本数据集包含我国典型积雪区2017-2020年3个积雪季16个25km样方的积雪深度、雪压和积雪密度等数据。积雪样方主要采集自我国新疆和东北地区。数据集共包含16个文件夹，16个样方数据表，共670条观测记录。
\n其中，每个样方数据存放于1个文件夹，文件夹内还包含记录表格的扫描档、样方点分布示意图及样方点矢量图（shp或kmz格式）。
\n数据集命名规则、时间范围及站点经纬度见说明文档。
", "ds_source": "本数据集为自主观测的野外数据。
", "ds_process_way": "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": "数据质量控制阶段分两步：
\n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样方内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，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最后整合各样方数据，得到完整、准确、格式一致的25km样方数据集。
", "ds_acq_start_time": "2017-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "新疆、东北地区", "ds_acq_lon_east": 125.61944444444444, "ds_acq_lat_south": 34.358333333333334, "ds_acq_lon_west": 81.91666666666667, "ds_acq_lat_north": 47.63805555555555, "ds_acq_alt_low": 115.0, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 1419855429, "ds_files_count": 475, "ds_format": "xlsx，jpg", "ds_space_res": null, "ds_time_res": "日、时、分", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "7557cb28-01ff-4b80-ac81-0dc2d09f14ae.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.db1663.2022", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2021-10-21 17:53:01", "last_updated": "2023-03-06 12:59:37", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.isnow.db1663.2022", "i18n": { "en": { "title": "snow survey dataset from measurement routes of 25km samples in the typical regions of China during 2017-2020", "ds_format": "xlsx，jpg", "ds_source": " <pre><code>\nThis data set is the field data of independent observation.
", "ds_quality": " <pre><code> &emsp;&emsp;The data quality control stage is divided into two steps:\nFirstly, 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 in the data sample 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 of data quality control coexist in the data set folder.
\nFinally, integrate the quadrat data to obtain a complete, accurate and consistent 25km quadrat data set.
", "ds_ref_way": "", "ds_abstract": " <pre><code>\nThis data set contains the data of snow depth, snow pressure and snow density of 16 25km quadrats in three snow seasons from 2017 to 2020 in China's typical snow area. Snow quadrats are mainly collected from Xinjiang and Northeast China. The data set contains 16 folders, 16 quadrat data tables and 670 observation records in total.\n Among them, each quadrat data is stored in a folder, which also contains the scanning file of the recording form, the schematic diagram of quadrat point distribution and the quadrat point vector diagram (SHP or KMZ format). \n See the description document for the naming rules, time range and longitude and latitude of the data set.
", "ds_time_res": "日、时、分", "ds_acq_place": "Xinjiang 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": [ "积雪样方", "25km", "雪深", "积雪密度", "雪压" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "新疆", "东北地区" ], "ds_time_tags": [ 2017, 2018, 2019, 2020 ], "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" } ], "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" }