本数据为利用sentinel2号反射率产品数据进行进一步加工，其中原始数据为全疆10米月度哨兵二号反射率镶嵌数据集，叶面积指数数据通过机器学习进行提取，质量控制主要采用全疆2020-2021年叶面积实测数据进行模型构建和验证。
", "ds_source": "哨兵二号反射率数据主要来源为欧空局下载。其余辅助数据来源为实地测量数据，自主产生。
", "ds_process_way": "用于本模型计算的叶面积指数通过lai2000测量仪器在样地内进行5点法平均采集。本数据集通过随机森林进行叶面积指数的反演的计算。数据分辨率为10m。其中随进森林算法的训练样本包括由吐鲁番哈密地区，艾比湖流域，南疆塔里木河流域北缘的实测数据集，数据采样仪器为LAI2000和Sunscan。
", "ds_quality": "质量控制主要采用全疆2020-2022年叶面积实测数据进行模型构建和验证。本数据集在农作物和草地等误差不超过20%。
", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 1443791205154, "ds_files_count": 32, "ds_format": "栅格", "ds_space_res": "10米", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "CGCS2000", "ds_thumbnail": "bf434d17-4313-42ea-9620-3291d081f09f.jpg", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "数据来源引用：新疆10m叶面积指数数据集（2022年4-10月）来源于第三次新疆综合科学考察专项 \"空天地网一体化综合科考监测体系建设(2021xjkk1400)\"", "ds_from_station": null, "organization_id": "a5877b42-96ea-4f13-af7e-246f355413d6", "doi_value": "", "subject_codes": [ "170.40" ], "quality_level": 1, "publish_time": "2025-12-04 18:58:27", "first_publish_time": null, "last_updated": "2026-01-14 11:22:50", "protected": false, "protected_to": "2025-10-31 00:00:00", "lang": "zh", "cstr": "33110.11.XIEG.xjsedata.2022.00000128", "license": null, "extra": null, "files_shape": [ { "name": "2021xjkk1400-70-2023031070", "size": null, "is_dir": true } ], "features": null, "data_level": 0, "i18n": { "en": { "title": "Xinjiang 10m leaf area index dataset (April to October 2022)", "ds_abstract": "This data is for further processing using sentinel2 reflectance product data. The original data is the 10-meter monthly Sentinel 2 reflectance mosaic data set in Xinjiang. The leaf area index data is extracted through machine learning. The quality control mainly uses the 2020-2021 leaf area measurement data in Xinjiang for model construction and verification.
", "ds_source": "The main source of Sentinel-2 reflectivity data is downloaded from ESA. The rest of the auxiliary data sources are on-site measurement data and are generated independently.
", "ds_process_way": "The leaf area index used for calculation of this model was collected on average by a 5-point method in the sample plot using a lai2000 measuring instrument. This dataset uses random forests to calculate the inversion of leaf area index. The data resolution is 10m. The training samples of the following forest algorithm include measured data sets from Turpan's Hami City, Aibi Lake Basin, and the northern edge of the Tarim River Basin in southern Xinjiang. The data sampling instruments are LAI2000 and Sunscan.
", "ds_quality": "Quality control mainly uses measured leaf area data from 2020 to 2022 in Xinjiang for model construction and verification. The error of this dataset in crops and grasslands does not exceed 20%.
", "ds_ref_instruction": "Data source citation: Xinjiang's 10m leaf area index dataset (April to October 2022) comes from the third Xinjiang comprehensive scientific expedition special project \"Construction of Integrated Comprehensive Scientific Research Monitoring System of Air, Space, Space and Network (2021 xjkk1400)\"", "ds_format": "grid", "ds_projection": "CGCS2000", "ds_space_res": "10 meters", "ds_time_res": "months" } }, "license_type": null, "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" ], "ds_subject_tags": [ "地图学" ], "ds_class_tags": [], "ds_locus_tags": [ "新疆" ], "ds_time_tags": [ 2022 ], "ds_contributors": [ "刘铁", "马勇刚" ], "ds_meta_authors": [ "马勇刚" ], "ds_managers": [ "李锦" ], "category": "哨兵" }