黑河流域30m/月植被指数（NDVI/EVI）数据集提供了2011-2014年的月度NDVI/EVI合成产品，该数据利用我国国产卫星HJ/CCD数据兼具较高时间分辨率（组网后2天）和空间分辨率（30m）的特点构造多角度观测数据集，以平均合成MC法作为主算法进行合成，备用算法采用VI法。同时，将多源数据集主要观测角作为质量描述符的一部分，以辅助分析合成植被指数残留的角度效应。每月获取的遥感数据能够提供比单天传感器数据更多的角度和更多次的观测，但由于传感器的在轨运行时间及性能差异，多时相、多角度观测数据的质量参差不齐。因此，为有效利用多时相、多角度观测数据，本算法在利用多源数据集进行植被指数合成前，设计了对多源数据集的数据质量检查，去除了较大误差观测及不一致的观测。
\n在黑河中游农田区域的验证结果表明，联合多时相、多角度观测数据的NDVI/EVI合成结果与地面实测数据具有较好的一致性（R2=0.89，RMSE=0.092）。总之，黑河流域30m/月合成植被指数（NDVI/EVI）数据集综合利用多时相、多角度观测数据以提高参数产品的估算精度、时间分辨率等，实现了稳定的标准化产品的从无到有，更好的服务于遥感数据产品的应用。
", "ds_source": "黑河流域30m/月植被指数（NDVI/EVI）数据集提供了2011-2014年的月度NDVI/EVI合成产品，该数据利用我国国产卫星HJ/CCD数据兼具较高时间分辨率（组网后2天）和空间分辨率（30m）的特点构造多角度观测数据集。
", "ds_process_way": "利用多源数据集进行植被指数合成前，设计了对多源数据集的数据质量检查，去除了较大误差观测及不一致的观测。在黑河中游农田区域的验证结果表明，联合多时相、多角度观测数据的NDVI/EVI合成结果与地面实测数据具有较好的一致性（R2=0.89，RMSE=0.092）。
", "ds_quality": "数据质量良好
", "ds_acq_start_time": "2011-01-01 00:00:00", "ds_acq_end_time": "2015-01-01 00:00:00", "ds_acq_place": "黑河流域", "ds_acq_lon_east": 101.75, "ds_acq_lat_south": 37.25, "ds_acq_lon_west": 97.75, "ds_acq_lat_north": 42.1, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 12200807827, "ds_files_count": 11, "ds_format": "tif", "ds_space_res": "/", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "/", "ds_thumbnail": "4359c938-13bc-4cb0-bcb7-fac75f0022fe.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "本数据由“黑河生态水文遥感试验（HiWATER）”产生，用户在使用数据时请在正文中明确声明数据的来源，并在参考文献部分引用本元数据提供的引用方式。", "ds_from_station": null, "organization_id": "c94b3578-20da-4346-9de9-c702b6ca8983", "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": "2021-09-14 09:57:20", "last_updated": "2025-05-29 16:19:01", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.2021.30", "i18n": { "en": { "title": "Heihe River eco hydrological remote sensing test: 30m / month synthetic vegetation index (NDVI / EVI) data set of Heihe River Basin (2011-2014)", "ds_format": "TIFF", "ds_source": "The 30m / month vegetation index (NDVI / EVI) data set of Heihe River basin provides the monthly NDVI / EVI synthetic product from 2011 to 2014. The data uses the characteristics of domestic satellite HJ / CCD data with high temporal resolution (2 days after Networking) and spatial resolution (30M) to construct a multi angle observation data set
", "ds_quality": "Good data quality
", "ds_ref_way": "", "ds_abstract": "The 30m / month vegetation index (NDVI / EVI) data set of Heihe River basin provides the monthly NDVI / EVI synthesis products from 2011 to 2014. The data uses the characteristics of domestic satellite HJ / CCD data with high temporal resolution (2 days after Networking) and spatial resolution (30M) to construct a multi angle observation data set. The average synthesis MC method is used as the main algorithm for synthesis, and the VI method is used as the standby algorithm. At the same time, the main observation angle of multi-source data set is taken as a part of quality descriptor to assist in analyzing the angle effect of synthetic vegetation index residue. The monthly remote sensing data can provide more angles and more observations than the single day sensor data, but the quality of multi temporal and multi angle observation data is uneven due to the differences in the on orbit operation time and performance of the sensor. Therefore, in order to make effective use of multi temporal and multi angle observation data, before using multi-source data sets for vegetation index synthesis, this algorithm designs the data quality inspection of multi-source data sets to remove large error observations and inconsistent observations
\nThe verification results in the farmland area in the middle reaches of Heihe River show that the NDVI / EVI synthesis results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.89, RMSE = 0.092). In short, the 30m / month synthetic vegetation index (NDVI / EVI) data set in Heihe River Basin comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, so as to realize the stable standardized products from scratch and better serve the application of remote sensing data products
", "ds_time_res": "月", "ds_acq_place": "Heihe River Basin", "ds_space_res": "/", "ds_projection": "/", "ds_process_way": "Before using multi-source data sets for vegetation index synthesis, the data quality inspection of multi-source data sets is designed to remove large error observations and inconsistent observations. The verification results in the farmland area in the middle reaches of Heihe River show that the NDVI / EVI synthesis results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.89, RMSE = 0.092)
", "ds_ref_instruction": "This data is generated by \"Heihe eco hydrological remote sensing experiment (hiwater)\". When using the data, users should clearly state the source of the data in the text and quote the reference method provided by this metadata in the reference part." } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC 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": [ "植被覆盖度", "遥感产品", "生态遥感产品" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域" ], "ds_time_tags": [ 2011, 2012, 2013, 2014 ], "ds_contributors": [ { "true_name": "李静", "email": "lijing01@radi.ac.cn", "work_for": "中国科学院遥感与数字地球研究所", "country": "中国" }, { "true_name": "柳钦火", "email": "qhliu@irsa.ac.cn", "work_for": "中国科学院遥感应用研究所", "country": "中国" }, { "true_name": "仲波", "email": "zhongbo@radi.ac.cn", "work_for": "中国科学院遥感与数字地球研究所遥感科学国家重点实验室", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "李静", "email": "lijing01@radi.ac.cn", "work_for": "中国科学院遥感与数字地球研究所", "country": "中国" } ], "ds_managers": [ { "true_name": "李静", "email": "lijing01@radi.ac.cn", "work_for": "中国科学院遥感与数字地球研究所", "country": "中国" } ], "category": "遥感及产品" }