{
    "created": "2024-09-24 12:08:46",
    "updated": "2026-08-08 00:59:44",
    "id": "7137ae47-2baf-4ff7-b14b-c69e28b817b1",
    "version": 7,
    "ds_topic": null,
    "title_cn": "2000、2010年中亚地区MODIS_250米地表含水量MSWCI数据集",
    "title_en": "",
    "ds_abstract": "<p>本数据集是2000年和2010年乌兹别克斯坦、吉尔吉斯斯坦、土库曼斯坦、塔吉克斯坦和哈萨克斯坦5个国家范围的地表含水量MSWCI数据。数据集包含2种：分别是①从2000年和2010年的第97天开始（含第97天的），每16天一个中亚五国范围的地表含水量img格式文件，共24个栅格文件；② 2个年平均地表含水量数据2000MSWCI_Clip.img和2010MSWCI_Clip.img格式文件。\n本数据集是对原始数据经过降尺度处理生成的，空间分辨率为250米，采用Albers投影坐标系。\n数据反映了中亚地区地表含水量时间变化与空间分布特征, 反映植被水分的亏缺程度，可利用此数据进行干旱监测。\n</p>",
    "ds_source": "<p>数据源来自MOD09A1产品。\n1.  2000年第97、113、129、145、161、177、193、209、225、241、257天的MOD09A1数据；\n2.  2010年第97、113、129、145、161、177、193、209、225、241、257天的MOD09A1数据；\n</p>",
    "ds_process_way": "<p>该数据是利用MODIS数据的第6、第7波段反射率值，得到SWCI，加入L参数修正SWCI，得到修正后的地表含水量指数MSWCI。利用修正后的地表含水量指数MSWCI分别反演出2000年和2010年4月1日至9月31日每8天中亚地区地表含水量，进而计算出这两个时段该地区的平均含水量。</p>",
    "ds_quality": "<p>获取的数据需要整理和计算处理才能使用，对研究区范围土要的气象观测数据、MODIS数据进行整理和计算处理,包括空白数据、缺测数据、质量缺陷等,对有问题的数据进行分析,根据情况进行处理，得到精确度高的数据。</p>",
    "ds_acq_start_time": "2000-01-01 00:00:00",
    "ds_acq_end_time": "2010-01-01 00:00:00",
    "ds_acq_place": "哈萨克斯坦；吉尔吉斯坦；塔吉克斯坦；乌兹别克斯坦；土库曼斯坦",
    "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": 322666026,
    "ds_files_count": 1,
    "ds_format": "栅格数据",
    "ds_space_res": "250",
    "ds_time_res": "年",
    "ds_coordinate": "WGS84",
    "ds_projection": "Albers",
    "ds_thumbnail": "7137ae47-2baf-4ff7-b14b-c69e28b817b1.png",
    "ds_thumb_from": 0,
    "ds_ref_way": "",
    "paper_ref_way": "",
    "ds_ref_instruction": "",
    "ds_from_station": null,
    "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6",
    "doi_value": "",
    "subject_codes": [
        "170.45"
    ],
    "quality_level": 1,
    "publish_time": "2025-03-17 19:49:06",
    "first_publish_time": null,
    "last_updated": "2025-04-22 19:41:15",
    "protected": false,
    "protected_to": null,
    "lang": "zh",
    "cstr": "33110.11.ariddc.00122",
    "license": null,
    "extra": null,
    "files_shape": [
        {
            "name": "Data.rar",
            "size": 322666026,
            "is_dir": false
        }
    ],
    "features": null,
    "data_level": 0,
    "i18n": {
        "en": {
            "title": "2000 and 2010 MODIS_250-meter surface water content MSWCI data set in Central Asia",
            "ds_abstract": "<p>This dataset is the MSWCI data of surface water content in five countries: Uzbekistan, Kyrgyzstan, Turkmenistan, Tajikistan and Kazakhstan in 2000 and 2010. The data set includes two types: ① Starting from the 97th day of 2000 and 2010 (inclusive), one surface water content img format file across the five Central Asian countries every 16 days, with a total of 24 grid files;② Two annual average surface water content data files in 2000MSWCI_Clip.img and 2010MSWCI_Clip.img format files.\nThis dataset is generated by downscaling the raw data, with a spatial resolution of 250 meters, and adopts the Albers projection coordinate system.\nThe data reflects the temporal changes and spatial distribution characteristics of surface water content in Central Asia, as well as the degree of vegetation water deficit. This data can be used for drought monitoring.\n</p>",
            "ds_source": "<p>The data source comes from the MOD09A1 product.\n1.  MOD09A1 data on Days 97, 113, 129, 145, 161, 177, 193, 209, 225, 241, and 257 in 2000;\n2.  MOD09A1 data on Days 97, 113, 129, 145, 161, 177, 193, 209, 225, 241, and 257 in 2010;\n</p>",
            "ds_process_way": "<p>The data uses the reflectance values of the 6th and 7th bands of MODIS data to obtain SWCI, and adds the L parameter to correct the SWCI to obtain the corrected surface water content index MSWCI. The revised surface water content index MSWCI was used to invert the surface water content of Central Asia every eight days from April 1 to September 31, 2000 and 2010, respectively, and then calculate the average water content of the region during these two periods. </p>",
            "ds_quality": "<p>The obtained data needs to be sorted out and calculated before it can be used. The meteorological observation data and MODIS data in the study area are sorted out and calculated, including blank data, missing data, quality defects, etc. The problematic data are analyzed and processed according to the situation to obtain high-precision data. </p>",
            "ds_acq_place": "Kazakhstan; Kyrgyzstan; Tajikistan; Uzbekistan; Turkmenistan",
            "ds_format": "raster data",
            "ds_projection": "Albers",
            "ds_space_res": "250",
            "ds_time_res": "years"
        }
    },
    "license_type": null,
    "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": [
        "地表含水量",
        "生态",
        "MSWCI"
    ],
    "ds_subject_tags": [
        "地理学"
    ],
    "ds_class_tags": [],
    "ds_locus_tags": [
        "中亚"
    ],
    "ds_time_tags": [
        2000,
        2010
    ],
    "ds_contributors": [
        "陈秋晓",
        "陈曦"
    ],
    "ds_meta_authors": [
        "陈秋晓"
    ],
    "ds_managers": [
        "李锦"
    ],
    "category": "中分辨率成像光谱仪"
}