植被的净初级生产力（NPP，Net Primary Productivity）是陆地植被通过光合作用固定太阳能，在单位时间内单位面积所获得生物量的净增加量。\n
NPP作为陆地生态系统碳循环的一个重要组成成分，其对于控制大气中CO₂浓度的上升有着举足轻重的作用。它是植物自身生物学特性与外界环境相互适应的结果，不仅是异养生物生存的物质和能量基础，同时也是生物地球化学循环的关键环节，是评价生态结构功能稳定性的重要指标之一。\n
由于光合作用直接影响植被的NPP，而归一化植被指数（Normalized Difference Vegetation Index,NDVI）又可以较为精准地反映植被的绿度和光合作用的强度，因此在区域和全球生态系统模型中，NDVI常被直接或间接地用于计算植被NPP。", "ds_source": "
该数据集的数据源为MOD17A3HGF.v006 版本数据，涉及分幅影像网格为h26v05和h27v05，空间分辩率为500 m，时间分辨率为1年。", "ds_process_way": "
（1）运行MRT工具，生成MOD17A3HGF NPP数据拼接和投影转换的prm文件，利用MATLAB 语言程序生成调用MRT工具的批处理文件，并运行。\n
（2）利用渭河流域矢量边界，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 MOD17A3HGF.v006质量一致。NPP数据单位为kgC/m²/year，有效范围﹣30000—32700，放缩因子为0.0001，填充值范围32761—32767，其中：32761为未分类土地类型，32762为城镇建成区，32763为永久湿地或淹没的沼泽地，32764为常年积雪或覆盖冰的区域，32765为贫瘠稀疏的地区（如岩石、苔原和沙漠），32766为内陆淡水等覆盖区，32767为其他情况填充值。", "ds_acq_start_time": "2000-01-01 00:00:00", "ds_acq_end_time": "2020-12-31 00:00:00", "ds_acq_place": "渭河流域,甘肃省,陕西省,宁夏回族自治区", "ds_acq_lon_east": 110.27444444444444, "ds_acq_lat_south": 33.69611111111111, "ds_acq_lon_west": 103.9713888888889, "ds_acq_lat_north": 37.40833333333333, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 30969508, "ds_files_count": 22, "ds_format": "tif", "ds_space_res": "500", "ds_time_res": "年", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "12eb4ca9-7568-410c-bdb9-f4ade0236491.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "0d5fea4e-6fd7-4c70-b28b-3f91204c579a", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2021-10-13 11:38:41", "last_updated": "2025-05-29 11:35:52", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.WRiver.2021.31", "i18n": { "en": { "title": "MOD17A3HGF Net Primary Productivity NPP data for the Weihe River Basin (2000-2020)", "ds_format": "tif", "ds_source": "
The data source for this dataset is the MOD17A3HGF.v006 version of the data, which involves split-image grids of h26v05 and h27v05 with a spatial resolution of 500 m and a temporal resolution of 1 year.", "ds_quality": "
This dataset is consistent in quality with the source dataset MODIS MOD17A3HGF.v006.The NPP data unit is kgC/m²/year, with a valid range of -30,000 to 32700, an exaggeration factor of 0.0001, and a range of fill values of 32761 to 32767, where: 32761 is unclassified land type, 32762 is built-up area of towns and cities, 32763 is permanent wetland or submerged marshland, 32764 is perennial snow or ice-covered area, 32765 is barren and sparse area (e.g., rocky, tundra, and deserts), 32766 is covered area such as inland freshwater, and 32767 is the infill value for other cases.", "ds_ref_way": "", "ds_abstract": "
Net Primary Productivity (NPP, Net Primary Productivity) of vegetation is the net increase in biomass per unit area per unit time gained by terrestrial vegetation through the fixation of solar energy by photosynthesis.\n
As an important component of the carbon cycle in terrestrial ecosystems, NPP plays a pivotal role in controlling the rise of atmospheric CO₂ concentration. It is the result of the mutual adaptation between plants' own biological characteristics and the external environment, and is not only the material and energy basis for the survival of heterotrophic organisms, but also a key link in the biogeochemical cycle, which is one of the important indexes for evaluating the functional stability of ecological structure.\n
Since photosynthesis directly affects the NPP of vegetation, and the Normalized Difference Vegetation Index (NDVI) can more accurately reflect the greenness of vegetation and the intensity of photosynthesis, NDVI is often used directly or indirectly to calculate the NPP of vegetation in regional and global ecosystem models.
", "ds_time_res": "年", "ds_acq_place": "Weihe River Basin, Gansu Province, Shaanxi Province, Ningxia Hui Autonomous Region", "ds_space_res": "500", "ds_projection": "", "ds_process_way": "(1) Run the MRT tool to generate prm files for MOD17A3HGF NPP data splicing and projection conversion, and use the MATLAB language program to generate a batch file for calling the MRT tool and run it. \n
(2) Using the vector boundaries of the Weihe River Basin, steps such as Python batch cropping are used, and finally the GeoTIFF format is used for output and saving.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 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, "ds_topic_tags": [ "MOD17A3", "净初级生产力", "NPP" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "渭河流域", "甘肃省", "宁夏回族自治区", "陕西省" ], "ds_time_tags": [ 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020 ], "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": "生态" }