泥沙在入海口周边沉积形成淤积
蚀退 指海岸地带在风浪、沿岸海流、潮汐等作用影响下,岸线逐渐蚀退
人为 填海 建设用地 用于城镇居住、工业与交通等的填海
农业用地 用于农、林、牧业生产的填海
港口用地 用于港口码头、港池、堤坝等所使用的填海
未利用地 主要指已填充或正在填充但未开发利用的填海
围海 围海养殖 用于渔业养殖或渔业基础设施的围海
待利用水面 主要指已筑堤和正在筑堤的尚未利用的围海区域
利用ArcGIS的矢量编辑工具,将研究区每个相邻时相的海岸线进行叠加,提取出各海岸线的动态范围,利用线转面工具提取海岸线变化面积。然后使用目视解译的方法,同时结合遥感影像和Google Earth对海域变化部分赋予类别属性,得到泉州港各时期海域演变情况。

4 结果与讨论

4.1 海岸线变化特征分析

利用以上方法分别获得6个年份的海岸线分布图（图3）。
Fig. 3 Extracted coastlines of QuanzhouPort from 1990 to 2014

图3 1990-2014年泉州港海岸线提取结果

4.1.1 海岸线长度变化分析
根据本次遥感解译结果（表3）,泉州港海岸线长度从1990年的418.19 km增加到2014年的455.97 km,共增加了37.78 km,年均增加1.57 km。1990-2014年,海岸线长度持续增长,各研究年份的海岸线长度均表现为比前一研究年份有所增长。
Tab. 3 The lengths and fractal dimensions of coastlines of Quanzhou Port in each study year

表3 1990-2014年泉州港海岸线长度及分形维数

1990年 1994年 2000年 2006年 2009年 2014年
海岸线长度/km 418.19 424.87 429.25 432.00 445.17 455.97
分形维数 1.1481 1.1481 1.1498 1.1497 1.1553 1.1593
R2 0.9974 0.9976 0.9976 0.9977 0.9977 0.9978

注：网格数目N的对数与网格长度r(N) 的对数的拟合系数R2越接近1,表明分形维数值越精确

为了客观比较各时期泉州港海岸线变化的时空差异,利用海岸线变化速率计算公式得到不同时期海岸线变化速率（表4）。1990-1994年海岸线变化速率为1.67 km/a,这主要是由于湄洲湾工业用地及港口的建设、泉州湾围垦造田以及淤积等因素导致了该时期海岸线长度的变化。1994-2006年海岸线长度变化速率相对较小,都小于0.8 km/a。2006年以后泉州港海岸线长度进入一个快速增长时期,其中2006-2009年海岸线变化最显著,变化速率达4.39 km/a,这主要是由于建设用地和港口等增加,造成原本平直的海岸线变成凸出的多边形,从而导致海岸线的加长,港口处尤为显著。
Tab. 4 The changing rate of coastline lengths and sea areas of Quanzhou Port in various periods

表4 不同时期泉州港海岸线长度变化速率及海域变化面积

1990-1994年 1994-2000年 2000-2006年 2006-2009年 2009-2014年 1990-2014年
变化速率/(km/a) 1.67 0.73 0.46 4.39 2.16 1.57
变化面积/km2 3.43 4.45 44.79 9.97 8.44 68.02
4.1.2 海岸线分形维数变化分析
利用盒计数法计算泉州港海岸线分形维数,得到6个研究年份的泉州港海岸线的分形维数（表3）。从表3可知,泉州港海岸线的分形维数总体呈略增长趋势,从1990年的1.1481增加到2014年的1.1593,微增了0.98%,说明泉州港海岸线的总体形状基本稳定,但局部的围海造地（建设用地、养殖、港口）使得海岸线的形状发生局部变化。
4.1.3 海岸线变化引发的海域面积变化分析
利用ArcGIS的矢量编辑工具,将研究区每个相邻时相的海岸线进行叠加,提取出各海岸线的动态范围,利用线转面工具提取出海岸线变化区域（图4）,并计算其面积。结果表明,1990-2014年泉州港因海岸线变化导致的海域面积变化达68.02 km2。对各时期的海域变化面积分别进行统计,可以发现（表4）：2000-2006年海域变化面积最大,达到44.79 km2,占总变化面积的63.01%,远大于其它各时期的变化量;其次为2006-2009年,海域变化面积为9.97 km2,占总变化面积的14.03%;而1990-1994年的海域变化面积最小,仅为3.43 km2,占总变化面积的4.83%。
Fig. 4 Sea area changes in Quanzhou Port from 1990 to 2014

图4 1990-2014年各时期泉州港海域变化面积图

4.1.4 海域利用类型变化分析
泉州港各研究时间段海域利用类型变化的解译结果如表5所示。从表5得知,在本文研究的24年间,泉州港的围填海造地使得局部海域利用类型发生明显的变化。从导致海域发生变化的两大因素来看,人工因素导致的变化远大于自然因素,表现为自然因素（淤积、蚀退）引起的面积变化比例仅有2.59%。在人工因素导致的变化类型中,城市建设用地是变化最大的类型。在24年间,人工填海增加的城市建设用地达20.94 km2,占新增面积的30.78%;其次为港口用地与围填海养殖,分别占新增面积的5.72%和5.88%。农业围垦用地仅占新增面积的不到2%。值得注意的是,泉州港围填海新增面积的利用率不高,表现在未利用地占新增面积的10.74%,而待利用水面甚至占到了新增面积的42.32%。
Tab. 5 Statistics of the use types of sea area in each study sub-period

