{
    "created": "2019-01-24 01:30:24",
    "updated": "2026-06-13 15:31:47",
    "id": "9a345cd1-0e2e-4398-878c-f660c5aefa31",
    "version": 2,
    "ds_topic": "a9243521-7a33-4a8a-a235-288c1f4bc8b8",
    "title_cn": "2013-2017年河龙区间多沙粗沙国家级重点治理区林草植被覆盖度图数据集",
    "title_en": "Data set of vegetation coverage map of forest and grass in national key control area of heavy and coarse sand in Helong section from 2013 to 2017",
    "ds_abstract": "<p>河龙区间多沙粗沙国家级重点治理区土地利用图数据集包括内蒙古自治区准格尔旗、伊金霍洛旗、东胜区，陕西省神木县、宝塔区等区域2013年、2014年、2015年、2016年和2017年的林草植被覆盖度，基于空间分辨率为2米的卫星遥感影像加工获得。</p>",
    "ds_source": "<p>数据源为资源三号和高分一号卫星影像，主要由水利部信息中心提供。",
    "ds_process_way": "<p>基于遥感估算的方法，利用归一化植被指数（NDVI）采用像元二分模型法进行植被盖度估算。首先利用多光谱影像的近红外波段与红波段数据计算每个像元的NDVI，然后使用模型计算整个区域植被覆盖度，并根据划分规则对植被覆盖度进行等级划分，最后使用该区域遥感解译得到的土地利用类型数据和基于遥感估算得到的植被覆盖度数据做叠加运算，获得每个像元的植被覆盖度信息。</p>",
    "ds_quality": "<p>解译结果复查：抽取不少于总图斑的5%进行核查。\n野外验证样本数量和成果满足《水土保持遥感监测技术规范》（SL592-2012）的要求，对于核查图斑，抽取10%作为验证样本进行实地验证。</p>\n</p>",
    "ds_acq_start_time": "2013-01-01 00:00:00",
    "ds_acq_end_time": "2017-12-31 00:00:00",
    "ds_acq_place": "河龙区间多沙粗沙国家级重点治理区",
    "ds_acq_lon_east": 111.44166666666668,
    "ds_acq_lat_south": 38.20611111111111,
    "ds_acq_lon_west": 109.00888888888889,
    "ds_acq_lat_north": 40.323888888888895,
    "ds_acq_alt_low": null,
    "ds_acq_alt_high": null,
    "ds_share_type": "apply-access",
    "ds_total_size": 45780020,
    "ds_files_count": 2,
    "ds_format": "TIF",
    "ds_space_res": "25.0m",
    "ds_time_res": "年",
    "ds_coordinate": "CGCS2000",
    "ds_projection": "高斯—克吕格",
    "ds_thumbnail": "9a345cd1-0e2e-4398-878c-f660c5aefa31.jpg",
    "ds_thumb_from": 2,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "18fc6591-ef53-4202-bc01-c3961ad212d2",
    "ds_serv_man": "敏玉芳",
    "ds_serv_phone": "0931-4967596",
    "ds_serv_mail": "ncdc@lzb.ac.cn",
    "doi_value": "",
    "subject_codes": [],
    "quality_level": 3,
    "publish_time": "2021-01-04 14:43:29",
    "last_updated": "2024-03-19 15:13:38",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "11738.11.ncdc.HHSTBC.2020.163",
    "i18n": {
        "en": {
            "title": "Data set of vegetation coverage map of forest and grass in national key control area of heavy and coarse sand in Helong section from 2013 to 2017",
            "ds_format": "",
            "ds_source": "<p>The data sources are ZY-3 and GF-1 satellite images, which are mainly provided by the information center of the Ministry of water resources.",
            "ds_quality": "<p>Re examination of interpretation results: no less than 5% of the total map spots shall be selected for verification.\nThe number and results of field verification samples meet the requirements of technical specification for remote sensing monitoring of soil and water conservation (sl592-2012). For verification spots, 10% of them are selected as verification samples for field verification. </p>\n</p>",
            "ds_ref_way": "",
            "ds_abstract": "<p>The land use map data set of the national key control areas of Sandy and coarse sand in Helong region includes the forest and grass vegetation coverage of Zhungeer banner, Yijinhuoluo banner and Dongsheng District of Inner Mongolia Autonomous Region, Shenmu county and Baota District of Shaanxi Province in 2013, 2014, 2015, 2016 and 2017, which is based on the satellite remote sensing image processing with spatial resolution of 2m. </p>",
            "ds_time_res": "年",
            "ds_acq_place": "National key control area of heavy and coarse sand in Helong section",
            "ds_space_res": "25.0m",
            "ds_projection": "",
            "ds_process_way": "<p>Based on the method of remote sensing estimation, the normalized vegetation index (NDVI) was used to estimate the vegetation coverage using the pixel bisection model method. Firstly, the NDVI of each pixel is calculated by using the near-infrared band and red band data of multispectral images, and then the vegetation coverage of the whole region is calculated by using the model, and the vegetation coverage is classified according to the classification rules. Finally, the land use type data obtained from remote sensing interpretation and the vegetation coverage data estimated based on remote sensing are used for superposition operation to obtain each pixel Vegetation coverage information of each pixel. </p>",
            "ds_ref_instruction": ""
        }
    },
    "submit_center_id": "ncdc",
    "data_level": 0,
    "recommendation_value": 0,
    "license_type": "https://creativecommons.org/licenses/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,
    "belong_to_nieer": false,
    "ds_topic_tags": [
        "中高低覆盖度，林草植被覆盖度",
        "多沙粗沙",
        "裸地"
    ],
    "ds_subject_tags": [],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "内蒙古",
        "准格尔旗",
        "神木县",
        "伊金霍洛旗",
        "东胜区",
        "宝塔区",
        "陕西省"
    ],
    "ds_time_tags": [
        2013,
        2014,
        2015,
        2016,
        2017
    ],
    "ds_contributors": [
        {
            "true_name": "黄河流域水土保持生态环境监测中心",
            "email": "1283337@qq.com",
            "work_for": "黄河流域水土保持生态环境监测中心",
            "country": "中国"
        }
    ],
    "ds_meta_authors": [
        {
            "true_name": "黄河流域水土保持生态环境监测中心",
            "email": "szyjdata@163.com",
            "work_for": "黄河流域水土保持生态环境监测中心",
            "country": "中国"
        }
    ],
    "ds_managers": [
        {
            "true_name": "黄河流域水土保持生态环境监测中心",
            "email": "szyjdata@163.com",
            "work_for": "黄河流域水土保持生态环境监测中心",
            "country": "中国"
        }
    ],
    "category": "水土保持"
}