本数据集在谷歌地球引擎（GEE）平台上，利用陆地卫星专题成像仪（TM）、增强型专题成像仪增强版（ETM+）和陆地成像仪（OLI）影像的长时间序列，分析了 1990 年至 2019 年包括海南和台湾在内的中国海岸线的时空演变特征。
", "ds_source": "1、检索了 1990-2019 年期间所有可用的经地形校正（L1T）的第 1 级大地遥感卫星正射影像，包括专题成像仪（TM）、增强型专题成像仪增强版（ETM+）和陆地成像仪（OLI）。共有 60 527 幅大地遥感卫星图像（图 1b）作为美国地质调查局（USGS）图像集存档在谷歌地球引擎（GEE）平台上。
\n2、选取 17 个关键潮汐站，包括 8 个暖温带潮汐站、7 个亚热带潮汐站和 2 个热带潮汐站（Jia 等，2021 年）。这些站点的潮汐表可在网上查阅（https://www.chaoxibiao.net/，最后访问日期：2024 年 11 月 12 日）。为了消除降水的影响，选择了中国沿海地区雨季的潮汐数据，时间跨度为 4 月至 9 月（Liu et al.） 根据高潮时间和卫星过境时间，我们选择了 1583 幅图像来提取海岸线。
\n3、使用了三个全球海岸线数据集作为参考数据集。一个空间分辨率为 30 米的新全球海岸线矢量（GSV；Sayre 等人，2019 年）是根据 2014 年大地卫星卫星图像的年度合成图开发的。2015 年全球多尺度海岸线数据集（GMSSD_2015；Liu 等人，2019 年）是利用谷歌地球图像生成的。该数据集包括分辨率为米级的全球矢量海岸线数据，这些数据是通过人机交互和分析谷歌地球图像获得的。Coastline_ECS（Li 等人，2019 年）是东海地区大陆海岸线及其类型的时空变化数据集。该数据集涵盖 1990 年至 2015 年的 5 年时间间隔，使用 Landsat 图像，通过单波段边缘检测方法生成： 1990 年、2000 年和 2015 年。
", "ds_process_way": "采用基于指数时间序列重构的阈值分割方法。首先，利用时间序列谐波分析算法（HANTS）构建了高质量重构的修正归一化差异水指数（MNDWI）时间序列。其次，利用大津算法，根据高潮位的 MNDWI 值来分离沿海地区的陆地和水域。最后，生成了 30 年海岸线数据集。
", "ds_quality": "评估了提取的海岸线与参考数据集之间的一致性。结果显示，50% 以上样本点的偏移量小于 1 px。超过 70% 的样本点的偏移量小于 2 px，超过 80% 的样本点的偏移量小于 3 px。海岸线的最大平均绝对偏差为 57.98 米，最小平均绝对偏差为 29.35 米。用这种方法提取的海岸线与参考数据集具有良好的一致性，这在一定程度上证实了结果的可靠性。
", "ds_acq_start_time": "1990-01-01 00:00:00", "ds_acq_end_time": "2019-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 135.01666666666668, "ds_acq_lat_south": 3.8666666666666667, "ds_acq_lon_west": 73.66666666666667, "ds_acq_lat_north": 53.5, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 290985733, "ds_files_count": 3, "ds_format": "shp", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "9b6a5ff6-69ee-400f-958e-7ac066bb5260.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0a4269e1-65f4-45f1-aeba-88ea3068eebf", "ds_serv_man": "敏玉芳", "ds_serv_phone": "09314967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170" ], "quality_level": 3, "publish_time": "2025-01-24 10:10:31", "last_updated": "2026-01-14 10:52:50", "protected": false, "protected_to": null, "lang": "zh", "cstr": "https://cstr.cn/31253.11.sciencedb.16228", "i18n": { "en": { "title": "Using the 30 year change of coastline in Chinese Mainland, the time series analysis data of Landsat (1990-2019)", "ds_format": "shp", "ds_source": "1. We retrieved all available Level 1 Earth Remote Sensing satellite orthorectified images with terrain correction (L1T) from 1990 to 2019, including the Topographic Imager (TM), Enhanced Topographic Imager Plus (ETM+), and Land Imager (OLI). A total of 60527 land remote sensing satellite images (Figure 1b) are archived on the Google Earth Engine (GEE) platform as part of the United States Geological Survey (USGS) image collection.
\n2. Select 17 key tidal stations, including 8 warm temperate tidal stations, 7 subtropical tidal stations, and 2 tropical tidal stations (Jia et al., 2021). The tide tables for these sites can be found online（ https://www.chaoxibiao.net/ Last visit date: November 12, 2024. In order to eliminate the influence of precipitation, we selected tidal data from the rainy season in coastal areas of China, spanning from April to September (Liu et al.) Based on the high tide time and satellite transit time, we selected 1583 images to extract the coastline.
\n3. Three global coastline datasets were used as reference datasets. A new global coastline vector with a spatial resolution of 30 meters (GSV; Sayre et al., 2019) was developed based on the annual composite map of 2014 Landsat satellite images. The 2015 Global Multiscale Coastline Dataset (GMSSD_2015; Liu et al., 2019) was generated using Google Earth imagery. This dataset includes global vector coastline data with a resolution of meters, which was obtained through human-computer interaction and analysis of Google Earth images. Coastline_CS (Li et al., 2019) is a spatiotemporal dataset of the continental coastline and its types in the East China Sea region. This dataset covers a 5-year time interval from 1990 to 2015, generated using Landsat images and single band edge detection methods: 1990, 2000, and 2015.
", "ds_quality": "Evaluated the consistency between the extracted coastline and the reference dataset. The results showed that over 50% of the sample points had an offset of less than 1 px. More than 70% of the sample points had an offset of less than 2 px, and over 80% had an offset of less than 3 px. The maximum average absolute deviation of the coastline was 57.98 meters, and the minimum average absolute deviation was 29.35 meters. The coastline extracted by this method has good consistency with the reference dataset, which to some extent confirms the reliability of the results.
", "ds_ref_way": "", "ds_abstract": "This dataset uses the Google Earth Engine (GEE) platform to analyze the spatiotemporal evolution characteristics of China's coastline, including Hainan and Taiwan, from 1990 to 2019 using long time series of images from the Land Satellite Theme Imager (TM), Enhanced Theme Imager Plus (ETM+), and Land Imager (OLI).
", "ds_time_res": "", "ds_acq_place": "China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Adopting a threshold segmentation method based on exponential time series reconstruction. Firstly, a high-quality reconstructed Modified Normalized Difference Water Index (MNDWI) time series was constructed using the Time Series Harmonic Analysis Algorithm (HANTS). Secondly, using the Otsu algorithm, the land and water in coastal areas are separated based on the MNDWI value of high tide levels. Finally, a 30-year coastline dataset was generated.
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "海岸线", "Landsat 影像", "中国" ], "ds_subject_tags": [ "地球科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019 ], "ds_contributors": [ { "true_name": "孙伟伟", "email": "sunweiwei@nbu.edu.cn", "work_for": "宁波大学数学与统计学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "孙伟伟", "email": "sunweiwei@nbu.edu.cn", "work_for": "宁波大学数学与统计学院", "country": "中国" } ], "ds_managers": [ { "true_name": "孙伟伟", "email": "sunweiwei@nbu.edu.cn", "work_for": "宁波大学数学与统计学院", "country": "中国" } ], "category": "遥感及产品" }