{
    "created": "2019-10-10 16:37:46",
    "updated": "2026-05-04 20:58:32",
    "id": "8883a561-55b9-4b6d-a811-cfcb80d66898",
    "version": 3,
    "ds_topic": null,
    "title_cn": "中国长序列地表冻融数据集——决策树算法（1987-2009）",
    "title_en": "A long series surface freeze-thaw dataset of China - Decision tree algorithm (1987-2009)",
    "ds_abstract": "<p>中国长序列地表冻融数据集——决策树算法（1987-2009）是利用被动微波遥感 SSM/I亮度温度资料通过决策树分类提取得到。</p>\n\n<p>该数据集采用EASE-Grid投影方式（等积割圆柱投影，标准纬线为±30°），空间分辨率25.067525km，提供逐日的中国大陆主体部分的地表冻融状态分类结果。数据集按年份存放，共由23个文件夹组成，从1987到2009。每个文件夹里包含当年的逐日地表冻融分类结果，为ASCII码文件，命名规则为：SSMI-frozenYYYY<strong><em>.txt，其中YYYY代表年，</em></strong>代表儒略日（001~365/366）。冻融分类结果txt文件可直接用文本程序打开察看，还可用ArcView + Spatial Analyst扩展模块或者Arcinfo的Asciigrid命令打开。</p>\n\n<p>提取地表冻融的原始数据来源于由美国国家雪冰数据中心（NSIDC）处理的1987 年以来的逐日被动微波数据，这一数据集采用EASE-Grid（等面积可扩充地球网格）作为标准格式。</p>\n\n<p>中国地表冻融长时间序列数据集——决策树算法（1987-2009）属性由该数据集的时空分辨率、投影信息、数据格式组成。</p>\n\n<p>时空分辨率：时间分辨率为逐日，空间分辨率为25.067525km，经度范围为60°～140°E，纬度为15°～55°N。</p>\n\n<p>投影信息：全球等积圆柱EASE-Grid投影，关于EASE-Grid投影的详细信息见数据准备中关于这种投影的说明。</p>\n\n<p>数据格式：数据集由1987到2009共23个文件夹组成，每个文件夹里包括当年的逐日地表冻融分类结果，按日存储为txt文件。文件命名规则：例如SMI-frozen1994001.txt代表1994年第1天的地表冻融分类结果。该数据集的ASCII码文件是由头文件和主体内容构成。头文件包括行数、列数、x-轴左下点坐标、y-轴左下点坐标、栅格大小、无数据区标值等6行描述信息组成；主体内容为根据行数列数组成的二维数组，以列为优先进行排列，数值为整数型，从1到4，1代表冻结，2代表融化，3代表沙漠，4代表降水。因为该数据集中的所有ASCII码文件所描述的空间为我国全国范围，所以这些文件的头文件是不变的，现将头文件摘录如下（其中xllcenter， yllcenter和cellsize单位为m）：</p>\n\n<p>ncols 308</p>\n\n<p>nrows 166</p>\n\n<p>xllcorner 5778060</p>\n\n<p>yllcorner 1880060</p>\n\n<p>cellsize 25067.525</p>\n\n<p>nodata_value 0</p>\n\n<p>该数据集中的所有ASCII码文件可以直接用文本程序（如记事本）打开。除了头文件，主体内容为数值表征地表冻融的状态：1代表冻结，2代表融化，3代表沙漠，4代表降水。如果要用图示来显示的话，我们推荐用ArcView + 3D 或 Spatial Analyst 扩展模块来读取，在读取过程中会生成grid格式的文件，所显示的grid文件就是该ASCII码文件的图形表达。读取方法：</p>\n\n<p>[1] 在ArcView软件中添加3D或Spatial Analyst扩展模块，然后新建一个View；</p>\n\n<p>[2] 将View激活，点击File菜单，选择Import Data Source选项，弹出Import Data Source选择框，在此框中的Select import file type:中选择ASCII Raster，自动弹出选择源ASCII文件的对话框，点击寻找该数据集中的任一个ASCII文件，，然后按OK键；</p>\n\n<p>[3] 在Output Grid对话框中键入的Grid文件名字（建议使用有意义的文件名，以便以后自己查看）和点击存放此Grid文件的路径，再次按Ok键，然后按Yes（要选择整型数据），Yes（把生成grid文件调入到当前的view中）。生成的文件可以按照Grid文件标准进行属性编辑。这样就完成了显示将ASCII文件显示成Grid文件的过程。</p>\n\n<p>[4] 批处理时，可以使用ARCINFO的ASCIIGRID命令，编写成AML文件，再用Run命令在Grid模块中完成：</p>\n\n<p>Usage: ASCIIGRID <in_ascii_file> <out_grid> {INT | FLOAT} </p>",
    "ds_source": "<p>提取地表冻融的原始数据来源于由美国国家雪冰数据中心（NSIDC）处理的1987 年以来的逐日被动微波数据，这一数据集采用EASE-Grid（等面积可扩充地球网格）作为标准格式。</p>",
    "ds_process_way": "<p>决策树算法</p>",
    "ds_quality": "<p>数据集通过严格的人工审核控制质量</p>",
    "ds_acq_start_time": "1987-01-01 00:00:00",
    "ds_acq_end_time": "2009-12-31 00:00:00",
    "ds_acq_place": "中国",
    "ds_acq_lon_east": 135.5,
    "ds_acq_lat_south": 17.766666666666666,
    "ds_acq_lon_west": 73.19972222222222,
    "ds_acq_lat_north": 53.86666666666667,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "login-access",
    "ds_total_size": 18598832,
    "ds_files_count": 4,
    "ds_format": "ASCII Grid",
    "ds_space_res": "25067.525m",
    "ds_time_res": "逐日",
    "ds_coordinate": "WGS84",
    "ds_projection": "全球等积圆柱EASE-Grid投影",
    "ds_thumbnail": "8883a561-55b9-4b6d-a811-cfcb80d66898.png",
    "ds_thumb_from": 0,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "None",
    "ds_from_station": null,
    "organization_id": "9c4867b1-5cb1-4de0-abeb-df42547bf41e",
    "ds_serv_man": "李红星",
    "ds_serv_phone": "0931-4967287",
    "ds_serv_mail": "westdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [
        "170.4510"
    ],
    "quality_level": 3,
    "publish_time": "2020-04-08 11:17:59",
    "last_updated": "2023-08-23 16:46:27",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.Westdc.2020.636",
    "i18n": {
        "en": {
            "title": "A long series surface freeze-thaw dataset of China - Decision tree algorithm (1987-2009)",
