2019年黄河多沙粗沙国家级重点治理区土地利用数据集包括山西省古交市、娄烦县、右玉县、静乐县、神池县、五寨县、岢岚县、河曲县、保德县、偏关县、吉县、乡宁县、大宁县、隰县、永和县、蒲县、汾西县、离石区、兴县、临县、柳林县、石楼县、岚县、方山县、中阳县、交口县，\n内蒙古托克托县、和林格尔县、清水河县、东胜区、达拉特旗、准格尔旗、鄂托克前旗、鄂托克旗、杭锦旗、乌审旗、伊金霍洛旗、磴口县、凉城县，陕西省韩城市、宝塔区、安塞县、延长县、延川县、子长县、志丹县、吴起县、宜川县、榆阳区、神木市、府谷县、横山区、靖边县、定边县、绥德县、米脂县、佳县、吴堡县、清涧县、子洲县，永乐县\n甘肃省泾川县、灵台县、西峰区、庆城县、环县、华亭县、合水县、宁县、镇原县，宁夏回族自治区盐池县70个县2019年的土地利用统计表，基于空间分辨率优于16m的卫星遥感影像加工获得，保存格式为xlsx，数据命名采用“所属重点治理区＋行政区＋年份＋土地利用统计表”的形式，如“××重点治理区××县××年土地利用统计表”。土地利用的分类系统包括8个一级类、25个二级类。
", "ds_source": "土地利用遥感影像数据源为资源三号和高分一号卫星影像，从水利部信息中心获取。
", "ds_process_way": "基于eCognition软件平台，采用面向对象计算机自动分类与人工目视解译相结合的方法，提取研究区逐年土地利用数据。最后采用三种方法对数据精度进行验证：野外样本点调查、高分辨率影像识别和Google Earth的样本点识别。
", "ds_quality": "遥感影像均经过辐射纠正、正射纠正以及融合、镶嵌等预处理。 最小图斑面积对应的实际地物面积不小于0.1h㎡，多边形无重叠、无空隙，图斑属性无空置或冗余。 遥感影像解译前，采用遥感影像、典型调查、与实地对照的方法建立土地利用遥感解译标志。 基于遥感影像，结合解译标志，提取土地利用类型。 解译结果复查：抽取不少于总图斑的5%进行核查。 野外验证样本数量和成果满足《水土保持遥感监测技术规范》（SL592-2012）的要求，对于核查图斑，抽取10%作为验证样本进行实地验证。
", "ds_acq_start_time": "2019-01-01 00:00:00", "ds_acq_end_time": "2019-12-31 00:00:00", "ds_acq_place": "黄河多沙粗沙国家级重点治理区", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 300292, "ds_files_count": 2, "ds_format": "xlsx", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "cbb60a43-4e4e-4fdc-93f7-ab86b70c8072.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "18fc6591-ef53-4202-bc01-c3961ad212d2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.hhstbc.db2673.2022", "subject_codes": [], "quality_level": 3, "publish_time": "2021-10-27 14:09:18", "last_updated": "2025-10-15 14:48:50", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.HHSTBC.2021.315", "license": null, "i18n": { "en": { "title": "Land use data set of the Yellow River Sandy and coarse sand national key control area in 2019", "ds_format": "", "ds_source": "Land use remote sensing image data sources are ZY-3 and Gao FEN-1 satellite images, which are obtained from the information center of the Ministry of water resources.
", "ds_quality": "Remote sensing images are preprocessed by radiation correction, ortho rectification, fusion and mosaic. The actual surface area corresponding to the minimum spot area is not less than 0.1 h ^, the polygons have no overlap or gap, and the spot attributes have no vacancy or redundancy. Before remote sensing image interpretation, the land use remote sensing interpretation marks are established by using remote sensing image, typical survey and field comparison. Based on remote sensing images, combined with interpretation marks, land use types are extracted. Re examination of interpretation results: no less than 5% of the total map spots shall be selected for verification. The number and results of field verification samples meet the requirements of technical specification for remote sensing monitoring of soil and water conservation (sl592-2012). For verification spots, 10% of them are selected as verification samples for field verification.
", "ds_ref_way": "", "ds_abstract": "The land use data set of the Yellow River Sandy and coarse sand national key control areas in 2019 includes Gujiao City, Loufan County, Youyu County, jingle County, Shenchi County, Wuzhai County, Kelan County, Hequ County, Baode County, Pianguan County, Ji County, Xiangning County, Daning County, Xi county, Yonghe County, Pu County, Fenxi County, Lishi District, Xingxian County, Linxian County, Liulin County, Shilou County, Lan county Fangshan County, Zhongyang County, Jiaokou County,\nTuoketuo County, Helingeer County, Qingshuihe County, Dongsheng District, Dalate Banner, Zhungeer banner, Etuokeqian banner, Etuoke Banner, Hangjin Banner, Wushen Banner, Yijinhuoluo banner, Dengkou County, Liangcheng County in Inner Mongolia; Hancheng City, Baota District, Ansai County, Yanchang County, Zichang County, Zhidan County, Wuqi County, Yichuan County, Yuyang District, Shenmu City, Fugu County in Shaanxi Province Hengshan District, Jingbian County, Dingbian County, Suide County, Mizhi County, Jia County, Wubao County, Qingjian County, Zizhou County, Yongle County\nThe land use statistics of Jingchuan County, Lingtai County, Xifeng District, Qingcheng County, Huan County, Huating County, Heshui County, Ning county and Zhenyuan County in Gansu Province, and 70 counties in Yanchi County in Ningxia Hui Autonomous Region in 2019 are obtained by processing satellite remote sensing images with spatial resolution better than 16m, and the preservation format is xlsx, The data is named in the form of \"key governance area + administrative region + year + land use statistical table\", such as“ ×× Key governance areas ×× county ×× Statistics of land use in 2001 \". The classification system of land use includes 8 first class and 25 second class.
", "ds_time_res": "", "ds_acq_place": "National key control area of Yellow River with abundant and coarse sediment", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Based on ecognition software platform, the method of object-oriented computer automatic classification combined with manual visual interpretation was used to extract the land use data of the study area year by year. Finally, three methods are used to verify the accuracy of the data: field sample point survey, high-resolution image recognition and Google Earth sample point recognition.
", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [ "土地利用统计表，8个一级类要素，25个二级类要素" ], "ds_subject_tags": [], "ds_class_tags": [], "ds_locus_tags": [ "黄河多沙粗沙国家级重点治理区，山西省，内蒙古，陕西省，甘肃省，宁夏回族自治区" ], "ds_time_tags": [], "ds_contributors": [ { "true_name": "黄河流域水土保持生态环境监测中心", "email": "1283337@qq.com", "work_for": "黄河流域水土保持生态环境监测中心", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "黄河流域水土保持生态环境监测中心", "email": "szyjdata@163.com", "work_for": "黄河流域水土保持生态环境监测中心", "country": "中国" } ], "ds_managers": [ { "true_name": "黄河流域水土保持生态环境监测中心", "email": "szyjdata@163.com", "work_for": "黄河流域水土保持生态环境监测中心", "country": "中国" } ], "category": "水土保持" }