淤地坝是修建在多泥沙沟道中用于固沟减蚀、蓄洪滞洪和控制泥沙输移的一种水土保持工程措施，具有良好的水土保持功效，在拦泥淤地、滞洪蓄水、建设农田、巩固退耕还林（草）、发展生产、减轻黄河泥沙、改善生态环境等方面均发挥了重要作用。基于Google Earth 19级遥感影像数据，在黄河中上游流域通过目视解译标记了714张淤地坝样本，每个样本进行了图像增强，总产生了3570个淤地坝样本。此样本集可作为淤地坝图像识别的基础数据，促进黄河上中游区域的淤地坝自动识别研究。
", "ds_source": "样本基于Google Earth 遥感影像数据，使用BIGEMAP地图下载器获取缩放级别为19的Google Earth卫星图像，分辨率为0.54m/pixel，包括红、绿、蓝波段。
", "ds_process_way": "淤地坝一般位于沟道中，形似水坝，上窄下宽；坝体至少有一侧为淤积地、耕地或水域；一条沟道中可有多个淤地坝。对影像进行切片，切片后逐片进行标注。使用ArcGIS Pro的训练样本管理器进行样本的标记。
", "ds_quality": "样本标记来自于黄河上中游淤地坝密集修建区域，主要包括陕西省榆林地区、山西省吕梁和汾西县等，据统计数据分析，这两个区域的淤地坝修建数量占全国的60%以上，样本具有普适性。
", "ds_acq_start_time": "2018-10-23 00:00:00", "ds_acq_end_time": "2022-11-30 00:00:00", "ds_acq_place": "黄河上中游区域", "ds_acq_lon_east": 112.15972222222223, "ds_acq_lat_south": 33.62138888888889, "ds_acq_lon_west": 108.36277777777777, "ds_acq_lat_north": 37.811388888888885, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 1725045759, "ds_files_count": 2, "ds_format": "*.tif, *.twf, *.xml", "ds_space_res": "0.54", "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "b492be52-12fc-4013-8819-a966aec2d5af.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "52b7b79b-860c-49a5-9083-9a70cf8bed5a", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2024-02-29 11:26:50", "last_updated": "2025-04-24 16:16:34", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB4212.2024", "i18n": { "en": { "title": "A dataset of high-resolution optical remote sensing satellite image sample of sediment storage dams in the upper and middle reaches of the Yellow River", "ds_format": "*.tif, *.twf, *.xml", "ds_source": "The sample is based on Google Earth remote sensing image data, and the BIGEMAP map downloader is used to obtain Google Earth satellite images with a zoom level of 19, with a resolution of 0.54m/pixel, including red, green, and blue bands", "ds_quality": "
The sample markers come from the densely built areas of silt dams in the upper and middle reaches of the Yellow River, mainly including Yulin area in Shaanxi Province, Lvliang and Fenxi County in Shanxi Province. According to statistical data analysis, the number of silt dams built in these two areas accounts for more than 60% of the national total, indicating the universality of the sample", "ds_ref_way": "", "ds_abstract": "
A silt dam is a soil and water conservation engineering measure built in multi sediment channels for stabilizing gullies, reducing erosion, storing floodwaters, and controlling sediment transport. It has good soil and water conservation effects and plays an important role in blocking silt and siltation, storing floodwaters, constructing farmland, consolidating farmland for afforestation (grassland), developing production, reducing sediment in the Yellow River, and improving the ecological environment. Based on Google Earth 19 level remote sensing image data, 714 sediment dam samples were visually interpreted and labeled in the upper and middle reaches of the Yellow River basin. Each sample underwent image enhancement, resulting in a total of 3570 sediment dam samples. This sample set can serve as the basic data for image recognition of silt dams, promoting research on automatic recognition of silt dams in the upper and middle reaches of the Yellow River
", "ds_time_res": "", "ds_acq_place": "The upper and middle reaches of the Yellow River region", "ds_space_res": "0.54", "ds_projection": "", "ds_process_way": "A silt dam is generally located in a channel, resembling a dam, narrow at the top and wide at the bottom; At least one side of the dam body is silted land, cultivated land, or water; There can be multiple silt dams in a channel. Slice the image and label each slice after slicing. Use ArcGIS Pro's training sample manager to label samples", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "淤地坝", "遥感影像样本", "图像识别" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黄河上中游地区" ], "ds_time_tags": [ 2018, 2019, 2020, 2021, 2022 ], "ds_contributors": [ { "true_name": "敏玉芳", "email": "myf@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "艾鸣浩", "email": "aimh@lzb.ac.cn", "work_for": "中科院西北研究院", "country": "中国" }, { "true_name": "张耀南", "email": "yaonan@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "黄波", "email": "huangbo@lzb.ac.cn", "work_for": "中国科学院西北生态环境研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "敏玉芳", "email": "myf@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "敏玉芳", "email": "myf@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "水土保持" }