            "ds_format": "ASCII Grid",
            "ds_source": "<p>The original data for extracting surface freeze-thaw was derived from day-by-day passive microwave data since 1987 processed by the US National Snow and Ice Data Center (NSIDC) using the EASE-Grid (Equivalent Area Expandable Earth Grid) as the standard format. </p>",
            "ds_quality": "<p>Data set quality control through strict manual audit</p>",
            "ds_ref_way": "",
            "ds_abstract": "<p>The Long-Series Surface Freeze-Thaw Dataset of China - Decision Tree Algorithm (1987-2009) was extracted by decision tree classification using passive microwave remote sensing SSM/I brightness temperature data.</p>\n<p>The dataset uses the EASE-Grid projection ( equal product cut cylindrical projection with ±30° standard latitude) with a spatial resolution of 25.067525km to provide a day-by-day classification of the surface freezing and thawing state of the main part of mainland China.The dataset is stored by year and consists of 23 folders in total, from 1987 to 2009.Each folder contains the day-by-day surface freeze-thaw classification results for the year as ASCII files with the naming convention:SSMI-frozenYYYY<strong><em>.txt, where YYYY stands for year and </em></strong> stands for Julian day (001~365/366).The txt file of the freeze-thaw classification results can be opened directly by the text program, as well as by the ArcView + Spatial Analyst extension or the Asciigrid command of Arcinfo.</p>\n<p>The original data used to extract the surface freeze-thaw was derived from daily passive microwave data processed by the US National Snow and Ice Data Center (NSIDC) since 1987, using the EASE-Grid (Equivalent Area Expandable Earth Grid) as the standard format.</p>\n<p>The attributes of long series surface freeze-thaw dataset of China - Decision tree algorithm (1987-2009) consist of the spatial and temporal resolution, projection information, and data format of this dataset.</p>\n<p>Temporal and spatial resolution: the temporal resolution is day-by-day, the spatial resolution is 25.067525km, the longitude range is 60° to 140°E and the latitude is 15° to 55°N.</p>\n<p>Projection information: global equiprobable cylindrical EASE-Grid projection. Detailed information on the EASE-Grid projection can be found in the description of this projection in the Data Preparation. </p>\n<p>Data format: The dataset consists of 23 folders from 1987 to 2009, each folder contains the day-by-day surface freeze-thaw classification results for that year, stored as txt files by day. The file naming rules: e.g. SMI-frozen1994001.txt represents the surface freeze-thaw classification results for day 1 of 1994. The ASCII file of this dataset is composed of a header file and the main content. The header file consists of six lines of descriptive information including rows, columns, coordinates of the lower left point of the x-axis, coordinates of the lower left point of the y-axis, raster size, and no data area marker values; the main content is a two-dimensional array based on the number of rows and columns, arranged in column order, with integer values from 1 to 4, with 1 representing freezing, 2 representing thawing, 3 representing desert, and 4 representing precipitation. Because all the ASCII files in this dataset describe the space for the whole of China, the header files for these files are unchanged and are extracted below (where xllcenter, yllcenter and cellsize are in m):</p>\n<p>ncols 308</p>\n<p>nrows 166</p>\n<p>xllcorner 5778060</p>\n<p>yllcorner 1880060</p>\n<p>cellsize 25067.525</p>\n<p>nodata_value 0</p>\n<p>All ASCII files in this dataset can be opened directly with a text program (e.g. Notepad). Apart from the header file, the main content is a numerical representation of the state of freezing and