表5 各时期各利用类型面积及所占比例

利用类型 1990-1994年 1994-2000年 2000-2006年 2006-2009年 2009-2014年 1990-2014年
面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/% 面积/km2 比例/%
淤积 1.65 48.25 0.18 2.64 0.27 0.61 0.20 1.75 0.02 0.08 0.25 0.36
蚀退 0.08 2.34 1.52 22.56 0.33 0.74 0.51 4.37 0.37 1.97 1.51 2.23
建设用地 0.42 12.28 0.43 6.35 2.96 6.56 6.68 57.39 9.38 49.37 20.94 30.78
农业用地 0.47 13.74 1.12 16.71 1.06 2.35 0.31 2.64 0.00 0.00 1.34 1.97
港口用地 0.08 2.34 0.61 9.06 0.86 1.91 0.71 6.14 0.85 4.45 3.89 5.72
未利用地 0.07 2.05 0.09 1.27 2.03 4.51 2.82 24.19 6.81 35.82 7.30 10.74
围海养殖 0.37 10.82 2.43 36.20 1.60 3.56 0.00 0.00 0.72 3.79 4.00 5.88
待利用水面 0.28 8.19 0.35 5.21 35.95 79.76 0.41 3.53 0.86 4.52 28.79 42.32
总计 3.43 100 6.72 100 45.08 100 11.64 100 19.01 100 68.02 100

注：除蚀退表示海域面积增加外,其它利用类型均表示海域面积减少

为了进一步分析泉州港海岸线变迁海域利用类型变化,分别选择了4片变化最大的典型区域来进一步研究它们在各个时期的变化历程,分别位于：泉港区南埔镇、惠安县东桥镇、丰泽区东海新城和晋江市陈埭-西滨。
（1）泉港区南埔镇（图5（a）-（e））,近24年来经历了从围海养殖和农业用地为主到建设用地（工业用地）为主的演变过程,海域面积减少了7.33 km2。其中1990-1994年该海域利用类型为淤积;1994-2009年该海域填海的利用类型主要以农业和围海养殖为主;2009-2014年对该海域进行大范围的填海造陆工程,海域利用类型发生显著改变,主要转为工业用地,用来港口、仓储、石化等工业产业的发展。根据《福建省湄洲湾石化基地发展规划》,该区域规划为泉港石化工业区重点发展的南垦片区的一部分,主要建设福建炼化一体化二期项目（占地约5.17 km2）和台湾石化专区等,从图5d可以看出该项目正在建设之中。
Fig. 5 Four typical coastline change areas

图5 4个典型的海岸线变化区

（2）惠安县东桥镇（图5（f）-（h））,近24年来经历了从围海养殖为主到建设用地（工业用地）为主的演变过程,海域面积减少了34.85 km2。该海域一直到2006年都未发生改变,2006-2009年开始围海筑堤（外走马埭围垦海堤）,2009年后开始填海造地。根据《福建省湄洲湾石化基地发展规划》,该区域规划为泉惠石化工业区,总规划用地为32 km2,主要发展石化下游深加工产品。通过围填海,现已建成中化集团1200万吨/年炼油项目（图6）,是国家“十二五”规划以及福建省重点建设项目。
Fig. 6 Quanhui petrochemical industrial zone

图6 泉惠石化工业区

（3）丰泽区东海新城（图5（i）-（m））,近24年来经历了从围海养殖转为建设用地的演变过程,海域面积减少了4.88 km2。1990-2006年,该海域逐步发展围海养殖,养殖坑塘不断增加;2006年后该海域进行了大范围的填海造陆工程,建设用地大面积增加。根据《泉州市城市总体规划（2008-2030）》,该区域规划为东海组团的一部分,重点完善市级行政服务功能,目前已成为泉州市政府所在地。
（4）晋江市陈埭~西滨（图5（n）-（p））,近24年来该海域的围填海以农业和养殖业为主,海域面积减少了5.17 km2。1990年,该海域主要利用类型为农业用地,而到了2014年,该海域除了农业利用外,其南部区域增加了大面积的围海养殖。相比于上述3个海域的变化情况,该海域主要以围海工程为主,而其它3个海域主要以填海工程为主。

