2008年3月17日在扁都口加密观测区开展了针对Landsat TM的地面同步观测试验，试验的目的是通过地物格网化波谱测量结果，探索地物亚象元波谱空间变异特点及规律，对寒旱区地物波谱特性进行分析。在此基础上，为典型地物目标与背景模型波谱模型数据库提供数据资料，为遥感影像模拟，遥感数据空间尺度转换提供基础数据。\n
测量的参数包括：光谱数据、地表温度、大气参数、土壤剖面重量含水量（0-1cm、1-3cm、3-5cm）、表层土壤冻融深度、土壤粗糙度。时间范围大约为11:10-13:30。\n
波谱测量仪器采用的是ASD Fieldspec FRTM（Boulder, Co, USA），波谱范围为350nm-2500nm，在可见光近红外波段波谱分辨率为3nm，在短波红外波谱分辨率为10nm。\n
数据为ASCII格式，可以使用记事本、写字板等软件打开。文件前5行为文件头，描述了数据的相关信息；之后两列数据，一列代表波长，一列代表反射率（百分反射率）。原始文件夹中后缀为.txt的文件不是反射率，是计算反射率的中间文件。 原始数据中文件为ASD自带格式，用ASD Viewspec软件打开。\n
本数据集包括9个文件，分别为：TM数据、太阳分光光度计测量数据、扁都口B1样地测量数据、扁都口B2样地测量数据、扁都口C1样地测量数据、扁都口G1样地测量数据、扁都口W1样地测量数据、扁都口W2样地测量数据和地物波谱数据。", "ds_source": "
地面同步测量的样方包括扁都口C1样地、扁都口G1样地、扁都口W1样地、扁都口W2样地、扁都口B1样地、扁都口B2样地。样方类型包括草地、麦茬地、深翻地、油菜茬地。在平坦、均质区域内选择区域中心布设样方。分别选择90m×90m、450m×450m作为三种不同尺度格网采样区。在90m×90m、450m×450m样方区内将用9×9格网划分，这样三种样方分别被划分为81个10m×10m、50m×50m的子格网。三种格网的具体含义为：以30m×30m、150m×150m作为卫星传感器的基础分辨率，在此基础上考虑单一象元八邻域象元对中心象元的贡献。并且将每个象元划分为9个子象元，探索亚象元波谱与整个象元波谱之间的规律。由于样点之间距离较远，90m×90m样方采用测绳、标志杆布设样方的方式实现，450m×450m样方采用GPS布设控制点方式实现。\n
\n采样方法为剖面线测量，通过对每一个子样方中心剖面线的测量来代表整个样方像元的波谱，通过多次测量波谱统计平均值，来代替对子样方的全采样。测量路线采用巡回方式，这样可以最大限度地节省人力物力，加快波谱测量速度，保证波谱测量的准同步性。", "ds_process_way": "
含水量测量方法是：取0-1cm、1-3cm、3-5cm土样，放入自封袋，土壤冻结深度的测量方法是通过用筷子插入地表感觉土壤硬度或者将土壤表层冻结层直接挖出测量冻结层厚度，来判断冻结深度。直尺直接测量，当土壤硬度较大并且有冰晶时，认为土壤冻结；反之，则认为土壤未冻。数据可以用Microsoft Office软件打开。", "ds_quality": "
\n数据质量良好
", "ds_acq_start_time": "2008-03-17 00:00:00", "ds_acq_end_time": "2008-03-18 00:00:00", "ds_acq_place": "黑河流域，上游寒区水文试验区，扁都口加密观测区", "ds_acq_lon_east": 100.44305555555556, "ds_acq_lat_south": 38.04333333333333, "ds_acq_lon_west": 100.58972222222222, "ds_acq_lat_north": 38.973888888888894, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 97800018, "ds_files_count": 2, "ds_format": "ascll", "ds_space_res": null, "ds_time_res": "时", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "12933996-ec77-4ef2-bbec-c28026548ee3.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "本数据由“黑河综合遥感联合试验”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": "14df1d8b-6362-4c0f-b88e-b46d4abe5db9", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.NIEER.db1891.2022", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2022-03-15 16:58:25", "last_updated": "2025-06-30 16:05:49", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.2021.1944", "i18n": { "en": { "title": "Heihe integrated remote sensing joint test: Landsat TM ground synchronous observation data set in biandukou encrypted observation area (March 17, 2008)", "ds_format": "ascll", "ds_source": "The quadrats for ground synchronous measurement include Biandu port C1, Biandu port G1, Biandu port W1, Biandu port W2, Biandu port B1 and Biandu port B2. Quadrat types include grassland, wheat stubble, deep ploughing and rape stubble. Select the center of the area to lay the quadrat in a flat and homogeneous area. Select 90m respectively × 90m、450m × 450m is used as the grid sampling area of three different scales. At 90m × 90m、450m × 9 will be used in 450m quadrat area × 9 grid division, so that the three quadrats are divided into 81 10m × 10m、50m × 50m sub grid. The specific meaning of the three grids is: 30m × 30m、150m × 150m is the basic resolution of satellite sensor. On this basis, the contribution of single pixel and eight neighborhood pixels to the central pixel is considered. Each pixel is divided into 9 sub pixels to explore the law between the sub-pixel spectrum and the whole pixel spectrum. Due to the long distance between sample points, 90m × The 90m quadrat is realized by laying the quadrat with measuring rope and marker post, with a height of 450m × The 450m quadrat is realized by laying control points with GPS.\n
\nThe sampling method is profile measurement, which represents the spectrum of the whole quadrat pixel by measuring the central profile of each sub quadrat, and replaces the full sampling of the sub quadrat by measuring the statistical average of the spectrum for many times. The survey route adopts tour mode, which can save manpower and material resources to the greatest extent, speed up the spectrum measurement speed and ensure the quasi synchronization of spectrum measurement.", "ds_quality": "
