2019年子午岭六盘山国家级重点预防区土地利用统计表数据集包括陕西省耀州区、王益区、印台区、宜君县、陈仓区、陇县、千阳县、麟游县、彬县、长武县、旬邑县、淳化县、甘泉县、富县、洛川县、黄龙县、黄陵县，甘肃省清水县、张家川、崆峒区、崇信县、华亭县、静宁县、正宁县，宁夏回族自治区隆德县、泾源县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": "子午岭六盘山国家级重点预防区", "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": 350056, "ds_files_count": 2, "ds_format": "xlsx", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "7c328abb-ac73-491d-9d3c-4639c394e0d3.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.db2662.2022", "subject_codes": [], "quality_level": 3, "publish_time": "2021-10-27 14:08:43", "last_updated": "2025-10-15 14:48:46", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.HHSTBC.2021.311", "i18n": { "en": { "title": "Land use data set of Liupanshan national key prevention area in Ziwuling 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 data set of land use statistics of Liupanshan national key prevention area in Ziwuling in 2019 includes Yaozhou District, Wangyi District, Yintai District, Yijun County, Chencang District, Longxian County, Qianyang County, Linyou County, Binxian County, Changwu County, Xunyi County, Chunhua County, Ganquan County, Fuxian County, Luochuan County, Huanglong County, Huangling County, Qingshui County, Zhangjiachuan county, Kongtong District, Chongxin County in Gansu Province The land use statistical tables of Huating County, Jingning County, Zhengning County, Longde County and Jingyuan County of Ningxia Hui Autonomous Region in 2019 are obtained by processing satellite remote sensing images with spatial resolution better than 16m, and the storage format is xlsx. The data naming adopts 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": "Ziwuling Liupanshan national key prevention area", "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.
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