4.2 海岸线变化驱动力分析

综合分析泉州港近24年来在海岸线长度、变化速率、分形维数、海域变化面积和海域利用类型等方面的变化,可以看出人为因素是造成海岸线变化最主要的原因。大范围经济开发战略的实施和经济结构的调整决定了泉州港海岸线的变化过程与趋势。人地矛盾一直是泉州港地区发展面临的主要问题,因此近24年来泉州港建设用地成为主要的围填海利用类型。同时,工业产业的快速发展和物流运输的需要也加大了港口码头的用地需求,这些因素使泉州港的海岸线不断向海域扩展。综合分析泉州港海域利用类型变化情况,可以认为以下因素是泉州港海岸线变化的主要驱动力。
4.2.1 新城区建设
改革开放以来,泉州的经济是福建省乃至全国发展最快、最具活力的地区之一。根据泉州统计年鉴,1990-2014年,泉州市GDP从61.87亿元增加到5733.36亿元,年均GDP增长率高达20.77%,高于全国同时期15.81%的年均GDP增长率。经济的快速增长促进了城市化进程的加快,造成城市人口数量急剧增加。根据泉州统计年鉴,泉州市总人口从1990年的573.44万人上升到2014年的716.22万人,年均增加5.95万人。原有的旧城区已经无法满足泉州经济和人口发展的需要,原有城区周边也已无空间可供城市扩张。因此,泉州市2008年新一轮城市规划选择填海来建设新城区,从而形成了东海新城,并已成为泉州市的行政文化中心和现代商务中心（图5（l））。
4.2.2 临港工业产业发展
泉州市“十一五”规划提出建设海洋经济强市的战略目标,加快建设现代化亿吨大港,充分发挥港口对泉州市新一轮经济发展、城市建设的“龙头”带动和辐射作用。2008年《泉州港总体规划》明确将泉州港确定为中国沿海地区性重要港口、对台“三通”的主要港口和海峡西岸经济区服务纵深腹地的重要出海口,加上新近确立的“一带一路”建设的海上丝绸之路起点,这一系列的政策导向都为泉州港临港工业产业的发展注入了新的动力。
泉州港凭借临海的区位优势,一直是经济增长的重心。自1978年以来,泉州港临港工业产业快速发展,现已经形成了石油化工、机械制造、汽车装配、修造船业、纺织鞋服、建筑建材、工艺制品、食品饮料、电子信息等25个优势产业集群和一大批规模企业、优势企业,是中国石化产业规划九大基地之一和沿海八大修造船基地之一。泉州港临港工业园区如泉港石化工业园区、泉惠石化工业园区的建设是临港工业快速发展的突出表现。泉州港的港口货物吞吐量从1990年的101万吨起步,至2014年已达11201万t,年均增长率高达21.68%;集装箱从1990年的130标箱起步,至2014年已达188万标箱,年均增长率高达49.05%,集装箱吞吐量排名居全国港口第18位。港口经济和物流的快速发展,导致港口用地需求急剧增加,泉州港北部湄洲湾的填海就是为满足港口用地需求而开展的围填海建设。
4.2.3 农渔业发展
由于泉州港多淤泥质海岸,围堤成本低,工艺简单且成本效益高,所以农业用地和围海养殖也是造成泉州港海岸线变化的因素之一。晋江市陈埭-西滨的南部海域是围垦发展农渔业的典型代表,此外,零星围海造田、养殖造成的海岸线变化还可见于惠安县东桥镇的西南海域以及其它的一些海域。
综上可知,建设用地、港口码头、围海养殖、农业用地等人为因素是近24年来引起泉州港海岸线变迁的关键因素;而新城区建设、临港工业产业发展、农渔业发展决定了围填海工程的利用类型,是驱动泉州港海域变化的主要因素。

5 结论

本文选用6期Landsat遥感影像数据,应用遥感和GIS技术,从海岸线长度、变化速率、分形维数、海域变化面积和利用类型5个方面对泉州港海岸线1990-2014年的变化及其驱动力进行分析,得出以下主要结论：
（1）1990-2014年,泉州港海岸线的长度增加了37.78 km,年均增长1.57 km;海岸线形状总体稳定,但局部有明显变化。海岸线变化导致的海域变化面积为68.02 km2。在所利用的海域面积中,建设用地（城市和港口建设）占用的比例最大,围海养殖也是一个重要的利用类型。但泉州港围填海新增面积的利用率不高,表现在未利用地占新增面积的10.74%,而待利用水面甚至占到了新增面积的42.32%,即超过一半的围填海面积尚未合理地开发利用。
（2）在导致泉州港海岸线变化的因素中,人为因素远大于自然因素。在人为因素导致的变化类型中,建设用地、港口码头、围海养殖和农业发展等因素是泉州港海岸线变化的关键因素。而新城区建设、临港工业产业发展、农渔业发展等决定了围填海工程造地的利用类型。

The authors have declared that no competing interests exist.

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[ Li Y, Wang Y L, Peng J, et al.Research on dynamic changes of coastline in Shenzhen City based on Landsat image[J]. Resources Science, 2009,31(5):875-883. ]

[5]
Gens R.Remote sensing of coastlines: detection, extraction and monitoring[J]. International Journal of Remote Sensing, 2010,31(7):1819-1836.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.

