{ "created": "2023-12-25 09:48:17", "updated": "2026-06-18 23:02:16", "id": "1546f7cb-af61-4af2-b6c4-443d3f0fd78a", "version": 4, "ds_topic": null, "title_cn": "甘肃省MOD13A2归一化植被指数（NDVI）数据集（2018-2022年）", "title_en": "Gansu Province MOD13A2 Normalized Vegetation Index (NDVI) Dataset (2018-2022)", "ds_abstract": "

  植被指数主要反映植被在可见光、近红外波段反射与土壤背景之间差异的指标，各个植被指数在一定条件下能用来定量说明植被的生长状况。目前，归一化植被指数(NDVI)是检测植被生长状态、植被覆盖度和消除部分辐射误差相关方面的重要数据源。\n

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  NDVI能反映出植物冠层的背景影响，如土壤、潮湿地面、雪、枯叶、粗糙度等，且与植被覆盖有关。是反映农作物长势和营养信息的重要参数之一。根据该参数,可以知道不同季节的农作物对氮的需求量, 对合理施用氮肥具有重要的指导作用。\n

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  基于MODIS MOD13A2数据集，将覆盖甘肃省的分幅影像，利用MRT工具及Python语言代码，进行批量拼接、投影转换、裁剪等处理，生成2018-2022年甘肃省MODIS MOD13A2 NDVI数据。本数据集空间分辨率为1km，时间分辨率为16天。", "ds_source": "

  本数据集的数据源为MOD13A2.v005 版本数据，数据来源于NASA官网(https://ladsweb.modaps.eosdis.nasa.gov)。", "ds_process_way": "

  （1）试运行MRT工具，生成MOD13A2 NDVI数据拼接和投影转换的prm文件。\n空间分辨率为1000 m。 \n

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  （2）利用MATLAB 语言程序生成调用MRT工具的批处理文件，并运行； \n

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  （3）利用甘肃省矢量边界，采用Python批量裁剪等步骤，最后采用GeoTIFF格式输出保存。", "ds_quality": "

  本数据集与源数据集MODIS MOD13A2.005质量一致。数据有效范围-2000 至 10000，缩放因子为0.0001，填充值为-3000。", "ds_acq_start_time": "2018-01-01 00:00:00", "ds_acq_end_time": "2022-12-31 00:00:00", "ds_acq_place": "甘肃省", "ds_acq_lon_east": 108.7075, "ds_acq_lat_south": 32.596111111111114, "ds_acq_lon_west": 92.33777777777777, "ds_acq_lat_north": 42.79333333333333, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 8916108500, "ds_files_count": 809, "ds_format": "tif", "ds_space_res": "1000m", "ds_time_res": "16天", "ds_coordinate": "WGS84", "ds_projection": "/", "ds_thumbnail": "1546f7cb-af61-4af2-b6c4-443d3f0fd78a.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "526ff655-4cd4-4650-bb86-6fd3481dfb65", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45", "170.4510" ], "quality_level": 3, "publish_time": "2023-12-27 11:22:30", "last_updated": "2025-05-29 16:22:21", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.GSEER.DB4129.2023", "i18n": { "en": { "title": "Gansu Province MOD13A2 Normalized Vegetation Index (NDVI) Dataset (2018-2022)", "ds_format": "TIFF", "ds_source": "

    The data source of this dataset is MOD13A2-v005 version data, which is sourced from the NASA official website（ https://ladsweb.modaps.eosdis.nasa.gov ）.", "ds_quality": "

  The quality of this data set is consistent with that of the source data set MODIS mod13a2.005. The valid range of data is - 2000 to 10000, the scaling factor is 0.0001, and the filling value is - 3000.", "ds_ref_way": "", "ds_abstract": "

    The vegetation index mainly reflects the difference between vegetation reflection in visible and near-infrared bands and soil background. Under certain conditions, each vegetation index can be used to quantitatively indicate the growth status of vegetation. At present, Normalized Difference Vegetation Index (NDVI) is an important data source for detecting vegetation growth status, vegetation coverage, and eliminating some radiation errors.\n

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    NDVI can reflect the background influence of plant canopy, such as soil, moist ground, snow, dead leaves, roughness, etc., and is related to vegetation cover. It is one of the important parameters reflecting the growth and nutritional information of crops. Based on this parameter, the nitrogen requirements of crops in different seasons can be determined, which plays an important guiding role in the rational application of nitrogen fertilizers.\n

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    Based on the MODIS MOD13A2 dataset, segmented images covering Gansu Province will be processed using MRT tools and Python language code for batch stitching, projection conversion, cropping, etc., to generate MODIS MOD13A2 NDVI data for Gansu Province from 2018 to 2022. The spatial resolution of this dataset is 1km, and the temporal resolution is 16 days.

", "ds_time_res": "16天", "ds_acq_place": "Gansu Province", "ds_space_res": "1000m", "ds_projection": "/", "ds_process_way": "

    (1) Run the MRT tool to generate prm files for MOD13A2 NDVI data concatenation and projection conversion.\nThe spatial resolution is 1000 meters.\n

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    (2) Generate a batch file using MATLAB language program to call the MRT tool and run it; \n

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    (3) Utilize the vector boundary of Gansu Province, perform batch cropping using Python, and finally output and save in GeoTIFF format.", "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": [ "植被指数", "植被覆盖度", "投影转换", "植物冠层", "农作物长势" ], "ds_subject_tags": [ "地理学", "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "甘肃省" ], "ds_time_tags": [ 2018, 2019, 2020, 2021, 2022 ], "ds_contributors": [ { "true_name": "张耀南", "email": "yaonan@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": "李红星", "email": "lihongxing@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": "敏玉芳", "email": "myf@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": "遥感及产品" }