2019年天山北坡国家级重点预防区土地利用数据集包括新疆维吾尔自治区天山区、达坂城区、乌鲁木齐县、独山子区、哈密市、伊吾县、巴里坤哈萨克自治县、昌吉市、阜康市、呼图壁县、玛纳斯县、奇台县、吉木萨尔县、木垒哈萨克自治县、博乐市、精河县、温泉县、塔城市、乌苏市、额敏县、沙湾县、托里县、裕民县、石河子市、五家渠市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。\n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。\n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。\n基于遥感影像，结合解译标志，提取土地利用类型。\n解译结果复查：抽取不少于总图斑的5%进行核查。\n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": "天山北坡国家级重点预防区", "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": 279590, "ds_files_count": 2, "ds_format": "xlsx", "ds_space_res": "16m", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "5bfc469e-9eb1-44c7-bf9e-eed2ab56277b.png", "ds_thumb_from": 0, "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.db2637.2022", "subject_codes": [], "quality_level": 3, "publish_time": "2021-10-27 14:08:16", "last_updated": "2025-10-15 14:42:14", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.HHSTBC.2021.296", "i18n": { "en": { "title": "Data set of land use statistical table of national key prevention area on northern slope of Tianshan Mountain in 2018", "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.\nThe 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.\nBefore remote sensing image interpretation, the land use remote sensing interpretation marks are established by using remote sensing image, typical survey and field comparison.\nBased on remote sensing images, combined with interpretation marks, land use types are extracted.\nRe examination of interpretation results: no less than 5% of the total map spots shall be selected for verification.\nThe 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 national key prevention areas on the northern slope of Tianshan Mountain in 2019 includes Tianshan District, Dabancheng District, Urumqi county, Dushanzi District, Hami City, Yiwu County, Balikun Kazakh Autonomous County, Changji City, Fukang City, Hutubi County, Manas County, Qitai County, jimusar County, Mulei Kazakh Autonomous County, Bole City, Jinghe county The land use statistical tables of Wenquan County, Tacheng City, Wusu city, Emin County, Shawan County, Tuoli County, Yumin County, Shihezi city and Wujiaqu City in 2019 are obtained by processing satellite remote sensing images with spatial resolution better than 16m. The saved 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": "年", "ds_acq_place": "National key prevention area on the north slope of Tianshan Mountain", "ds_space_res": "16m", "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", "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": [ "新疆维吾尔自治区天山区，达坂城区，乌鲁木齐县，独山子区，哈密市，伊吾县，巴里坤哈萨克自治县，昌吉市，阜康市，呼图壁县，玛纳斯县，奇台县，吉木萨尔县，木垒哈萨克自治县，博乐市，精河县，温泉县，塔城市，乌苏市，额敏县，沙湾县，托里县，裕民县，石河子市，五家渠市" ], "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" }