DOI

[6]
Li W, Gong P.Continuous monitoring of coastline dynamics in western Florida with a 30-year time series of Landsat imagery[J]. Remote Sensing of Environment, 2016,179:196-209.Continuous monitoring of coastline dynamics is of crucial importance to the understanding of relative contributions of various potential driving factors behind the long-term coastline change. While a large number of efforts have been made to extract coastline and detect coastline change with remotely sensed data, the temporal frequency and spatial resolution of coastline datasets obtained are generally not fine enough to reflect the detailed process of coastline retreat and/or advance, particularly in coastlines with subtle variability. To overcome these limitations, we developed a method to continuously monitor the dynamics of a muddy coastline with subtle variability in western Florida at annual and subpixel scales using time-series Landsat data (1984-2013). First, robust indicators were used to indicate the annual "average" location of the dynamic coastline. Due to the complexity of muddy-coast morphology, the annual average location is represented not by the coast "line", but by the fractional inundated "area" of coastline pixels (pixels where the coastline is located), namely annually inundated area. Second, the annually inundated area of coastline pixels was estimated with a model proposed in this study, and the uncertainty was estimated with the Monte Carlo method. The retrievals were validated at 10 sites with aerial imagery, and the overall RMSE (root mean square error) is 11.48%. Third, the long-term trend for the time series of annually inundated area was derived with a statistical model. The results indicate that the muddy coast in western Florida continues to shrink with an average rate of 0.42 0.05 km2/year during the three decades. This study demonstrates the feasibility of time-series Landsat data in continuous monitoring of coastline dynamics.

DOI

[7]
Choung Y J, Jo M H.Shoreline change assessment for various types of coasts using multi-temporal Landsat imagery of the east coast of South Korea[J]. Remote Sensing Letters, 2016,7(1):91-100.Shoreline change assessment is an important task for protecting coastal properties and preserving coastal environments. This research aimed to assess the shoreline changes using the multi-temporal Landsat imagery, acquired from the east coast of South Korea during 1994 and 2014. The procedure for the shoreline change assessment consists of the following steps: (i) generating the normalized difference water index (NDWI) map from each Landsat image; (ii) extracting the shorelines from each NDWI map through the thresholding method; and (iii) assessing the shoreline changes in the various types of coasts such as the sandy, rocky and harbour coasts using the checkpoints with 1 km intervals. The statistical results showed that 94% of the shorelines in the sandy coasts and 96% of the shorelines in the rocky coasts moved landward between 1994 and 2014 due to coastal erosions, while 91% of the shorelines in the harbour coasts moved seaward during the same period due to the land reclamation works. This research contributed to the assessment of the shoreline changes and the calculation of the erosion rates in the various coasts of the study area between 1994 and 2014.

DOI

[8]
Yousef A, Iftekharuddin K M, Karim M A.Shoreline extraction from light detection and ranging digital elevation model data and aerial images[J]. Optical Engineering, 2014,53(1):011006.As sea level rises and coastal populations continue to grow, there is an increased demand for understanding the accurate position of the shorelines. The automatic extraction of shorelines utilizing the digital elevation models (DEMs) obtained from light detection and ranging (LiDAR), aerial images and multi-spectral images has become very promising. In this paper, we propose a new algorithm that can effectively extract shorelines from fused LiDAR DEMs with aerial images depending on the availability of training data. The LiDAR data and the aerial image are fused together by maximizing the mutual information using the genetic algorithm. The extraction of shoreline is obtained by segmenting the fused data into water and land by means of the support vector machines classifier. Compared with other relevant techniques in literature, the proposed method offers better accuracy in shoreline extraction.

DOI

[9]
Maiti S, Bhattacharya A K.Shoreline change analysis and its application to prediction: a remote sensing and statistics based approach[J]. Marine Geology, 2009,257(1):11-23.The result shows that 39% of transects have uncertainties in shoreline change rate estimations, which are usually nearer to cell boundaries. On the other hand, 69% of transects exhibit lower RMSE values for the short-term period, indicating better agreement between the estimated and satellite based shoreline positions. It is also found that cells dominated by natural processes have lower RMSE, when considered for long term period, while cells affected by anthropogenic interventions show better agreement for the short-term period. However, on regional considerations, there is not much difference in the RMSE values for the two periods. Geomorphological evidence corroborates the results. The present study demonstrates that combined use of satellite imagery and statistical methods can be a reliable method for shoreline related studies.

DOI

[10]
张云,张建丽,李雪铭,等.1990年以来中国大陆海岸线稳定性研究[J].地理科学,2015,35(10):1288-1293.海岸线变迁是一个动态的演变过程,它是自然与人类共同作用的结果。基于1990年、2000年、2007年和2012年4个时期的资源卫星、Landsat系列卫星的遥感影像,采用色差Canny算子计算方法提取岸线数据,计算近22 a来中国大陆海岸线向海推进或向陆后退的空间位置变化量及年均变化速度,研究中国大陆海岸线空间位置与稳定性的演变规律,得出以下结论:1中国海岸线空间位置变化以向海推进为主;2中国海岸线多为相对稳定海岸线,其次为强烈岸进岸线,稳定性岸线全国均有分布,而强烈岸进岸线多分布于江苏和辽宁两省;3自1990年以来,中国大陆岸线的稳定性指数逐渐降低,22 a下降了1.1,以长江入海口为分界,南方沿海城市岸线稳定性指数高于北方。

[ Zhang Y, Zhang J L, Li X M, et al.Stability of continental coastline in China since 1990[J]. Scientia Geographica Sinica, 2015,35(10):1288-1293. ]

[11]
Petropoulos G P, Kalivas D P, Griffiths H M, et al.Remote sensing and GIS analysis for mapping spatio-temporal changes of erosion and deposition of two Mediterranean river deltas: The case of the Axios and Aliakmonas rivers, Greece[J]. International Journal of Applied Earth Observation and Geoinformation, 2015,35:217-228.Wetlands are among Earth's most dynamic, diverse and varied habitats as the balance between land and water surfaces provide shelter to a unique mixture of plant and animal species. This study explores the changes in two Mediterranean wetland delta environments formed by the Axios and Aliakmonas rivers located in Greece, over a 25-year period (1984鈥2009). Direct photo-interpretation of four Landsat TM images acquired during the study period was performed. Furthermore, a sophisticated, semi-automatic image classification method based on support vector machines (SVMs) was developed to streamline the mapping process. Deposition and erosion magnitudes at different temporal scales during the study period were quantified using both approaches based on coastline surface area changes. Analysis using both methods was conducted in a geographical information systems (GIS) environment.

