黑河流域30m/月合成植被覆盖度（FVC）数据集提供了2011-2014年的月度FVC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，将全国划分为不同植被区划、地类，分别计算植被指数（NDVI）与FVC的转换系数，采用计算的转换系数查找表和月度合成NDVI产品生产区域月度合成FVC产品。
黑河流域30m/月合成FVC产品通过高分辨率数据可以直接获得植被覆盖比例，减轻低分辨率数据异质性的影响；另外，选择植被生长变化的典型时期，通过对每一个像元时间序列植被指数进行拟合得到每个像元对应的生长曲线参数；再配合土地利用图和植被分类图，寻找区域的代表性均一像元用于训练植被指数的转换系数。
通过黑河流域30m/月合成FVC产品与ASTER参考FVC结果相比，30m/月合成FVC产品的数值略高于ASTER参考结果，但总体偏差并不大，产品与参考值的均方根误差（RMSE）最大值小于0.175。此外，与河北怀来实验场地面测量数据对比，30m/月合成FVC产品总体上反映了植被生长季节性变化，与地面测量数据结果偏差小于0.1；同时与东北、华北、东南地区的多个流域植被盖度地面测量结果对比，30m/月合成FVC产品与地面测量数据整体误差在0.2以内。
总之，黑河流域30m/月合成FVC数据集综合利用多时相、多角度遥感数据以提高FVC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/月合成植被覆盖度（FVC）数据集提供了2011-2014年的月度FVC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": "将全国划分为不同植被区划、地类，分别计算植被指数（NDVI）与FVC的转换系数，采用计算的转换系数查找表和月度合成NDVI产品生产区域月度合成FVC产品。
", "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, 中游人工绿洲试验区, 上游寒区水文试验区, 下游天然绿洲试验区", "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": 6356933128, "ds_files_count": 6, "ds_format": "tif", "ds_space_res": "/", "ds_time_res": "月", "ds_coordinate": "WGS84", "ds_projection": "/", "ds_thumbnail": "6754519b-9131-493a-a8c3-5964b694d84a.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 09:55:37", "last_updated": "2025-06-30 16:34:41", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB2854.2023", "i18n": { "en": { "title": "Heihe River eco hydrological remote sensing test: 30m / month synthetic vegetation coverage (FVC) data set of Heihe River Basin (2011-2015)", "ds_format": "TIFF", "ds_source": "The 30m / month synthetic vegetation coverage (FVC) data set of Heihe River basin provides the monthly FVC 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 vegetation coverage (FVC) data set of Heihe River basin provides the monthly FVC 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, which divides the country into different vegetation divisions and land types, Calculate the conversion coefficient between vegetation index (NDVI) and FVC respectively, and use the calculated conversion coefficient lookup table and monthly synthetic FVC products in the production area of monthly synthetic NDVI products
Synthetic FVC products at 30m / month in Heihe River basin can directly obtain the vegetation coverage ratio through high-resolution data, so as to reduce the impact of heterogeneity of low-resolution data; In addition, the typical period of vegetation growth and change is selected, and the growth curve parameters corresponding to each pixel are obtained by fitting the vegetation index of each pixel time series; Then, combined with the land use map and vegetation classification map, find the representative uniform pixels of the region for training the conversion coefficient of vegetation index
Compared with the aster reference FVC results, the value of 30m / month synthetic FVC products in Heihe River Basin is slightly higher than the aster reference FVC results, but the overall deviation is not large, and the maximum root mean square error (RMSE) between products and reference values is less than 0.175. In addition, compared with the ground measurement data of Hebei Huailai experimental field, the 30m / month synthetic FVC product generally reflects the seasonal change of vegetation growth, and the deviation from the ground measurement data is less than 0.1; At the same time, compared with the ground measurement results of vegetation coverage in many watersheds in Northeast, North and Southeast China, the overall error between 30m / month synthetic FVC product and ground measurement data is less than 0.2
In short, the 30m / month synthetic FVC data set in Heihe River basin makes comprehensive use of multi temporal and multi angle remote sensing data to improve the estimation accuracy and time resolution of FVC parameter products and better serve the application of remote sensing data products
", "ds_time_res": "月", "ds_acq_place": "Heihe River Basin, artificial oasis test area in the middle reaches, hydrological test area in the upper cold area, and natural oasis test area in the lower reaches", "ds_space_res": "/", "ds_projection": "/", "ds_process_way": "Divide the country into different vegetation divisions and land types, calculate the conversion coefficient between vegetation index (NDVI) and FVC respectively, and use the calculated conversion coefficient lookup table and monthly synthetic NDVI product production areas to synthesize FVC products monthly
", "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": "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": [ "植被覆盖度", "遥感产品", "生态遥感产品", "LUCC数据" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域", "中游人工绿洲试验区", "上游寒区水文试验区", "下游天然绿洲试验区" ], "ds_time_tags": [ 2011, 2012, 2013, 2014 ], "ds_contributors": [ { "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" }, { "true_name": "吴俊君", "email": "", "work_for": "中国科学院空天信息创新研究院遥感科学国家重点实验室", "country": "中国" }, { "true_name": "穆西晗", "email": "muxihan@bnu.edu.cn", "work_for": "北京师范大学地理学与遥感科学学院遥感科学国家重点实验室", "country": "中国" }, { "true_name": "吴善龙", "email": "", "work_for": "中国科学院空天信息创新研究院", "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" } ], "ds_meta_authors": [ { "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_managers": [ { "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" } ], "category": "遥感及产品" }