该数据集具有高覆盖性、时效性好（2020年）、分辨率高（10米）的特点，以渭河流域为研究区域，提取基于机器学习方法对哨兵2遥感影像处理的土地利用数据，分为十大类（水体、树木、草地、被淹没的植被、农作物、灌丛/灌木、建筑区、裸地、雪/冰、云层）。", "ds_source": "
数据来源于https://livingatlas.arcgis.com/landcover/", "ds_process_way": "
基于10米分辨率的欧空局哨兵2号遥感影像。通过机器学习的方法获取2020年全年10类土地利用数据；以甘肃省为研究区域，掩膜提取渭河流域2020年空间分辨率为10米的土地利用数据。", "ds_quality": "
数据质量良好。", "ds_acq_start_time": "2020-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "甘肃省", "ds_acq_lon_east": 108.7075, "ds_acq_lat_south": 32.596111111111114, "ds_acq_lon_west": 92.33777777777777, "ds_acq_lat_north": 42.79333333333333, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 416542472, "ds_files_count": 7, "ds_format": "tif", "ds_space_res": "10m", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "UTM", "ds_thumbnail": "0dc7ec51-e581-4ffc-8c51-fe6a2ab259a8.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "526ff655-4cd4-4650-bb86-6fd3481dfb65", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2023-12-27 09:59:42", "last_updated": "2025-06-30 16:30:18", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.GSEER.DB4146.2023", "i18n": { "en": { "title": "Gansu Province Land Use LC10 Meter Dataset (2020)", "ds_format": "tif", "ds_source": "
The data comes from https://livingatlas.arcgis.com/landcover/", "ds_quality": "
The data quality is good.", "ds_ref_way": "", "ds_abstract": "
This dataset has the characteristics of high coverage, good timeliness (2020), and high resolution (10 meters). Taking the Weihe River Basin as the research area, land use data based on machine learning methods for Sentinel-2 remote sensing image processing were extracted and divided into ten categories (water bodies, trees, grasslands, submerged vegetation, crops, shrubs/shrubs, built-up areas, bare land, snow/ice, clouds).
", "ds_time_res": "年", "ds_acq_place": "Gansu Province", "ds_space_res": "10m", "ds_projection": "", "ds_process_way": "Based on the 10 meter resolution European Space Agency Sentinel-2 remote sensing image. Obtain 10 types of land use data for the whole year of 2020 through machine learning methods; Using Gansu Province as the research area, mask extraction of land use data with a spatial resolution of 10 meters in the Weihe River Basin in 2020.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC 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": [ "土地利用", "甘肃省", "遥感" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "甘肃省" ], "ds_time_tags": [ 2020 ], "ds_contributors": [ { "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" } ], "ds_meta_authors": [ { "true_name": "李红星", "email": "lihongxing@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": "基础地理" }