长时间序列中国植被指数数据集是主要针对归一化植被指数（NDVI），基于空间分辨率为1km自1998年4月1日至2011年12月31日的每10天合成的四个波段的光谱反射率及10天最大化NDVI数据集。
", "ds_source": "长时间序列中国植被指数数据集是主要针对归一化植被指数（NDVI），基于空间分辨率为1km自1998年4月1日至2011年12月31日的每10天合成的四个波段的光谱反射率及10天最大化NDVI数据集。SPOT-VEGETATION-NDVI数据集中包含从1998年4月1日至2011年12月31日以旬为时间分辨率的.zip压缩文件。解压以后为每10天为一景的ESRI-GRID文件。SPO -VEGETATION-NDVI数据集命名规则为：v-yymmdd,其中v为vegetation的简称，yymmdd即表示该文件的当天日期，也是区别其他文件的主要标识。
", "ds_process_way": "VEGETATION传感器于1998年3月由SPOT-4搭载升空，从1998年4月开始接收用于全球植被覆盖观测的SP0T VGT数据。它拥有十分完善和高效的图像地面处理机构体系。VEGETATION数据主要由瑞典的Kiruna地面站负责接收，由位于法国Toulouse的图像质量监控中心负责图像质量并提供相关参数(如定标系数)，最终由位于比利时的VITO研究所的图像处理与存档中心负责全球VEGETATION数据存档与用户定单。 其中VGT—P(prototype)数据产品主要为科研人员提供高质量的物理量原型数据以便于他们研建算法和应用模型。数据经过严格的系统误差订正并重采样为经纬网投影，像元分辨率lkm，像元亮度值是地物在大气顶层的反射率。除提供四个波段原始数据外，还根据用户需要提供相关辅助参数，如大气状况、系统信息(太阳的天底角、方位角，视场角和接收时间)和地形数据等。 VGT—S(synthesis)产品提供经过大气纠正的地表反射率数据，并运用多波段合成技术来获得lkm分辨率的归一化植被指数( w)数据集。VGI—S产品包括每天合成的四个波段的光谱反射率及NDVI数据集(s1)，每10天合成的四个波段的光谱反射率及10天最大化NDVI数据集(S10)以减少云及BRDF的影响，同时S10 还被重采样成4km 分辨率(S10.4)和8km分辨率(S10.8)数据集。VGT—S产品以其高时间分辨率而被广泛使用。本数据集包含的是每10天合成的四个波段的光谱反射率及10天最大化NDVI数据集(S10)。SPOT源数据的预处理包括大气校正，辐射校正，几何校正，生成了10 d最大化合成的NDVI数据，并将-1到-0.1的值设置为-0.1，再通过公式\nYDN =(JNDVI +0.1)/0.004\n转换到0~250的YDN值。
", "ds_quality": "植被指数产品的一个重要特点是可以转换成叶冠生物物理学参数。植被指数(Ⅵ)在植被生物物理学参数(如，叶面指数LAI，绿蔽度，光合作用有效吸收辐射fAPAR 等)的获取方面还起着“中间变量”的作用。目前正在利用有全球代表性的地面、飞机和卫星观测的数据集研究植被指数和植被生物物理学参数的关系。这些资料可用于在卫星发射前评估Ⅵ算法性能，同时也提供植被指数产品与叶冠生物物理特性之间的转换系数。生物物理学资料的使用是植被指数验证计划的组成部分。植被指数产品将在几项对地观测系统(EOS)研究中发挥主要作用，同时也是近年来全球和区域生物圈模式产品的组成部分。
", "ds_acq_start_time": "1998-04-01 00:00:00", "ds_acq_end_time": "2011-12-23 00:00:00", "ds_acq_place": "黄河上游", "ds_acq_lon_east": 112.0, "ds_acq_lat_south": 32.0, "ds_acq_lon_west": 95.0, "ds_acq_lat_north": 42.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "apply-access", "ds_total_size": 55780391, "ds_files_count": 2, "ds_format": "adf", "ds_space_res": null, "ds_time_res": "日", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "9ef9e3e8-dc63-4976-9b64-9c6785886414.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": null, "ds_from_station": null, "organization_id": "9c4867b1-5cb1-4de0-abeb-df42547bf41e", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596 ", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": null, "quality_level": 3, "publish_time": "2020-12-22 10:28:21", "last_updated": "2023-08-23 16:46:11", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.Westdc.2020.686", "i18n": { "en": { "title": "Long time series vegetation index (NDVI) data set of the upper Yellow River (1998-2011)", "ds_format": "", "ds_source": "The long-time series vegetation index data set of China is mainly aimed at the normalized vegetation index (NDVI), which is based on the spectral reflectance of four bands synthesized every 10 days with a spatial resolution of 1km from April 1, 1998 to December 31, 2011 and the 10 day maximum NDVI data set. The spot-vegetation-ndvi dataset contains. Zip compressed files with ten day time resolution from April 1, 1998 to December 31, 2011. Decompress esri-grid file every 10 days. The naming rule of spo-vegetation-ndvi dataset is: v-yymmdd, where V is the abbreviation of vegetation, yymmdd means the date of the day of the file, and it is also the main identification to distinguish other files.
