本数据集为1970年代、1990年代、2000年、2010年塔里木河绿洲数据，包含塔里木河绿洲的\n（13）tm_oasis_1970\n（14）tm_oasis_1990\n（15）tm_oasis_2000\n（16）tm_oasis_2010
", "ds_source": "usgs数据获取
", "ds_process_way": "1.采用的遥感数据为Landsat MSS和TM/ETM数据，多光谱数据纠正后的影像采用432波段假彩色合成，在ARCGIS软件中通过人机交互方式以1：10万制图标准提取绿洲信息。\n2.数据生成流程为：影像下载-几何纠正-分类体系确定-解译标志确定-人机交互解译-精度验证
", "ds_quality": "1.原始资料数据精度\n严格按照仪器操作规范进行观测和数据采集，纠正后的图像满足同名像元误差平原地区小于1个像元，山区小于2个像元。\n2. 项目数据产生和汇集过程中的相关质量控制措施，包括完整的数据产生过程、使用的方法和标准规范、数据应用范围等内容。\n(1)数据生产过程: \n解译标志建立后就可进行图像解译的绿洲信息提取工作，解译过程中要求以相应时期的CBRES图像、土地覆盖、辅助数据和相应的地形图为综合信息源，由专业人员完成判读分析。在土地覆盖类型的属性判定中，水体、农田和建设用地等类型，要求准确率达到或超过90%，其他类型达到或超过80%。在类型界线勾绘时，遥感影像与土地覆盖主要类型便捷的对应点误差一般小于图上0.6mm，最大不超过图上1mm。\n信息提取时，根据信息源分辨率及制图精度要求，确定了以下解译原则：判读成图的最小图斑TM/ETM影像为6×6个象元，即180m×180m。屏幕解译线划描迹精度为1个象元，即线划定位精度相当于地面60米。解译完成后作业人员之间交换解译成果，以便相互详细查错补漏，然后送交质量检查组检查，对不满足质量要求的图幅重返前两道工序。经过三级工序的严格质量控制体系，保证了定位精度达1个像元，定性精度达95%以上。\n3.加工后数据精度\n为了保证解译的正确性，对四期绿洲数据进行抽查，通过再次判读，以保证信息提取精度达到设计要求。抽样时，采取随机抽样的方法，对全部图斑，以5%的抽样率以及10%的面积比例进行选取样本。判别标准采用多期河西走廊土地覆盖外业考察所获取的GPS定位信息、野外记录、照片等信息，以及各种相关的辅助资料信息。\n结果表明，全部抽样图斑达3704个，经判读确认有3609个图斑属性正确、95个图斑属性错误，解译定性正确率达到97.44%（表1.7）。各类型的准确率也达到了90%以上。其中水域湿地和建设用地分类准确率高达100%和98.51%，耕地和林地的准确率为96.85%和96.29%，草地中由于对低盖度草地的解译精度较低，所以草地的准确率较低，为93.81%。
", "ds_acq_start_time": "1970-01-01 00:00:00", "ds_acq_end_time": "2010-01-01 00:00:00", "ds_acq_place": "新疆塔里木河流域", "ds_acq_lon_east": 101.0, "ds_acq_lat_south": 42.0, "ds_acq_lon_west": 98.0, "ds_acq_lat_north": 38.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 11282297, "ds_files_count": 3, "ds_format": "adf", "ds_space_res": null, "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "ee05effb-ce34-491e-a31d-fbbf7d9fea4a.png", "ds_thumb_from": 0, "ds_ref_way": "颜长珍, 常存，西北干旱区塔里木河流域1：10万土地绿洲数据集(1970、1990、2000、2010年)，国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2020，doi：10.12072/ncdc.973Desert.db0006.2020", "paper_ref_way": "", "ds_ref_instruction": "使用本数据集时，请在文章中引用以下文献：\n [1]廖杰,王涛,薛娴. 近55a来黑河流域绿洲演变特征的初步研究. 2012, 中国沙漠, 32(5):1426-1441.\n", "ds_from_station": null, "organization_id": "eb2b3ac4-919d-433d-b987-bcee1ae83c9e", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": null, "quality_level": 3, "publish_time": "2020-12-21 11:56:48", "last_updated": "2020-12-21 11:56:48", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.973Desert.2020.106", "i18n": { "en": { "title": "", "ds_format": "", "ds_source": "USGS data acquisition
", "ds_quality": "1. Accuracy of original data\nObservation and data acquisition are carried out in strict accordance with the instrument operation specifications. The corrected image meets the requirements of the same pixel error. The error of plain area is less than 1 pixel, and that of mountain area is less than 2 pixels.\n2. Relevant quality control measures in the process of project data generation and collection, including complete data generation process, methods and standards, data application scope, etc.\n(1) Data production process:\nAfter the establishment of the interpretation mark, the oasis information can be extracted for image interpretation. In the process of interpretation, cbres image, land cover, auxiliary data and corresponding topographic map in corresponding period should be taken as the comprehensive information source, and the interpretation and analysis should be completed by professionals. In the attribute judgment of land cover type, the accuracy rate of water body, farmland and construction land should reach or exceed 90%, and that of other types should reach or exceed 80%. When drawing the type boundary, the error between the remote sensing image and the main types of land cover is generally less than 0.6 mm on the map, and the maximum error is no more than 1 mm on the map.