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[12]
王李娟,牛铮,赵德刚,等.基于ETM遥感影像的海岸线提取与验证研究[J].遥感技术与应用,2010,25(2):235-239.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%。

[ Wang L J, Niu Z, Zhao D G, et al.The study of soastline extraction and validation using ETM remote sensing image[J]. Remote Sensing Technology and Application, 2010,25(2):235-239.]

[13]
Misra A, Balaji R.Decadal changes in the land use/land cover and shoreline along the coastal districts of southern Gujarat, India[J]. Environmental monitoring and assessment, 2015,187(7):1-13.The coastal zone along the districts of Surat, Navsari, and Valsad in southern Gujarat, India, is reported to be facing serious environmental challenges in the form of shoreline erosion, wetland loss, and man-made encroachments. This study assesses the decadal land use/ land cover (LULC) changes in these three districts for the years 1990, 2001, and 2014 using satellite datasets of Landsat TM, ETM, and OLI. The LULC changes are identified by using band ratios as a pre-classification step, followed by implementation of hybrid classification (a combination of supervised and unsupervised classification). An accuracy assessment is carried out for each dataset, and the overall accuracy ranges from 90 to 95 %. It is observed that the spatial extents of aquaculture, urban built-up, and barren classes have appreciated over time, whereas the coverage of mudflats has depreciated due to rapid urbanization. The changes in the shoreline of these districts have also been analyzed for the same years, and significant changes are found in the form of shoreline erosion. The LULC maps prepared as well as the shoreline change analysis done for this study area will enable the local decision makers to adopt better land-use planning and shoreline protection measures, which will further aid in sustainable future developments in this region.

DOI PMID

[14]
Kuleli T, Guneroglu A, Karsli F, et al.Automatic detection of shoreline change on coastal Ramsar wetlands of Turkey[J]. Ocean Engineering, 2011,38(10):1141-1149.This research focuses on the shoreline change rate analysis by automatic image analysis techniques using multi-temporal Landsat images and Digital Shoreline Analysis System (DSAS) along the coastal Ramsar wetlands of Turkey. Five wetlands were selected for analysis: Yumurtalik Ramsar, the Goksu Ramsar, Kizilirmak and Yesilirmak wetlands and Gediz wetlands. Accretion or erosion processes were observed on multi-temporal satellite images along the areas of interest. Landsat images were geometrically and radiometrically corrected for the quantitative coastline delineation analysis. DSAS (Digital Shoreline Analysis System) was used as a reliable statistical approach for the rate of coastline change. For the detection of coastal change in Aegean part (Gediz wetland) of the study, zonal change detection method was used. As a result of the analysis, in some parts of research area remarkable shoreline changes (more than 765m withdrawal and 6120.68m/yr erosion in Yumurtalik, 650m withdrawal and 6125.99m/yr erosion in Goksu, 660m withdrawal and 6116.10m/yr erosion in Kizilirmak and 640m withdrawal and 614.91m/yr erosion in Yesilirmak) were observed for three periods (1989, 1999 and 2009). Wetland in Gediz delta which is 35.57km 2 was converted to sea or salt pan for the period 1975 and 2009.

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[15]
徐进勇,张增祥,赵晓丽,等.2000-2012年中国北方海岸线时空变化分析[J].地理学报,2013,68(5):651-660.利用遥感和GIS技术获取了中国北方"三省一市"2000年、2005年、2008年、2010年、2011年与2012年共6期大陆海岸线的时空分布情况;采用网格法计算了各个时期海岸线的分形维数;分析了海岸线时空变化特征、海岸线长度变化与分形维数变化之间的关系,以及海岸线动态变化的原因。2000-2012年,研究区海岸线长度持续增加,总共增加了637.95km,年均增加53.16km。从区域上看,以天津市与河北省所在的渤海湾区域海岸线变化最强烈;从时间过程上看,2008年后海岸线长度进入快速增长时期,其中2010-2011年是海岸线长度变化最剧烈的时期,变化强度为2.49%。2000-2012年研究区海岸线的分形维数不断增大,其中渤海湾区域海岸线分形维数变化最剧烈;历史海岸线的长度与分形维数之间存在较好的线性关系,相关系数为0.9962;通过对大量海岸线动态引起的整体海岸线长度变化与分形维数变化的统计分析研究表明,在大多数情况下,局部海岸线长度增大(或缩减)会导致整体海岸线分形维数增大(或减小),并且呈正比例变化。从2000-2012年各时段海岸线动态对应的各类沿海工程的面积汇总情况来看,港口建设、渔业设施建设以及盐场建设分别占前三位,人类工程建设是中国北方海岸线变化最主要原因;与人类活动影响相比,自然变化如河口淤积与侵蚀对海岸线影响比较小。

