Satellite-based shoreline detection: macrotidal high-energy coasts dataset

This dataset accompanies the article by Konstantinou et al. (2022) titled ‘Satellite-based shoreline detection: macrotidal high-energy coasts’. This study assesses the ability of existing satellite image analysis technology to capture shoreline position change at relevant magnitudes and timescales for two different coastal environments in the United Kingdom. It addresses the influence of tidal elevation and wave-induced water-level fluctuations at two sites representing end members of beach morphological type in a region of low satellite useability (high cloud cover combined with low image availability). The study uses 14 years of monthly topographic surveys at two macrotidal sites in the UK, combined with modelled wave data and harmonic tidal predictions to investigate the influence of tidal elevation and wave action on SDS accuracy.

Description

The dataset consists of two matlab files each containing the information listed below for the two test sites (Slapton Sands (SLSdata); Perranporth (PPTdata)):

dnum: date of satellite image capture in matlab datenum format

sat: name of satellite (L5=Landsat 5; L7=Landsat 7; L8=Landsat 8; S2=Sentinel-2)

transects: a structure containing the following variables:

profName – the name of the survey profile

startEast;   startNorth;   endEast;   endNorth: OSGB coordinates of the start (landward) and end (seaward) of the transect line

startUTMlat;   startUTMlon;   endUTMlat;   endUTMlon: WGS84-UTM30 coordinates of the start (landward) and end (seaward) of the transect line

orientation: profile orientation

shoreOrient: shoreline orientation

transAngle: profile angle to shore-normal.

transTimeSeries: time series of the intersection of the SDW at each transect in three columns that include chainage (m), longitude, latitude.

profData: a nested structure containing the survey data at organised by profile including survey date, OSGB and WGS84-UTM30 coordinates of surveyed points.

本数据集随附Konstantinou等人2022年发表的题为《基于卫星的海岸线检测：大潮差高能海岸》的学术文章。本研究针对英国两种不同海岸环境，评估现有卫星影像分析技术在匹配的量级与时间尺度下捕捉海岸线位置变化的能力。研究聚焦于卫星影像可用性较低（高云量结合低影像获取率）区域内代表两类典型海滩地貌端元的两个站点，探讨潮汐高程与波浪诱发水位波动的影响。研究使用英国两个大潮差站点14年的月度地形测量数据，结合模拟波浪数据与调和潮汐预报模型，分析潮汐高程与波浪作用对海岸线检测系统（Shoreline Detection System，简称SDS）精度的影响。

数据集说明
本数据集包含两个MATLAB文件，分别为两个测试站点存储如下信息：斯拉普顿沙滩（Slapton Sands，缩写SLSdata）、佩兰波斯（Perranporth，缩写PPTdata）：
1. dnum：以MATLAB datenum格式存储的卫星影像捕获日期
2. sat：卫星名称（L5=Landsat 5；L7=Landsat 7；L8=Landsat 8；S2=Sentinel-2）
3. transects：包含以下变量的结构体：
- profName：测量剖面的名称
- startEast、startNorth、endEast、endNorth：测线起点（向陆侧）与终点（向海侧）的OSGB坐标系坐标
- startUTMlat、startUTMlon、endUTMlat、endUTMlon：测线起点与终点的WGS84-UTM30坐标系坐标
- orientation：剖面方位
- shoreOrient：海岸线方位
- transAngle：剖面与岸线法线的夹角
4. transTimeSeries：各测线处SDW交集的时间序列，以三列形式存储，包含链长（m）、经度、纬度
5. profData：嵌套结构体，存储按剖面整理的测量数据，包含测量日期、测点的OSGB坐标系与WGS84-UTM30坐标系坐标