\nAccording to the resolution of information source and the requirement of mapping accuracy, the following interpretation principles are determined: the minimum TM / ETM image is 6 × 6 pixels, namely 180m × 180m. The accuracy of line trace interpretation on screen is 1 pixel, that is, the positioning accuracy of line drawing is equivalent to 60 meters on the ground. After the interpretation is completed, the interpretation results are exchanged among the operators so as to check each other's errors and make up the omissions, and then send them to the quality inspection team for inspection, and return to the first two processes for the drawings that do not meet the quality requirements. Through the strict quality control system of three-level process, the positioning accuracy is up to 1 pixel, and the qualitative accuracy is more than 95%.\n3. Data accuracy after processing\nIn order to ensure the accuracy of the interpretation, the fourth phase of oasis data were selected and re interpreted to ensure the accuracy of information extraction to meet the design requirements. When sampling, random sampling method is adopted to select samples from all spots with a sampling rate of 5% and an area ratio of 10%. The discrimination criteria are GPS positioning information, field records, photos and other information obtained from multi-stage field investigation of land cover in Hexi Corridor, as well as various relevant auxiliary information.\nThe results showed that 3704 spots were sampled, 3609 spots were correct and 95 spots were wrong after interpretation, and the accuracy rate of qualitative interpretation was 97.44% (table 1.7). The accuracy of each type is more than 90%. The accuracy of water wetland and construction land was 100% and 98.51%, the accuracy of cultivated land and woodland was 96.85% and 96.29%. The accuracy of grassland was 93.81% because of the low coverage grassland.
", "ds_ref_way": "", "ds_abstract": "This data set is the data of Tarim River Oasis in 1970's, 1990's, 2000's and 2010's\n（13）tm_ oasis_ one thousand nine hundred and seventy\n（14）tm_ oasis_ one thousand nine hundred and ninety\n（15）tm_ oasis_ two thousand\n（16）tm_ oasis_ two thousand and ten
", "ds_time_res": "年", "ds_acq_place": "Tarim River Basin, Xinjiang", "ds_space_res": "", "ds_projection": "", "ds_process_way": "", "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": [ "绿洲", "遥感", "多光谱", "landsat", "土地利用" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "西北干旱区", "塔里木河绿洲", "新疆" ], "ds_time_tags": [ 1970, 1990, 2000, 2010 ], "ds_contributors": [ { "true_name": "颜长珍", "email": "yancz@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "常存", "email": "changc@ms.xjb.ac.cn", "work_for": "中国科学院新疆生态与地理研究所", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "颜长珍", "email": "yancz@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "常存", "email": "changc@ms.xjb.ac.cn", "work_for": "中国科学院新疆生态与地理研究所", "country": "中国" } ], "ds_managers": [ { "true_name": "王涛", "email": "wangtao@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "颜长珍", "email": "yancz@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "常存", "email": "changc@ms.xjb.ac.cn", "work_for": "中国科学院新疆生态与地理研究所", "country": "中国" } ], "category": "沙漠与荒漠化" }