DOI

[ Xu J Y, Zhang Z X, Zhao X L, et al.Spatial-temporal analysis of coastline changes in northern China from 2000 to 2012[J]. Acta Geographica Sinica, 2013,68(5):651-660. ]

[16]
高志强,刘向阳,宁吉才,等.基于遥感的近30a中国海岸线和围填海面积变化及成因分析[J].农业工程学报,2014,30(12):140-147.该文利用4期遥感影像和中国沿海地区调查资料,综合运用遥感和GIS技术,结合Google Earth/Google Maps在线遥感信息,完成了对中国沿海地区1980-2010年间海岸线变迁和围填海演变信息的提取,并对其具体进程和驱动因素进行了深入研究,研究表明:30 a间,中国海岸线呈增长趋势,海岸线变迁程度较为剧烈,80年代中国海岸线变迁面积最大,90年代变迁面积最小,中国海岸线的变迁方向是向海洋推进,且推进的趋势越来越明显。1990-2000年间,中国沿海地区围填海增加面积最少;2000-2010年间,中国沿海地区围填海增加面积最多,远远大于其他时期的增加量。30 a间,围填海利用类型经历了从农业用地为主到养殖池为主再到待利用水面为主的演变过程;待利用水面是30 a围填海增加面积最大的利用类型;港口所占比例不断上升,而农业用地所占比例则在逐渐下降。人为因素是近30 a中国海岸线变迁的关键因素,自然因素和社会因素共同决定了沿海地区围填海的演变过程。该文可为海岸带规划管理和可持续发展提供数据支持。

DOI

[ Gao Z Q, Liu X Y, Ning J C, et al.Analysis on changes in coastline and reclamation area and its causes based on 30-year satellite data in China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014,30(12):140-147. ]

[17]
Hapke C J, Reid D, Richmond B.Rates and trends of coastal change in California and the regional behavior of the beach and cliff system[J]. Journal of Coastal Research, 2009, 25(3): 603-615.HAPKE, C.J.; REID, D., and RICHMOND, B., 2009. Rates and trends of coastal change in California and the regional behavior of the beach and cliff system. Journal of Coastal Research, 25(3), 603鈥615. West Palm Beach (Florida), ISSN 0749-0208. The U.S. Geological Survey (USGS) recently completed an analysis of shoreline change and cliff retreat along the California coast. This is the first regional, systematic measurement of coastal change conducted for the West Coast. Long-term (120 y) and short-term (25 y) shoreline change rates were calculated for more than 750 km of coastline, and 70 year cliff-retreat rates were generated for 350 km of coast. Results show that 40% of California's beaches were eroding in the long term. This number increased to 66% in the short term, indicating that many beaches have shifted toward a state of chronic erosion. The statewide average net shoreline change rates for the long and short term were 0.2 m/y and 0.2 m/y, respectively. The long-term accretional signal is likely related to large coastal engineering projects in some parts of the state and to large fluxes of sediment from rivers in other areas. The cliff-retreat assessment yielded a statewide average of 0.3 m/y. It was found that Northern California has the highest overall retreat rates, which are influenced by erosion hot spots associated with large coastal landslides and slumps. The databases established as part of the shoreline change and cliff-retreat analyses were further investigated to examine the dynamics of the beach/cliff system. A correlation analysis identified a strong relationship between the geomorphology of the coast and the behavior of the beach/cliff system. Areas of high-relief coast show negative cor-relations, indicating that higher rates of cliff retreat correlate with lower rates of shoreline erosion. In contrast, low-to moderate-relief coasts show strong positive correlations, wherein areas of high shoreline change correspond to areas of high cliff retreat.

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[18]
Schupp C A, McNinch J E, List J H. Nearshore shore-oblique bars, gravel outcrops, and their correlation to shoreline change[J]. Marine Geology, 2006,233(1):63-79.This study demonstrates the physical concurrence of shore-oblique bars and gravel outcrops in the surf zone along the northern Outer Banks of North Carolina. These subaqueous features are spatially correlated with shoreline change at a range of temporal and spatial scales. Previous studies have noted the existence of beach-surf zone interactions, but in general, relationships between nearshore geological features and coastal change are poorly understood. These new findings should be considered when exploring coastal zone dynamics and developing predictive engineering models.The surf zone and nearshore region of the Outer Banks is predominantly planar and sandy, but there are several discrete regions with shore-oblique bars and interspersed gravel outcrops. These bar fields have relief up to 3 m, are several kilometers wide, and were relatively stationary over a 1.5 year survey period; however, the shoreward component of the bar field does exhibit change during this time frame. All gravel outcrops observed in the study region, a 40 km longshore length, were located adjacent to a shore-oblique bar, in a trough that had width and length similar to that of the associated bar. Seismic surveys show that the outcrops are part of a gravel stratum underlying the active surface sand layer.Cross-correlation analyses demonstrate high correlation of monthly and multi-decadal shoreline change rates with the adjacent surf-zone bathymetry and sediment distribution. Regionally, areas with shore-oblique bars and gravel outcrops are correlated with on-shore areas of high short-term shoreline variability and high long-term shoreline change rates. The major peaks in long-term shoreline erosion are onshore of shore-oblique bars, but not all areas with high rates of long-term shoreline change are associated with shore-oblique bars and troughs.