thawing of ground: 1 for freezing, 2 for melting, 3 for desert and 4 for precipitation. To display this graphically, we recommend using ArcView + 3D or the Spatial Analyst extension to read it, which generates a grid format file during the reading process. Reading method: </p>\n<p>[1] Add the 3D or Spatial Analyst extension to the ArcView software and create a new View; </p>\n<p>[2] Activate the View, click on the File menu, select the Import Data Source option, the Import Data Source selection box will pop up, select ASCII Raster in the Select import file type: box, a dialog box to select the source ASCII file will pop up automatically, click on Find Click on Find any ASCII file in the dataset, and then press OK;</p>\n<p>[3] In the Output Grid dialog box type in the name of the Grid file (it is recommended to use a meaningful file name so that you can view it yourself later) and click on the path where this Grid file is stored, press Ok again and then press Yes (to select integer data) and Yes (to bring the generated grid file into the current view). The resulting file can be edited for properties according to the Grid file standard. This completes the process of displaying the ASCII file into a Grid file. </p>\n<p>[4] For batch processing, you can use ARCINFO's ASCIIGRID command, write it as an AML file, and then use the Run command to complete it in the Grid module: </p>\n<p>.</p>\n<p>Usage: ASCIIGRID <in_ascii_file> <out_grid> {INT | FLOAT} </out_grid></in_ascii_file></p>",
            "ds_time_res": "逐日",
            "ds_acq_place": "China",
            "ds_space_res": "25067.525m",
            "ds_projection": "",
            "ds_process_way": "<p>Decision tree algorithm</p>",
            "ds_ref_instruction": "In order to respect intellectual property rights, protect the rights and interests of data authors, expand the services of data centers, and evaluate the application potential of data, data users are invited to use the data\r\nStudents' research results (including published papers, treatises, data products and unpublished research reports, data products, etc.) shall be clearly indicated with data\r\nSource and data author. For data reprinted (secondary or multiple releases), the author must also indicate the source of the original data. The results published in Chinese refer to the following specifications:\r\nThe data comes from the \"Data Center for environmental and Ecological Sciences in Western China\" (http://westdc.westgis.ac.cn) published by the National Natural Science Foundation of China\r\nThe data set is provided by environmental and Ecological Science Data Center for West\r\nChina,National Natural Science Foundation of China (http://westdc.westgis.ac.cn)"
        }
    },
    "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": [
        "决策树算法",
        "冻融"
    ],
    "ds_subject_tags": [
        "自然地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "中国"
    ],
    "ds_time_tags": [
        1987,
        1988,
        1989,
        1990,
        1991,
        1992,
        1993,
        1994,
        1995,
        1996,
        1997,
        1998,
        1999,
        2000,
        2001,
        2002,
        2003,
        2004,
        2005,
        2006,
        2007,
        2008,
        2009
    ],
    "ds_contributors": [
        {
            "true_name": "晋锐",
            "email": "jinrui@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": "李新",
            "email": "lixin@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": "晋锐",
            "email": "jinrui@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": "李新",
            "email": "lixin@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": "晋锐",
            "email": "jinrui@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": "遥感及产品"
}