{
    "created": "2024-12-24 10:59:01",
    "updated": "2026-05-06 07:22:05",
    "id": "c311c535-0d26-475a-87cd-ca2a8ac87328",
    "version": 11,
    "ds_topic": null,
    "title_cn": "基于风云-3D 的全球露天生物质燃烧排放清单火点监测数据集（2020-2022年）",
    "title_en": "Global Emissions Inventory from Open Biomass Burning (GEIOBB): Utilizing Fengyun-3D global fire spot monitoring data",
    "ds_abstract": "<p>&emsp;&emsp;露天生物质燃烧（OBB）对区域和全球的空气质量、气候变化和人类健康都有重大影响。它容易受到火灾类型的影响，包括森林、灌木林、草地、泥炭地和耕地的燃烧。全球高分辨率卫星在探测活动火灾方面具有优势，可以更准确地估计这些排放。本数据集利用中国风云三号3D卫星的全球火点监测数据、卫星和观测生物量数据、植被指数衍生的时空可变燃烧效率以及基于土地类型的排放因子，建立了全球高分辨率（1km × 1km）的与露天生物质燃烧排放相关的日排放清单。",
    "ds_source": "<p>&emsp;&emsp;数据来源于figshare网站（https://doi.org/10.6084/m9.figshare.24793623.v2）。",
    "ds_process_way": "<p>&emsp;&emsp;根据 Wiedinmyer 等人（2006 年）和 Shi 等人（2015 年）描述的框架，采用燃烧面积法估算了全球露天生物质燃烧排放清单（GEIOBB）。GEIOBB 包括基于 FY-3D 卫星活动火灾数据检索的燃烧面积、卫星和地面测量的可用生物量、按树木覆盖（TC）和归一化差异植被指数（NDVI）缩放的 CF 以及基于土地覆盖（LC）的排放因子的 OBB 排放。GEIOBB 通过计算上述各项的乘积得出。",
    "ds_quality": "<p>&emsp;&emsp;数据质量良好。",
    "ds_acq_start_time": "2020-01-01 00:00:00",
    "ds_acq_end_time": "2022-12-31 00:00:00",
    "ds_acq_place": "全球",
    "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": "login-access",
    "ds_total_size": 10613305636,
    "ds_files_count": 4,
    "ds_format": "HDF5",
    "ds_space_res": "1000m",
    "ds_time_res": "年",
    "ds_coordinate": "无",
    "ds_projection": "",
    "ds_thumbnail": "c311c535-0d26-475a-87cd-ca2a8ac87328.png",
    "ds_thumb_from": 2,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "a4dd5849-78f2-44c5-b0f1-3450e952b2a2",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [
        "170.15"
    ],
    "quality_level": 3,
    "publish_time": "2024-12-27 15:54:36",
    "last_updated": "2026-01-14 11:01:10",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.NCDC.FIGSHARE.DB6697.2024",
    "i18n": {
        "en": {
            "title": "Global Emissions Inventory from Open Biomass Burning (GEIOBB): Utilizing Fengyun-3D global fire spot monitoring data",
            "ds_format": "HDF5",
            "ds_source": "<p>&emsp;Data sourced from figshare website（ https://doi.org/10.6084/m9.figshare.24793623.v2 ）.",
            "ds_quality": "<p>&emsp;The data quality is good.",
            "ds_ref_way": "",
            "ds_abstract": "<p> Open biomass burning (OBB) significantly impacts regional and global air quality, climate change, and human health. It is susceptible to fire types, including forests, shrublands, grasslands, peatlands, and croplands burning. Global high-resolution satellites have advantages in detecting active fires, enabling more accurate estimation of these emissions. In this study, we develop a global high-resolution (1 km×1 km) daily emission inventory associated with OBB emissions using the Chinese Fengyun-3D satellite’s global fire spot monitoring data, satellite and observational biomass data, vegetation index-derived spatiotemporal variable combustion efficiency, and land type-based emission factors.</p>",
            "ds_time_res": "年",
            "ds_acq_place": "Global",
            "ds_space_res": "1000m",
            "ds_projection": "",
            "ds_process_way": "<p>&emsp;According to the framework described by Wiedinmyer et al. (2006) and Shi et al. (2015), the global open air biomass burning emissions inventory (GEIOBB) was estimated using the burning area method. GEIOBB includes combustion area retrieved based on FY-3D satellite activity fire data, available biomass measured by satellite and ground, CF scaled by tree cover (TC) and normalized difference vegetation index (NDVI), and OBB emissions based on land cover (LC) emission factors. GEIOBB is obtained by calculating the product of the above items.",
            "ds_ref_instruction": ""
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "license_type": "CC 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": [
        "FY-3D",
        "露天燃烧",
        "排放数据"
    ],
    "ds_subject_tags": [
        "大气科学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "全球"
    ],
    "ds_time_tags": [
        2023
    ],
    "ds_contributors": [
        {
            "true_name": "石玉胜",
            "email": "shiys@aircas.ac.cn",
            "work_for": "中国科学院 航天信息研究所 遥感科学国家重点实验室",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "石玉胜",
            "email": "shiys@aircas.ac.cn",
            "work_for": "中国科学院 航天信息研究所 遥感科学国家重点实验室",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "石玉胜",
            "email": "shiys@aircas.ac.cn",
            "work_for": "中国科学院 航天信息研究所 遥感科学国家重点实验室",
            "country": "中国"
        }
    ],
    "category": "大气本底"
}