{
    "created": "2025-03-25 09:27:57",
    "updated": "2026-05-13 21:24:24",
    "id": "070409c9-cd50-43de-8232-2353b281c251",
    "version": 4,
    "ds_topic": null,
    "title_cn": "中国区域MuSyQ高分30米空间分辨率10天合成时空连续叶片叶绿素含量产品（2021-2022年）",
    "title_en": "A dataset of 30 m/10-day spatio-temporal continuous leaf chlorophyll content of MuSyQ GF-series (2021-2022, China)",
    "ds_abstract": "<p>&emsp;&emsp;叶片叶绿素含量（leaf chlorophyll content, LCC）反映了植被获取光合作用所需太阳辐射信息，是生态系统生理生态监测的重要参数，高精度、时空连续的LCC产品是全球及区域尺度碳循环精准模拟的基础。国际现有的全球LCC产品的空间分辨率为百米级，在空间分辨率上难以满足日益精细的检测需求；现有的MuSyQ LCC（v01）产品空间分辨率可达30m，但其产品值受云雨等因素影响，存在时空不连续问题，造成其在实际运用中高空间分辨率优势难以充分发挥。本文利用哨兵二号多光谱成像仪（Sentinel-2 MSI）基于叶绿素敏感指数（chlorophyll sensitive index, CSI）和时间序列谐波分析（Harmonic Analysis of Time Series，HANTS）法生产了MuSyQ高分系列中国地区2021-2022年30 m/10天分辨率的标准化LCC时空连续产品。本产品可有效弥补MuSyQ LCC（v01）产品的时空不连续问题，将在植被动态变化分析、农业生产管理等领域发挥更重要的作用。</p>",
    "ds_source": "<p>&emsp;&emsp;本文使用的地表反射率产品是Sentinel-2 MSI反射率二级产品（Level-2A，L2A）。</p>",
    "ds_process_way": "<p>&emsp;&emsp;本文利用哨兵二号多光谱成像仪（Sentinel-2 MSI）基于叶绿素敏感指数（chlorophyll sensitive index, CSI）和时间序列谐波分析（Harmonic Analysis of Time Series，HANTS）法生产了MuSyQ高分系列中国地区2021-2022年30 m/10天分辨率的标准化LCC时空连续产品。</p>",
    "ds_quality": "<p>&emsp;&emsp;数据质量良好。</p>",
    "ds_acq_start_time": "2021-01-01 00:00:00",
    "ds_acq_end_time": "2022-12-31 00:00:00",
    "ds_acq_place": "中国区域",
    "ds_acq_lon_east": null,
    "ds_acq_lat_south": null,
    "ds_acq_lon_west": null,
    "ds_acq_lat_north": null,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "open-access",
    "ds_total_size": 2762455698432,
    "ds_files_count": 58128,
    "ds_format": "",
    "ds_space_res": "30",
    "ds_time_res": "10天",
    "ds_coordinate": "无",
    "ds_projection": "",
    "ds_thumbnail": "070409c9-cd50-43de-8232-2353b281c251.png",
    "ds_thumb_from": 0,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "用户在使用数据时请在正文中明确声明数据的来源，并在参考文献部分引用本元数据提供的引用方式。",
    "ds_from_station": null,
    "organization_id": "d2c052ce-d283-4a48-8962-6a3dbcb03b8e",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [
        "170.45"
    ],
    "quality_level": 3,
    "publish_time": "2025-03-28 19:01:18",
    "last_updated": "2025-12-26 17:24:57",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "https://cstr.cn/31253.11.sciencedb.16673",
    "i18n": {
        "en": {
            "title": "A dataset of 30 m/10-day spatio-temporal continuous leaf chlorophyll content of MuSyQ GF-series (2021-2022, China)",
            "ds_format": "",
            "ds_source": "",
            "ds_quality": "",
            "ds_ref_way": "",
            "ds_abstract": "",
            "ds_time_res": "10天",
            "ds_acq_place": "China Region",
            "ds_space_res": "30",
            "ds_projection": "",
            "ds_process_way": "",
            "ds_ref_instruction": "When using data, users should clearly declare the source of the data in the main text and cite the citation method provided by this metadata in the reference section."
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "license_type": "https://creativecommons.org/licenses/by/4.0/",
    "doi_reg_from": "reg_outside",
    "cstr_reg_from": "reg_outside",
    "doi_not_reg_reason": null,
    "cstr_not_reg_reason": null,
    "is_paper_in_submitting": false,
    "ds_topic_tags": [
        "叶绿素含量（Chlleaf）产品",
        "高分辨率",
        "中国地区",
        "时空连续"
    ],
    "ds_subject_tags": [
        "地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "中国区域"
    ],
    "ds_time_tags": [
        2021,
        2022
    ],
    "ds_contributors": [
        {
            "true_name": "张虎",
            "email": "zhanghu@aircas.ac.cn",
            "work_for": "中国科学院空天信息创新研究院",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "张虎",
            "email": "zhanghu@aircas.ac.cn",
            "work_for": "中国科学院空天信息创新研究院",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "张虎",
            "email": "zhanghu@aircas.ac.cn",
            "work_for": "中国科学院空天信息创新研究院",
            "country": "中国"
        }
    ],
    "category": "生态"
}