青藏高原牧区雪灾是困扰和制约高寒畜牧业生产的重要因素之一，至今尚未全面系统地开展牧区雪灾本底数据的调查和数据库的建立。针对此问题，利用科技基础资源调查专项“中国积雪特性分布及调查”项目中第一、二课题积雪特性与分布地面调查和遥感监测数据集，在青藏高原设立典型区，利用高精度积雪数据产品（积雪面积、雪水当量、融雪时间）和积雪特性地面调查数据。在考虑牧区高程分布、草地类型、草层高度、社会经济数据等综合因素的基础上，根据灾情资料，建立易损性模型，确定不同等级雪灾条件下牲畜死亡率临界值，根据临界值进行各地承灾体易损性区划，进而建立致灾因子危险性计算模型。最终在综合考虑致灾因子危险性和承载体易损性基础上制作了青藏高原牧区雪灾风险区划专题图，该成果将通过共享的数据库平台实现开放共享，将在农牧业生产、牧区雪灾等多个方面发挥重要作用。", "ds_source": "
逐日雪深资料：是科技基础资源调查专项“中国积雪特性分布及调查”项目中制作的《1980-2020雪水当量/雪深产品数据》，该数据基于混合像元雪水当量反演算法，利用星载被动微波遥感亮温数据制备了1980-2020年空间分辨率为25km的逐日雪水当量/雪深数据集。该数据集包括雪深（cm）、雪水当量（mm）、经纬度、质量标识符等。\n
灾情资料：通过查阅《中国气象灾害大典》（青海卷）、《青海省统计年鉴》、青海和西藏灾情直报系统等，统计雪灾所造成的牲畜死亡率，以及雪灾发生时间、灾害等级、灾害受损状况等，上述数据均由权威机构发布保证了数据的真实和可靠性。\n
青藏高原矢量边界数据：由中国科学院地理科学与资源研究所张镱锂团队制作，目前该边界在青藏高原研究中已经广泛应用。\n
中国省界：由中国基础地理信息中心获取中国1:400万中国基础地理数据。", "ds_process_way": "
青藏高原牧区雪灾风险区划专题图，该专题图在制作过程主要包括如下步骤：\n
（1）挑选1985-2020年青海和西藏因积雪造成牲畜死亡的案例，共选出62个区域，统计每个区域发生雪灾的次数；\n
（2）建立牲畜死亡率与海拔高度的关系模型，并计算格点上的牲畜死亡率，具体模型为\nY=0.0019X-2.6787，式中Y为出现雪灾次数，X为海拔高度（米）；\n
（3）利用区域实际发生雪灾次数，并按照反距离权重进行空间插值；\n
（4）将（2）和（3）的插值结果进行平均，对格点均值进行标准化处理，形成承载体易损性数据；\n
（5）统计了1985-2020年青藏高原地区各格点上积雪深度≥2cm 的积雪日数；\n
（6）对统计后的各格点积雪日数进行空间插值和标准化处理，形成致灾因子危险性数据；\n
（7）将标准化的致灾因子危险性数据与易损性数据进行乘积；\n
（8）将（7）的数据在ArcGIS软件中采用自然断点法进行分级，叠加基础地理数据并进行专题图整饰。", "ds_quality": "
原始数据获取主要包括：（1）逐日雪深资料；（2）灾情资料；（3）青藏高原矢量边界数据；（4）中国省界；（5）青藏高原地区气象台站2000-2020年雪深观测资料。\n
数据加工处理主要包括：（1）灾情资料和雪深观测资料进行电子化；（2）逐日雪深资料进行裁剪、空间统计和标准化处理；（3）矢量边界数据进行投影转换等。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "青藏高原牧区", "ds_acq_lon_east": 73.0, "ds_acq_lat_south": 26.0, "ds_acq_lon_west": 145.0, "ds_acq_lat_north": 40.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 15024290, "ds_files_count": 2, "ds_format": "tif.shp.jpg", "ds_space_res": null, "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "等经纬度", "ds_thumbnail": "7c51b5e3-084e-4e9f-89c2-63e9797d11d5.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "李林，李晓东，李红梅，史飞飞，曹晓云. 青海省气象科学研究所.青藏高原牧区雪灾专题图. 202105", "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.isnow.db2712.2023", "subject_codes": [], "quality_level": 3, "publish_time": "2023-02-15 16:54:54", "last_updated": "2023-02-23 16:28:26", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.isnow.db2712.2023", "i18n": { "en": { "title": "Snow disaster risk zoning data in pastoral areas of the Qinghai-Tibet Plateau from 2000 to 2020", "ds_format": "", "ds_source": "
<pre><code>\nDaily snow depth data: refers to the 1980-2020 Snow Water Equivalent/Snow Depth Product Data produced in the special project of \"Distribution and Survey of Snow Cover Characteristics in China\" of the scientific and technological basic resources survey. This data is based on the mixed pixel snow water equivalent inversion algorithm, and uses the spaceborne passive microwave remote sensing brightness temperature data to prepare the daily snow water equivalent/snow depth data set with a spatial resolution of 25 km from 1980 to 2020. The data set includes snow depth (cm), snow water equivalent (mm), longitude and latitude, mass identifier, etc.\n
Disaster information: The death rate of livestock caused by the snow disaster, as well as the occurrence time, disaster level and disaster damage status of the snow disaster, were counted by consulting the \"China Meteorological Disaster Dictionary\" (Qinghai Volume), the \"Statistical Yearbook of Qinghai Province\", the direct disaster reporting system of Qinghai and Tibet, etc. The above data were released by the authority to ensure the authenticity and reliability of the data.\n
Vector boundary data of the Qinghai-Tibet Plateau: produced by Zhang Yili team of the Institute of Geographic Sciences and Resources of the Chinese Academy of Sciences. At present, this boundary has been widely used in the research of the Qinghai-Tibet Plateau.\n
China's provincial boundaries: China's basic geographic data of 1:4 million is obtained from China's Basic Geographic Information Center.", "ds_quality": "
<pre><code>\nThe original data acquisition mainly includes: (1) daily snow depth data; (2) Disaster information; (3) Vector boundary data of Qinghai-Tibet Plateau; (4) China's provincial boundary; (5) Snow depth observation data of meteorological stations in the Qinghai-Tibet Plateau from 2000 to 2020.\n
