{
    "created": "2019-10-08 17:25:28",
    "updated": "2026-04-19 17:00:15",
    "id": "e430aca1-2a98-4d93-99d8-dabd84883afe",
    "version": 6,
    "ds_topic": null,
    "title_cn": "黑河流域1公里土地覆盖格网数据集",
    "title_en": "MICLCover land cover map of the Heihe river basin",
    "ds_abstract": "<p>黑河流域1公里土地覆盖图是冉有华等（2009；2011）发展的融合了多源本地信息的中国1公里土地覆盖图（MICLCover）的子集。MICLCover土地覆盖图采用IGBP土地覆盖分类系统，基于证据理论，融合了2000年中国1：10万土地利用数据、中国植被图集（1：100万）的植被型、中国1：10万冰川分布图、中国1：100万沼泽湿地图和MODIS 2001年土地覆盖产品（MOD12Q1）。MICLCover的验证结果表明，其与中国土地利用图在7类水平上的总体一致性达到88.84%，其中，耕地、城市、湿地和水体类型的一致性达到95%以上；通过与MODIS2001年土地覆盖数据产品和IGBPDISCover土地覆盖图在三个典型地区的视觉比较，MICLCover在保持了中国土地利用图的总体精度，增加了中国植被图叶属性和叶型信息的同时，所反映的局部土地覆盖细节更加详细。采用国家森林资源调查数据，在甘肃省、云南省、浙江省、黑龙江和吉林省的验证结果表明，MICLCover的森林类型的精度相对于MODIS土地覆盖产品有大幅度的提高；采用甘肃省祁连山国家自然保护区管理局的一类森林资源调查数据对MICLCover的森林类型进行验证，结果表明，MICLCover的森林类型在该地区的精度为82.94%。</p>\n\n<p>总之，MICLCover土地覆盖图在保持了中国土地利用数据的总体精度条件下，补充了中国植被图中对植被类型及植被季相的信息，更新的中国湿地图、中国冰川图最新信息，使得中国土地覆盖数据的精度得到大大提高，分类系统更加通用，该数据可为陆面过程模型提供更高精度的土地覆盖信息。</p>",
    "ds_source": "<p>2000年中国1：10万土地利用数据、中国植被图集（1：100万）的植被型、中国1：10万冰川分布图、中国1：100万沼泽湿地图和MODIS 2001年土地覆盖产品（MOD12Q1）</p>",
    "ds_process_way": "<p>IGBP土地覆盖分类系统</p>",
    "ds_quality": "<p>数据质量良好</p>",
    "ds_acq_start_time": "2000-01-01 00:00:00",
    "ds_acq_end_time": "2000-12-31 00:00:00",
    "ds_acq_place": "黑河流域",
    "ds_acq_lon_east": 104.19972222222222,
    "ds_acq_lat_south": 37.7,
    "ds_acq_lon_west": 96.0,
    "ds_acq_lat_north": 43.25,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "open-access",
    "ds_total_size": 846243,
    "ds_files_count": 3,
    "ds_format": "栅格",
    "ds_space_res": "1000.0m",
    "ds_time_res": "",
    "ds_coordinate": "WGS84",
    "ds_projection": "+proj=longlat +datum=WGS84 +no_defs ",
    "ds_thumbnail": "e430aca1-2a98-4d93-99d8-dabd84883afe.png",
    "ds_thumb_from": 0,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "9c4867b1-5cb1-4de0-abeb-df42547bf41e",
    "ds_serv_man": "李红星",
    "ds_serv_phone": "0931-4967592",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [
        "170.4510"
    ],
    "quality_level": 3,
    "publish_time": "2021-01-11 11:40:51",
    "last_updated": "2026-01-22 17:30:27",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.Westdc.2020.446",
    "i18n": {
        "en": {
            "title": "MICLCover land cover map of the Heihe river basin",
            "ds_format": "Raster",
            "ds_source": "<p>1:100000 land use data of China in 2000, vegetation types of China Vegetation Atlas (1:1000000), glacier distribution map of China in 1:100000, swamp wet map of China in 1:1000000 and MODIS land cover product in 2001 (mod12q1)</p>",
            "ds_quality": "<p>Good data quality</p>",
            "ds_ref_way": "",
            "ds_abstract": "<p>One kilometer land cover map of Heihe River Basin is a subset of China's one kilometer land cover map (miclcover) developed by ran Youhua et al. (2009; 2011), which integrates multi-source local information. Miclcover land cover map adopts IGBP land cover classification system, based on evidence theory, integrates 1:100000 land use data of China in 2000, vegetation types of China Vegetation Atlas (1:1 million), 1:100000 glacier distribution map of China, 1:1 million marsh wet map of China and MODIS land cover product (mod12q1) in 2001. The verification results of miclcover show that the overall consistency between miclcover and China's land use map is 88.84% at seven levels, among which the consistency of cultivated land, city, wetland and water body types is more than 95%. By comparing with modis2001 land cover data products and igbpcover land cover map in three typical areas, miclcover maintains the overall consistency of China's land use map The volume precision increases the leaf attributes and leaf shape information of Chinese vegetation map, and reflects more detailed local land cover details. Using the national forest resources survey data in Gansu Province, Yunnan Province, Zhejiang Province, Heilongjiang Province and Jilin Province, the results show that the accuracy of forest types of miclcover is greatly improved compared with MODIS land cover products; using the class I forest resources survey data of Qilian Mountain National Nature Reserve Administration of Gansu Province, the forest types of miclcover are verified, and the results are as follows The results show that the accuracy of forest type of miclcover in this area is 82.94%.\n<p>In a word, while maintaining the overall accuracy of China's land use data, miclcover land cover map supplements the information of vegetation types and vegetation seasons in China's vegetation map, and updates the latest information of China's wet map and China's Glacier map, which greatly improves the accuracy of China's land cover data and makes the classification system more universal. The data can provide reference for land surface process model For more accurate land cover information. </p></p>",
            "ds_time_res": "",
            "ds_acq_place": "Heihe River Basin",
            "ds_space_res": "1000.0m",
            "ds_projection": "+proj=longlat +datum=WGS84 +no_defs ",
            "ds_process_way": "<p>IGBP land cover classification system</p>",
            "ds_ref_instruction": ""
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "license_type": "CC BY 4.0",
    "ds_topic_tags": [
        "土地利用",
        "IGBP土地覆盖分类系统",
        "土地覆盖",
        "植被"
    ],
    "ds_subject_tags": [
        "自然地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "黑河流域"
    ],
    "ds_time_tags": [
        2000
    ],
    "ds_contributors": [
        {
            "true_name": "冉有华 ",
            "email": "ranyh@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": "冉有华 ",
            "email": "ranyh@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": "冉有华 ",
            "email": "ranyh@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": "生态"
}