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[19]
孙晓宇,吕婷婷,高义,等.2000-2010年渤海湾岸线变迁及驱动力分析[J].资源科学,2014,36(2):413-419.利用多期遥感数据，以2年为时间步长提取了2000-2010年间各时期渤海湾海岸线空间位置、长度以及结构信息。通过空间分析，以岸线长度和陆域面积增长为数量指标对海岸线的时空变迁过程进行了定量反演，并进行了驱动力和影响分析。研究表明，研究期渤海湾岸线变化显著，岸线总长度增长了约427km，几乎全部为人工岸线，自然岸线变化微弱。由岸线变迁所造成的陆域面积增长达到937km2。海岸线变迁的主要驱动力表现为前期的围垦养殖以及中后期的工业园区和港口的建设。主要的陆域增长点为沾化和无棣沿海地区、曹妃甸工业区，天津滨海新区以及黄骅港、滨州港、东营港等。2010年的渤海湾海岸线形态相比于2000年要粗糙很多，10年间新增加了4处向海延伸20km左右的人工建筑以及多处10km左右的人工建筑，岸线形态的变化必然对渤海湾水动力环境造成显著影响。

[ Sun X Y, Lü T T, Gao Y, et al.Driving force analysis of Bohai Bay coastline change from 2000 to 2010[J]. Resources Science, 2014,36(2):413-419. ]

[20]
毋亭,侯西勇.海岸线变化研究综述[J].生态学报,2016,36(4):1170-1182.受全球及海岸带区域环境过程与人类活动的综合影响,海岸线发生剧烈的变化,对生态、环境及经济社会的影响不容忽视,海岸线变化相关研究因此得到普遍的关注。在讨论海岸线的定义和分类的基础上,介绍岸线信息提取的方法与技术,总结国内外海岸线变化的特征、机制与影响方面研究的进展,并指出未来研究的趋势,包括:对海岸线变化过程进行动态监测仍将是普遍关注的研究重点之一;对海岸线变化特征、规律与机理的认识已经日益深化,基于大量高精度数据和机理模型的研究已成为热点和前沿问题;针对不同的海岸带区域,聚焦海岸线变化的原因和机制及其对环境和生态的影响,以及不同区域之间的相互联系与影响特征,这将是未来研究的重点之一;中国海岸线变化的独特性、复杂性突出,促进和支撑中国的海岸带综合管理实践,提高决策者与管理者对岸线变化所带来的灾害风险的重视,为中国海岸带的科学规划与发展提供依据,这应该是我国海岸线变化研究的重要目标。

DOI

[ Wu T, Hou X Y.Review of research on coastline changes[J]. Acta Ecologica Sinica, 2016,36(4):1170-1182. ]

[21]
Chander G, Markham B L, Helder D L.Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors[J]. Remote Sensing of Environment, 2009,113:893-903.This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of-Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.

DOI

[22]
Charvz P S Jr. Image-based atmospheric corrections: Revisited and revised[J]. Photogrammetric Engineering and Remote Sensing, 1996,62(9):1025-1036.

[23]
徐涵秋. 基于影像的 Landsat TM/ETM+数据正规化技术[J].武汉大学学报信息科学版,2007,32(1):62-66.阐述了基于影像的Landsat TM/ETM+的数据正规化技术及其发展.该技术通过将Landsat影像的亮度值转换成传感器处的辐射值和反射率来对影像进行辐射校正.实例表明,使用 正规化技术处理后的影像可以明显削弱日照和大气的影响,去除它们产生的噪声;其所求的传感器处的反射率与地面实测反射率的RMS值非常小.

DOI

[ Xu H Q.Image-based normalization technique used for Landsat TM/ETM+ imagery[J]. Geomatics and Information Science of Wuhan University, 2007,32(1):62-66. ]

[24]
Boak E H, Turner I L.Shoreline definition and detection: A review[J]. Journal of Coastal Research, 2005,21(4):688-703.

[25]
Dolan R, Hayden B P, May P, et al.The reliability of shoreline change measurements from aerial photographs[J]. Shore and Beach, 1980,48(4): 22-29.The study described indicates that the aerial photographic method provides statistically reliable measures of erosion along the Atlantic and Gulf coasts which appear to be adequate for long-term planning use in determining setback lines for North Carolina and regional-scale planning in Louisiana. Schematic representation of the shoreline and limit of storm-surge penetration on a barrier island are given.

[26]
王颖. 中国区域海洋学:海洋地貌学[M].北京:海洋出版社,2012.