\nGood data quality
", "ds_ref_way": "", "ds_abstract": "On March 17, 2008, the ground synchronous observation test for Landsat TM was carried out in the biandukou intensive observation area. The purpose of the test is to explore the spatial variation characteristics and laws of sub-pixel spectrum of ground objects through the grid spectrum measurement results of ground objects, and analyze the spectral characteristics of ground objects in cold and arid areas. On this basis, it provides data for the spectral model database of typical ground object target and background model, and provides basic data for remote sensing image simulation and spatial scale conversion of remote sensing data.\n
The measured parameters include: spectral data, surface temperature, atmospheric parameters, soil profile weight and water content (0-1cm, 1-3cm, 3-5cm), surface soil freezing and thawing depth and soil roughness. The time range is about 11:10-13:30.\n
ASD FieldSpec frtm (Boulder, Co, USA) is used as the spectrum measuring instrument. The spectrum range is 350nm-2500nm. The spectral resolution is 3nm in the visible near-infrared band and 10nm in the short wave infrared band.\n
The data is in ASCII format and can be opened by Notepad, WordPad and other software. The first 5 lines of the file are the file header, which describes the relevant information of the data; The next two columns of data, one for wavelength and one for reflectance (percent reflectance). The file with suffix. TXT in the original folder is not reflectivity, but an intermediate file for calculating reflectivity. The file in the original data is in ASD's own format and opened with ASD viewspec software.\n
This data set includes 9 files: TM data, solar spectrophotometer measurement data, Biandu port B1 sample measurement data, Biandu port B2 sample measurement data, Biandu port C1 sample measurement data, Biandu port G1 sample measurement data, Biandu port W1 sample measurement data, Biandu port W2 sample measurement data and ground object spectrum data.
", "ds_time_res": "时", "ds_acq_place": "Heihe River Basin, upstream cold region, hydrological test area, biandukou intensive observation area", "ds_space_res": "", "ds_projection": "", "ds_process_way": "The water content measurement method is: take 0-1cm, 1-3cm and 3-5cm soil samples and put them into self sealing bags. The measurement method of soil freezing depth is to judge the freezing depth by inserting chopsticks into the surface to feel the soil hardness or directly digging out the frozen layer on the surface of the soil to measure the thickness of the frozen layer. Measured directly with a ruler, when the soil hardness is large and there are ice crystals, it is considered that the soil is frozen; On the contrary, it is considered that the soil is not frozen. Data can be opened with Microsoft office software.", "ds_ref_instruction": "This data was generated by the \"Heihe Comprehensive Remote Sensing Joint Experiment\". When using the data, please clearly state the source of the data in the main text and cite the citation provided by this metadata in the reference section." } }, "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": [ "土壤物理温度", "土壤冻结深度", "ASD光谱仪", "土壤水分", "手持式红外温度计", "CE318太阳分光光度计", "地表辐射温度", "大气光学厚度", "地表粗糙度", "反射率", "地面同步观测", "TM" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域", "上游寒区水文试验区", "扁都口加密观测区" ], "ds_time_tags": [ 2008 ], "ds_contributors": [ { "true_name": "赵少杰", "email": "geo_zhao@126.com", "work_for": "北京师范大学", "country": "中国" }, { "true_name": "任华忠", "email": "renhuazhong@pku.edu.cn", "work_for": "北京大学遥感与地理信息系统研究所", "country": "中国" }, { "true_name": "赵天杰", "email": "zhaotj@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": "潘金梅", "email": "", "work_for": "北京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "赵少杰", "email": "geo_zhao@126.com", "work_for": "北京师范大学", "country": "中国" } ], "ds_managers": [ { "true_name": "赵少杰", "email": "geo_zhao@126.com", "work_for": "北京师范大学", "country": "中国" } ], "category": "遥感及产品" }