本数据集包含我国典型积雪区2018-2019年积雪季11个测雪路线（snow course）的积雪深度、雪压及积雪密度数据。测雪线路主要位于我国新疆、青海、内蒙及东北地区。
\n数据集按照snow course的位置编号和观测日期建立11个文件夹，每个子文件夹均包括一个kmz或shp格式的观测点分布文件、一个观测点示意图、一个记录观测数据的电子表格和观测时纸质表格的扫描档。其中2号线观测记录无纸质观测表扫描档和观测点分布的矢量文件，共169条记录。数据集同时还包含一个用于数据质量检查的数据自检表。数据集命名规则、时间范围及线路经纬度等见说明文档。
", "ds_source": "本数据集为自主观测的野外数据。
", "ds_process_way": "该数据集来自各单位的野外观测数据。样方数据中经纬度及高程信息来自手持GPS。雪深、雪压数据分别来自量尺和雪筒。雪深数据为三次测量的平均值。雪压数据通过人工称量装在雪筒中的一定体积的积雪重量得到。密度数据通过雪压和雪深数据相除得到。
", "ds_quality": "首先通过野外实测获得原始的数据资料，之后对数据进行质量控制。
\n数据质量控制阶段分两步：首先数据提供者对数据进行了完整性、准确性检查。数据完整性检查主要检查数据的观测点数目及观测字段是否达到项目要求。数据准确性检查一方面通过数值图示判断异常值并进行剔除，另一方面对数据的存储方式、数据格式进行统一与规范。第二阶段是数据提供者对其它组的数据进行交叉检查，再次审核数据的完整性和准确性，并对不同区域的数据进行整合。其中，用于数据质量控制的数据自检表及数据分析图一并存于数据集文件夹中。
\n最后整合各组观测数据，得到完整、准确、格式一致的snow course数据集。
", "ds_acq_start_time": "2017-01-01 00:00:00", "ds_acq_end_time": "2019-12-31 00:00:00", "ds_acq_place": "新疆、青海、内蒙古、东北地区", "ds_acq_lon_east": 128.97722222222222, "ds_acq_lat_south": 37.858333333333334, "ds_acq_lon_west": 87.6713888888889, "ds_acq_lat_north": 50.45, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 131323165, "ds_files_count": 101, "ds_format": "xlsx,jpg(tiff),shp(kmz)", "ds_space_res": null, "ds_time_res": "日、时、分", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "483f67bf-85a4-4055-ad3c-04fbdfdaecc8.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "aba68fe5-65d3-41b1-b036-bc274a834b5e", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.I-SNOW.db0014.2021", "subject_codes": [], "quality_level": 3, "publish_time": "2021-10-21 17:53:20", "last_updated": "2023-03-06 13:02:14", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.isnow.db2515.2022", "i18n": { "en": { "title": "Snow course dataset in typical snow area in China (2018-2019)", "ds_format": "xlsx,jpg(tiff),shp(kmz)", "ds_source": " <pre><code>\nThis data set is the field data of independent observation.
", "ds_quality": " <pre><code>\nFirstly, the original data are obtained through field measurement, and then the data quality is controlled.\n The data quality control stage is divided into two steps: first, the data provider checks the integrity and accuracy of the data. Data integrity check mainly checks whether the number of observation points and observation fields of data meet the project requirements. On the one hand, abnormal values are judged and eliminated through numerical diagrams. On the other hand, the data storage mode and data format are unified and standardized. The second stage is for data providers to cross check the data of other groups, review the integrity and accuracy of data again, and integrate the data of different regions. Among them, the data self inspection table and data analysis diagram 1 for data quality control coexist in the data set folder.\n Finally, the observation data of each group are integrated to obtain a complete, accurate and consistent snow course data set.
", "ds_ref_way": "", "ds_abstract": " <pre><code>\nThis data set contains the snow depth, snow pressure and snow density data of 11 snow courses in the snow season from 2018 to 2019 in China's typical snow areas. Snow survey lines are mainly located in Xinjiang, Qinghai, Inner Mongolia and Northeast China.\n The data set establishes 11 folders according to the location number and observation date of snow course. Each sub folder includes an observation point distribution file in KMZ or SHP format, an observation point schematic diagram, a spreadsheet recording observation data and a scanned file of paper form during observation. There are 169 records in total in the observation records of line 2 without paper observation table scanning files and vector files of observation point distribution. The data set also contains a data self-test table for data quality inspection. See the description document for the naming rules, time range, longitude and latitude of the data set.
", "ds_time_res": "日、时、分", "ds_acq_place": "Xinjiang, Qinghai, Inner Mongolia and Northeast China", "ds_space_res": "", "ds_projection": "", "ds_process_way": " <pre><code>\nThe data set comes from the field observation data of each unit. The longitude, latitude and elevation information in the quadrat data comes from handheld GPS. The data of snow depth and snow pressure are from the gauge and snow tube respectively. The snow depth data is the average of three measurements. The snow pressure data is obtained by manually weighing the weight of a certain volume of snow installed in the snow cylinder. The density data is obtained by dividing the snow pressure and snow depth data.
", "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": [ "雪深", "典型积雪区", "snow course" ], "ds_subject_tags": [], "ds_class_tags": [], "ds_locus_tags": [ "新疆", "内蒙古", "东北地区", "青海省" ], "ds_time_tags": [ 2017, 2018, 2019 ], "ds_contributors": [ { "true_name": "李兰海", "email": "lilh@ms.xjb.ac.cn", "work_for": "中国科学院新疆生态与地理研究所", "country": "中国" }, { "true_name": "车涛", "email": "chetao@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": "李晓峰", "email": "lixiaofeng@iga.ac.cn", "work_for": "中国科学院东北地理与农业生态研究所", "country": "中国" }, { "true_name": "刘艳", "email": "liuyan@idm.cn", "work_for": "中国气象局乌鲁木齐沙漠气象研究所", "country": "中国" }, { "true_name": "肖建设", "email": "", "work_for": "青海省气象科学研究所", "country": "中国" }, { "true_name": "戴礼云", "email": "dailiyun@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": "戴礼云", "email": "dailiyun@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": "车涛", "email": "chetao@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": "积雪" }