", "ds_quality": "An important feature of vegetation index products is that they can be converted into canopy biophysical parameters. Vegetation index (Ⅵ) also plays an \"intermediate variable\" role in the acquisition of biophysical parameters of vegetation (such as Lai, green cover, and fAPAR). At present, the relationship between vegetation index and biophysical parameters of vegetation is being studied by using the data sets of representative ground, aircraft and satellite observations. These data can be used to evaluate the performance of VI algorithm before satellite launch, and also provide the conversion coefficient between vegetation index products and canopy biophysical characteristics. The use of biophysical data is part of the vegetation index validation program. Vegetation index products will play a major role in several earth observation system of systems (EOS) studies, and are also part of global and regional biosphere model products in recent years.
", "ds_ref_way": "", "ds_abstract": "The long-time series vegetation index data set of China is mainly aimed at the normalized vegetation index (NDVI), which is based on the spectral reflectance of four bands synthesized every 10 days with a spatial resolution of 1km from April 1, 1998 to December 31, 2011 and the 10 day maximum NDVI data set.
", "ds_time_res": "日", "ds_acq_place": "", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Vegetation sensor was launched from SPOT-4 in March 1998, and received the sp0t VGT data for global vegetation coverage observation from April 1998. It has a very perfect and efficient image ground processing mechanism system. Vegetation data is mainly received by Kiruna ground station in Sweden, image quality monitoring center in Toulouse in France is responsible for image quality and providing relevant parameters (such as calibration coefficient). Finally, image processing and archiving center of Vito Research Institute in Belgium is responsible for global vegetation data archiving and user orders. Among them, vgt-p (prototype) data products mainly provide researchers with high-quality physical quantity prototype data to facilitate their research and construction of algorithms and application models. After strict system error correction and resampling, the data is projected by the longitude and latitude net. The pixel resolution is LKM, and the pixel brightness value is the reflectivity of the ground object on the top of the atmosphere. In addition to providing the original data of four bands, it also provides relevant auxiliary parameters according to the user's needs, such as the atmospheric conditions, system information (the sun's sky bottom angle, azimuth angle, field angle and receiving time) and terrain data. Vgt-s (synthesis) products provide atmospheric corrected surface reflectance data, and use multi band synthesis technology to obtain LKM resolution normalized vegetation index (W) data set. Vgi-s products include four band spectral reflectance and NDVI data set (S1) synthesized every day, four band spectral reflectance synthesized every 10 days and 10 day maximum NDVI data set (S10) to reduce the impact of cloud and BRDF, while S10 is also resampled into 4km resolution (s10.4) and 8km resolution (s10.8) data set. Vgt-s products are widely used for their high time resolution. This dataset contains the spectral reflectance of four bands synthesized every 10 days and the 10 day maximum NDVI dataset (S10). The preprocessing of spot source data includes atmospheric correction, radiometric correction and geometric correction. The NDVI data of 10 d maximum synthesis is generated, and the value from - 1 to - 0.1 is set to - 0.1, and then the formula is used", "ds_ref_instruction": " In order to respect intellectual property rights, protect the rights and interests of data authors, expand the services of data centers, and evaluate the application potential of data, data users are requested to clearly indicate the data source and data authors in the research results (including published papers, works, data products and unpublished research reports, data products, etc.) produced by using data. For data reprinted (secondary or multiple releases), the author must also indicate the source of the original data." } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黄河上游" ], "ds_time_tags": [ 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011 ], "ds_contributors": [ { "true_name": "薛娴", "email": "xianxue@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": "杜鹤强", "email": "dilikexue119@163.com", "work_for": "中国科学院西北生态环境资源研究院", "country": "" } ], "ds_managers": [ { "true_name": "薛娴", "email": "xianxue@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" }