[ Wang Y.Regional oceanography of China seas: Marine geomorphology[M]. Beijing: China Ocean Press, 2012. ]

[27]
Xu H Q.Modification of the normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery[J]. International Journal of Remote Sensing, 2006,73(12):1381-2033.The normalized difference water index (NDWI) of McFeeters (1996) was modified by substitution of a middle infrared band such as Landsat TM band 5 for the near infrared band used in the NDWI. The modified NDWI (MNDWI) can enhance open water features while efficiently suppressing and even removing built-up land noise as well as vegetation and soil noise. The enhanced water information using the NDWI is often mixed with built-up land noise and the area of extracted water is thus overestimated. Accordingly, the MNDWI is more suitable for enhancing and extracting water information for a water region with a background dominated by built-up land areas because of its advantage in reducing and even removing built-up land noise over the NDWI.

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[28]
Ghosh M K, Kumar L, Roy C.Monitoring the coastline change of Hatiya island in Bangladesh using remote sensing techniques[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015,101:137-144.A large percentage of the world鈥檚 population is concentrated along the coastal zones. These environmentally sensitive areas are under intense pressure from natural processes such as erosion, accretion and natural disasters as well as anthropogenic processes such as urban growth, resource development and pollution. These threats have made the coastal zone a priority for coastline monitoring programs and sustainable coastal management. This research utilizes integrated techniques of remote sensing and geographic information system (GIS) to monitor coastline changes from 1989 to 2010 at Hatiya Island, Bangladesh. In this study, satellite images from Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) were used to quantify the spatio-temporal changes that took place in the coastal zone of Hatiya Island during the specified period. The modified normalized difference water index (MNDWI) algorithm was applied to TM (1989 and 2010) and ETM (2000) images to discriminate the land鈥搘ater interface and the on-screen digitizing approach was used over the MNDWI images of 1989, 2000 and 2010 for coastline extraction. Afterwards, the extent of changes in the coastline was estimated through overlaying the digitized maps of Hatiya Island of all three years. Coastline positions were highlighted to infer the erosion/accretion sectors along the coast, and the coastline changes were calculated. The results showed that erosion was severe in the northern and western parts of the island, whereas the southern and eastern parts of the island gained land through sedimentation. Over the study period (1989鈥2010), this offshore island witnessed the erosion of 6476 hectares. In contrast it experienced an accretion of 9916 hectares. These erosion and accretion processes played an active role in the changes of coastline during the study period.

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[29]
王琳,徐涵秋,李胜.厦门岛及其邻域海岸线变化的遥感动态监测[J].遥感技术与应用,2005,20(4):404-410.利用美国Landsat TM/ETM+卫星影像,分1989、1995和2000年3个时相,研究了福建省厦门市从1989~2000年的岸线变化情况。岸线变化的信息主要通过变化检测和信息提取等一系列遥感技术来获得。研究结果表明,厦门市在所研究的1989~2000年期间,海域面积共减少了7.54 km2,这主要是由于城市用地扩展和养殖业发展占用了海域的面积。分时段研究表明,从1995~2000年,海域减少的面积明显要比1989~1995年期间来的多,这从一个侧面反映了厦门在1995~2000年间,城市建设和经济发展对土地提出了更高的需求。

DOI

[ Wang L, Xu H Q, Li S.Dynamic monitoring of the shoreline changes in Xiamen Island with its surrounding areas of SE China using remote sensing technology[J]. Remote Sensing Technology and Application, 2005,20(4):404-410. ]

[30]
Smith G L, Zarillo G A.Calculating long-term shoreline recession rates using aerial photographic and beach profiling techniques[J]. Journal of Coastal Research, 1990:111-120.Univ. Wisconsin, dep. geology geophysics, Madison WI 53706, ETATS-UNIS02 0202 02 0202JCRSEK02 1990,02vol.026,02n1,02pp.02111-12002(24 ref.)AnglaisCoastal Education and Research Foundation, Lawrence, KS, ETATS-UNIS02 (1985) (Revue); ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; INIST-CNRS, Cote INIST : 20944

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[31]
Mandelbrot B.How Long is the coast of Britain? Statistical self-similarity and fractional dimension[J]. Science, 1967,156(3775):636-638.Geographical curves are so involved in their detail that their lengths are often infinite or, rather, undefinable. However, many are statistically "selfsimilar," meaning that each portion can be considered a reduced-scale image of the whole. In that case, the degree of complication can be described by a quantity D that has many properties of a "dimension," though it is fractional; that is, it exceeds the value unity associated with the ordinary, rectifiable, curves.

DOI PMID

[32]
韩雪培,傅小毛,汤景燕,等. 图上曲线长度量算的分维纠正法[J].华东师范大学学报:自然科学版,2006(6):34-40.根据分形几何理论并借鉴前人研究的成果,提出了一种基于GIS软件平台的数字地图曲线长度纠正法.详细讨论了该纠正法的原理及实现过程,并利用多种比例尺资料对我国海岸线长度进行了量算和纠正,结果表明该方法可以使数字地图的量算误差得到明显的改善.

DOI

[ Han X P, Fu X M, Tang J Y, et al.Fractal method for correcting the length of map curves[J]. Journal of East China Normal University (Natural Science), 2006,6:34-40.

[33]
国家海洋局. HY/T 123-2009 海域使用分类[S].北京:标准出版社,2009.

[ State Oceanic Administration People's Republic of China HY/T 123-2009 Sea area use classification[S] HY/T 123-2009 Sea area use classification[S]. Beijing: Standards Press of China, 2009. ]

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