探地雷达（GPR）数据浅层地下结构勘探的有效地球物理手段之一。但传统地面探地雷达进行大范围探测时，需要消耗较多的人力物力，并且对于复杂地形地区，操作比较困难。本研究利用大疆FlyCart 30多旋翼无人机平台，搭载自主研发的100MHz脉冲探地雷达系统，结合背景去除、增益、带通滤波、中值滤波、自适应滤波的数据处理流程，实现了深度为7米的地下地质结构探测。相比传统地面探地雷达数据，本数据集具备无人机平台灵活机动、覆盖范围广且数据采集效率高的优势。该数据集适用于黄土滑坡地下地质结构识别、地下介质属性评估等领域，为兰州榆中地区黄土滑坡综合研究提供了重要数据支持。
", "ds_source": "大疆FlyCart 30无人机由中国深圳大疆创新科技有限公司于2023年8月推出的首款民用运载无人机（https://www.dji.com/cn/flycart-30）。该产品最大载重达30公斤，飞行海拔高度可达6000米，高防护高智能，在山地、岸基运输上得到了广泛应用。探地雷达数据是由无人机所搭载的100MHz脉冲探地雷达所采集，该探地雷达由项目参与单位中国大连中睿科技发展有限公司根据项目需求自主研发，探地雷达中心频率为100MHz,探测深度最大可达8米。
", "ds_process_way": "背景去除、增益、带通滤波、中值滤波、自适应滤波。
", "ds_quality": "采用包含背景去除、增益、带通滤波、中值滤波、自适应滤波的数据处理流程，可以识别出黄土滑坡地区地下地质构造，包括滑坡面及落水洞结构，并且最大可对地下7米的结构进行准确识别。因此，本数据集可作为黄土滑坡地下结构探测的可靠指标。
", "ds_acq_start_time": "2025-08-15 00:00:00", "ds_acq_end_time": "2025-08-16 00:00:00", "ds_acq_place": "兰州榆中", "ds_acq_lon_east": 104.5, "ds_acq_lat_south": 35.83305555555556, "ds_acq_lon_west": 103.83305555555555, "ds_acq_lat_north": 36.166666666666664, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 197442397, "ds_files_count": 0, "ds_format": "*.zxy", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "e38a1afc-e1b6-4f63-88fb-9d61558aa044.jpeg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": "", "organization_id": "bf138922-7121-438c-8d1b-19d5f751c907", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.2540" ], "quality_level": 0, "publish_time": "2026-05-21 17:34:38", "last_updated": "2026-05-21 17:34:38", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.loess.db7345.2026", "i18n": { "en": { "title": "Unmanned aerial vehicle ground penetrating radar dataset at Yuzhong, Lanzhou in 2025", "ds_format": "*.zxy", "ds_source": "The DJI FlyCart 30 drone, launched in August 2023 by Shenzhen DJI Innovations Technology Co., Ltd., China, is the company’s first civil cargo drone (https://www.dji.com/cn/flycart-30). This product has a maximum payload capacity of 30 kilograms and can fly at altitudes up to 6000 meters. Featuring high protection and advanced intelligence, it has been widely used in mountainous and shore-based transportation. The ground-penetrating radar (GPR) data was collected by a 100 MHz pulsed GPR mounted on the drone. This radar was independently developed by Dalian Zhongrui Technology Development Co., Ltd., a project participant, according to project requirements. The GPR operates at a central frequency of 100 MHz and can detect structures up to 8 meters deep.", "ds_quality": "
By employing a data processing workflow that includes background removal, gain adjustment, bandpass filtering, median filtering, and adaptive filtering, underground geological structures in loess landslide areas—such as the landslide surface and subsurface water channels—can be identified. Furthermore, structures up to 7 meters underground can be accurately detected. Therefore, this dataset can serve as a reliable indicator for detecting underground structures in loess landslide regions.", "ds_ref_way": "", "ds_abstract": "
Ground-penetrating radar (GPR) data is one of the effective geophysical methods for shallow subsurface structure exploration. However, traditional ground-based GPR surveys over large areas require substantial manpower and resources, and operations can be challenging in complex terrains. This study utilizes the DJI FlyCart 30 multirotor drone platform equipped with a self-developed 100 MHz pulsed GPR system. By applying a data processing workflow that includes background removal, gain adjustment, bandpass filtering, median filtering, and adaptive filtering, subsurface geological structures up to a depth of 7 meters were successfully detected. Compared to traditional ground-based GPR data, this dataset benefits from the drone platform’s flexibility, wide coverage, and high data acquisition efficiency. The dataset is suitable for applications such as identifying underground geological structures and assessing subsurface media properties in loess landslide areas, providing important data support for comprehensive research on loess landslides in the Lanzhou Yuzhong region.", "ds_time_res": "", "ds_acq_place": "Yuzhong, Lanzhou", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
Background removal, gain, bandpass filtering, median filtering, adaptive filtering.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 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": [ "无人机探地雷达" ], "ds_subject_tags": [ "空间物理探测" ], "ds_class_tags": [], "ds_locus_tags": [ "中国", "兰州", "榆中" ], "ds_time_tags": [ 2025 ], "ds_contributors": [ { "true_name": "冯晅", "email": "fengxuan@jlu.edu.cn", "work_for": "吉林大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "冯晅", "email": "fengxuan@jlu.edu.cn", "work_for": "吉林大学", "country": "中国" } ], "ds_managers": [ { "true_name": "冯晅", "email": "fengxuan@jlu.edu.cn", "work_for": "吉林大学", "country": "中国" } ], "category": "其他" }