2008年3月7日至2008年3月21日，在扁都口加密观测区测量了典型地物的ASD光谱数据。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
\n测量采用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
\n测量时间、测量地物及内容如下：\n2008-03-07，仪器试测了扁都口地区干土、湿土、秸秆、雪地、草地的光谱，布置样方进行观测。2008-03-21地表有10cm左右积雪覆盖，测量了扁都口积雪的光谱特性，没有布置样方。2008-03-17观测数据是与TM同步的。\n
\n采样方式：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。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，保证波谱测量的准同步性。 \n
\n测量数据为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）。原始数据中文件为ASD自带格式，用ASD Viewspec软件打开。
", "ds_source": "测量采用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
\n测量时间、测量地物及内容如下：\n
\n2008-03-07，仪器试测了扁都口地区干土、湿土、秸秆、雪地、草地的光谱，布置样方进行观测。2008-03-21地表有10cm左右积雪覆盖，测量了扁都口积雪的光谱特性，没有布置样方。2008-03-17观测数据是与TM同步的。", "ds_process_way": "
波谱数据测量：\n
\n（1）在测量前将测量点位坐标输入GPS或采用测绳确定测量点位。\n
\n（2）同步测量开始前半小时到达试验场，检查仪器设备状态，分配测量参与人员任务。\n
\n（3）测量前15分钟前开机进行预热，使仪器暗电流值稳定后开始测量。\n
\n（4）记录天气状况、场地情况和测量人员。设定文件存储路径，设定波谱平均次数、暗电流和参考板采样次数。去除暗电流，对积分时间进行优化。\n
\n（5）对地物进行走测测量，注意在测量的过程中身体和自身阴影不在波谱仪视场范围内。每隔1分钟左右（根据天气情况进行调整）测量参考板。
\n（6）将测量结果进行记录，对地物照相记录，导出测量数据，关闭仪器和笔记本电脑。\n
\n采样方式：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。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，保证波谱测量的准同步性。", "ds_quality": "
\n数据质量良好
", "ds_acq_start_time": "2008-03-07 00:00:00", "ds_acq_end_time": "2008-03-21 00:00:00", "ds_acq_place": "黑河流域", "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": 156132826, "ds_files_count": 2, "ds_format": "ascll,txt", "ds_space_res": null, "ds_time_res": "14日", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "6ffa9fb1-0ce5-4929-b53f-11f448b97f2a.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.db1883.2022", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2022-03-15 17:04:08", "last_updated": "2025-06-30 16:05:50", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.2021.1741", "i18n": { "en": { "title": "Integrated remote sensing joint experiment of Heihe River: spectral measurement data set of typical features in biandukou intensive observation area", "ds_format": "ascll,txt", "ds_source": "ASD FieldSpec frtm (Boulder, Co, USA) was used for measurement. The spectral range is 350nm-2500nm. The spectral resolution is 3nm in visible near-infrared band and 10nm in short wave infrared band.\n
\nThe survey time, features and contents are as follows:\n
\nOn March 7, 2008, the instrument tested the spectra of dry soil, wet soil, straw, snow and grassland in biandukou area, and arranged quadrats for observation. On March 21, 2008, the surface was covered with about 10cm snow. The spectral characteristics of the snow at biandukou were measured, and no quadrat was arranged. On March 17, 2008, the observation data were synchronized with TM.", "ds_quality": "
\nGood data quality
", "ds_ref_way": "", "ds_abstract": "From March 7, 2008 to March 21, 2008, the ASD spectral data of typical features were measured in the Bian Du Kou encrypted observation area. Through the grid spectrum measurement results of ground features, the spatial variation characteristics and laws of ground feature subpixel spectrum are explored, and the spectral characteristics of ground features in cold and arid areas are analyzed. 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
\nASD FieldSpec frtm (Boulder, Co, USA) was used for measurement. The spectral range is 350nm-2500nm. The spectral resolution is 3nm in visible near-infrared band and 10nm in short wave infrared band.\n
\nThe survey time, features and contents are as follows:\nOn March 7, 2008, the instrument tested the spectra of dry soil, wet soil, straw, snow and grassland in biandukou area, and arranged quadrats for observation. On March 21, 2008, the surface was covered with about 10cm snow. The spectral characteristics of the snow at biandukou were measured, and no quadrat was arranged. On March 17, 2008, the observation data were synchronized with TM.\n
\nSampling method: select the center of the area in a flat and homogeneous area to lay the quadrat. Select 90m respectively × 90m、450m × 450m is used as the grid sampling area of three different scales. At 90m × 90m、450m × 9 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. The 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 patrol mode to ensure the quasi synchronization of spectrum measurement.\n
\nThe measurement data is in ASCII format and can be opened with 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 in the original data is in ASD's own format and opened with ASD viewspec software.
", "ds_time_res": "14日", "ds_acq_place": "Heihe River Basin", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Spectral data measurement:\n
\n（ 1) Before the survey, input the coordinates of the survey points into GPS or use the survey rope to determine the survey points.\n
\n（ 2) Arrive at the test site half an hour before the start of synchronous measurement, check the status of instruments and equipment, and assign tasks to measurement participants.\n
\n（ 3) Start the machine 15 minutes before measurement for preheating, and start measurement after stabilizing the dark current value of the instrument.\n
\n（ 4) Record weather conditions, site conditions and surveyors. Set the file storage path, set the average times of spectrum, dark current and reference board sampling times. Remove the dark current and optimize the integration time.\n
\n（ 5) During the walking survey of ground objects, pay attention that the body and its own shadow are not within the field of view of the spectrometer. Measure the reference plate every 1 minute or so (adjusted according to the weather conditions)\n
\n（ 6) Record the measurement results, take photos of the ground features, export the measurement data, and turn off the instrument and laptop.\n
\nSampling method: select the center of the area in a flat and homogeneous area to lay the quadrat. Select 90m respectively × 90m、450m × 450m is used as the grid sampling area of three different scales. At 90m × 90m、450m × 9 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. The 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 patrol mode to ensure the quasi synchronization of spectrum measurement.", "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": [ "地物光谱", "ASD光谱仪", "反射率" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域", "扁都口加密观测区", "上游寒区水文试验区" ], "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" } ], "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" }