黑河流域30m/月合成叶面积指数（LAI）数据集提供了2011-2014年的月度LAI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，考虑地表分类和地形起伏影响，算法针对不同植被类型特点选择适宜的一体化模型参数化方案，基于查找表方法反演LAI。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，首先设计了数据质量检查方案。利用黑河上游大野口地区与中游盈科、临泽等地区的9个森林样方，20个农田样方和14个稀树草原样方的LAI地面观测数据验证7月份LAI，反演结果与测量结果吻合得很好，平均误差小于1；此外联合多时相、多角度观测数据的LAI反演结果与地面实测数据具有较好的一致性（R2=0.9，RMSE=0.42）。
总之，黑河流域30m/月合成叶面积指数（LAI）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，更好的服务于遥感数据产品的应用。
", "ds_source": "黑河流域30m/月合成叶面积指数（LAI）数据集提供了2011-2014年的月度LAI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": "利用黑河上游大野口地区与中游盈科、临泽等地区的9个森林样方，20个农田样方和14个稀树草原样方的LAI地面观测数据验证7月份LAI，反演结果与测量结果吻合得很好，平均误差小于1；此外联合多时相、多角度观测数据的LAI反演结果与地面实测数据具有较好的一致性（R2=0.9，RMSE=0.42）。
", "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": 7723869645, "ds_files_count": 6, "ds_format": "tif", "ds_space_res": "/", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "/", "ds_thumbnail": "09423505-1ee8-400a-a0ee-fa3ba652817c.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 09:55:35", "last_updated": "2025-06-30 16:34:42", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.2021.9", "i18n": { "en": { "title": "Heihe River eco hydrological remote sensing experiment: 30m / month synthetic leaf area index (LAI) data set of Heihe River Basin (2011-2014)", "ds_format": "TIFF", "ds_source": "The 30m / month synthetic leaf area index (LAI) data set of Heihe River basin provides the monthly Lai synthetic 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
", "ds_quality": "Good data quality
", "ds_ref_way": "", "ds_abstract": "The 30m / month synthetic leaf area index (LAI) data set of Heihe River basin provides the monthly Lai synthetic 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, considering the influence of surface classification and terrain fluctuation, According to the characteristics of different vegetation types, the algorithm selects the appropriate parameterization scheme of the integrated model, and inverts the Lai based on the look-up table method. 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, a data quality inspection scheme is designed first. The Lai ground observation data of 9 forest quadrats, 20 farmland quadrats and 14 savanna quadrats in Dayekou area in the upper reaches of Heihe River and Yingke and Linze areas in the middle reaches of Heihe River are used to verify the Lai in July. The inversion results are in good agreement with the measurement results, and the average error is less than 1; In addition, the Lai inversion results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.9, RMSE = 0.42)
In short, the 30m / month synthetic leaf area index (LAI) data set in Heihe River basin makes comprehensive use of multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products 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": "The Lai ground observation data of 9 forest quadrats, 20 farmland quadrats and 14 savanna quadrats in Dayekou area in the upper reaches of Heihe River and Yingke and Linze areas in the middle reaches of Heihe River are used to verify the Lai in July. The inversion results are in good agreement with the measurement results, and the average error is less than 1; In addition, the Lai inversion results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.9, RMSE = 0.42)
", "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": [ "叶面积指数", "多角度观测数据", "遥感数据" ], "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": "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": "范闻捷", "email": "fanwj@pku.edu.cn", "work_for": "北京大学", "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": "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" } ], "ds_managers": [ { "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" } ], "category": "遥感及产品" }