Data processing mainly includes: (1) computerization of disaster data and snow depth observation data; (2) Tailoring, spatial statistics and standardization of daily snow depth data; (3) Projection conversion of vector boundary data, etc.", "ds_ref_way": "", "ds_abstract": "
<pre><code>\nSnow disaster in pastoral areas of the Qinghai-Tibet Plateau is one of the important factors that perplex and restrict the production of alpine animal husbandry. So far, the investigation of background data of snow disaster in pastoral areas and the establishment of database have not been carried out comprehensively and systematically. In response to this problem, the ground survey and remote sensing monitoring data sets of snow cover characteristics and distribution in the first and second topics of the special project \"Distribution and Investigation of Snow Cover Characteristics in China\" of the scientific and technological basic resources survey project are used to set up a typical area in the Qinghai-Tibet Plateau, and use high-precision snow cover data products (snow cover area, snow water equivalent, snow melting time) and ground survey data of snow cover characteristics. On the basis of considering the comprehensive factors such as elevation distribution, grassland type, grass layer height, social and economic data in the pastoral area, and according to the disaster information, the vulnerability model is established to determine the critical value of livestock mortality under different levels of snow disaster conditions, and the vulnerability zoning of disaster-bearing bodies is carried out according to the critical value, and then the calculation model of hazard factors is established. Finally, a thematic map of snow disaster risk zoning in pastoral areas of the Qinghai-Tibet Plateau was prepared on the basis of comprehensive consideration of hazard factors and vulnerability of the bearing body. The results will be open and shared through the shared database platform, and will play an important role in agricultural and animal husbandry production, snow disaster in pastoral areas and other aspects.
", "ds_time_res": "", "ds_acq_place": "Pastoral area of Qinghai-Tibet Plateau", "ds_space_res": "", "ds_projection": "", "ds_process_way": " <pre><code>\nThe thematic map of snow disaster risk zoning in pastoral areas of the Qinghai-Tibet Plateau mainly includes the following steps in the production process:\n
(1) The cases of livestock deaths caused by snow cover in Qinghai and Tibet from 1985 to 2020 were selected. A total of 62 regions were selected to count the number of snow disasters in each region;\n
(2) Establish the relationship model between livestock mortality and altitude, and calculate the livestock mortality on the grid. The specific model is\nY=0.0019X-2.6787, where Y is the number of snow disasters and X is the altitude (m);\n
(3) Use the actual number of snow disasters in the region, and carry out spatial interpolation according to the inverse distance weight;\n
(4) Average the interpolation results of (2) and (3), and standardize the grid mean value to form the bearing body vulnerability data;\n
(5) The number of snow days with snow depth ≥ 2 cm at each grid point in the Qinghai-Tibet Plateau from 1985 to 2020 was counted;\n
(6) Perform spatial interpolation and standardization on the number of snow days at each grid point after statistics to form hazard data of disaster factors;\n
(7) Multiply the standardized hazard data of hazard factors and vulnerability data;\n
(8) The data of (7) is graded by natural breakpoint method in ArcGIS software, and the basic geographic data is superimposed and the thematic map is trimmed.", "ds_ref_instruction": "Li Lin, Li Xiaodong, Li Hongmei, Shi Feifei, Cao Xiaoyun Qinghai Institute of Meteorological Sciences. Special map of snow disaster in pastoral areas of the Qinghai-Tibet Plateau two hundred and two thousand one hundred and five" } }, "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": [ "积雪面积", "雪水当量", "融雪时间" ], "ds_subject_tags": [], "ds_class_tags": [], "ds_locus_tags": [ "青藏高原" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "ds_contributors": [ { "true_name": "李林", "email": "1652330742@qq.com", "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": "李林", "email": "1652330742@qq.com", "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": "李林", "email": "1652330742@qq.com", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "积雪" }