2007年9月19日预试验期间，在临泽站开展了Envisat ASAR卫星地面同步观测试验，2007年9月19日成功获得了一景Envisat ASAR影像。Envisat ASAR数据为AP模式，VV/VH极化组合方式，过境时间约为11:29BJT。本地面数据可为发展和验证Envisat ASAR遥感反演土壤水分提供基本的地面数据集。\n
\n测量内容：\n
\n1. 土壤水分。样方分布：临泽芦苇地、张掖农田、张掖戈壁、临泽玉米地、临泽苜蓿地、张掖观象台、临泽湿地。观测方法：环刀法。\n
\n2. GPS位置，测量仪器：GARMIN GPS 76。\n
\n3. 植被信息。记录信息：株高、植株鲜重、植株干重、取样方式、描述（例如地表类型，均匀程度，干湿程度等）。\n
\n4. 大气参数。\n 测量仪器：遥感所的法国CIMEL公司生产CE318太阳分光光度计。\n 测量目标：利用太阳分光光度计测量得到的大气参数。测量地点：大满水管所。\n 测量内容：CE318太阳分光光度计通过直接太阳辐射测量数据，可以反演出非水汽通道的光学厚度、瑞利散射、气溶胶光学厚度，水汽通道936nm测量数据可以获得大气气柱的水汽含量，水平能见度也可从CE318数据导出。本次测量采用了北京师范大学的CE318，其可提供1020nm、936nm、870nm、670nm和440nm共5个波段的光学厚度，可以利用936nm测量数据反演大气柱水汽含量。\n 数据存储：本数据包括原始数据和处理后的大气数据。原始数据以CE318特有文件格式*.k7存储，可用ASTPWin软件打开，并附带说明文件ReadMe.txt ；处理后文件包括利用原始数据反演获得光学厚度、瑞利散射、气溶胶光学厚度、水平能见度和近地表大气温度，以及参与计算的太阳方位角、天顶角、日地距离修正因子和大气柱质量数。\n
\n5. 粗糙度观测。粗糙度数据由粗糙度板测量，通过数码照相采集，然后在ArcView软件下，对照片中每根辐条的顶端以及板子的四角做手工数字化采样，获得其图像坐标值，经过几何校正后，计算得到每根辐条的高度，然后按公式计算表面高度标准离差和表面相关长度。其计算公式见《微波遥感》第二卷234-236页。粗糙度数据中首先是样点名称，之后数据正文包括4列（编号、文件名、标准离差、相关长度）。每一个文件名，即txt文件对应一张采样照片，标准离差（cm）与相关长度（cm）即代表了粗糙度。之后是每张照片中101根辐条的长度，属于中间结果，用以检查校正。
", "ds_source": "2007年9月19日预试验期间，在临泽站开展了Envisat ASAR卫星地面同步观测试验，2007年9月19日成功获得了一景Envisat ASAR影像。Envisat ASAR数据为AP模式，VV/VH极化组合方式，过境时间约为11:29BJT。本地面数据可为发展和验证Envisat ASAR遥感反演土壤水分提供基本的地面数据集。
", "ds_process_way": "土壤水分。样方分布：临泽芦苇地、张掖农田、张掖戈壁、临泽玉米地、临泽苜蓿地、张掖观象台、临泽湿地。观测方法：环刀法。
\nGPS位置，测量仪器：GARMIN GPS 76。
\n植被信息。记录信息：株高、植株鲜重、植株干重、取样方式、描述（例如地表类型，均匀程度，干湿程度等）。
\n大气参数。测量仪器：遥感所的法国CIMEL公司生产CE318太阳分光光度计。\n
粗糙度观测。粗糙度数据由粗糙度板测量，通过数码照相采集，然后在ArcView软件下，对照片中每根辐条的顶端以及板子的四角做手工数字化采样，获得其图像坐标值，经过几何校正后，计算得到每根辐条的高度，然后按公式计算表面高度标准离差和表面相关长度。", "ds_quality": "
数据质量良好
", "ds_acq_start_time": "2007-09-19 00:00:00", "ds_acq_end_time": "2007-09-19 00:00:00", "ds_acq_place": "黑河流域, 观象台加密观测区, 中游干旱区水文试验区, 盈科绿洲加密观测区, 临泽站加密观测区, 临泽草地加密观测区", "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": "apply-access", "ds_total_size": 1700131157, "ds_files_count": 2, "ds_format": "excel", "ds_space_res": null, "ds_time_res": "时", "ds_coordinate": "WGS84", "ds_projection": "", "ds_thumbnail": "69f6653f-df70-405b-8c4e-662042470bcf.png", "ds_thumb_from": 0, "ds_ref_way": "戴礼云, 车涛, 李新, 韩旭军, 郝晓华, 晋锐, 李弘毅, 梁继, 潘小多, 冉有华 , 王旭峰, 刘强，黑河综合遥感联合试验：预试验期中游干旱区水文试验区加密观测区Envisat ASAR地面同步观测数据集（2007年9月19日），国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2020，doi：10.12072/ncdc.NIEER.db1813.2022", "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.db1813.2022", "subject_codes": null, "quality_level": 3, "publish_time": "2022-03-14 17:16:39", "last_updated": "2022-03-14 17:16:39", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.NIEER.2021.1793", "i18n": { "en": { "title": "Heihe River Integrated Remote Sensing joint test: ENVISAT ASAR ground synchronous observation data set of dense observation area in hydrological test area of arid area in the middle reaches of the pre-test period (September 19, 2007)", "ds_format": "", "ds_source": "During the pre-test on September 19, 2007, ENVISAT ASAR satellite ground synchronous observation test was carried out at Linze station, and an ENVISAT ASAR image was successfully obtained on September 19, 2007. ENVISAT ASAR data is AP mode, VV / VH polarization combination mode, and the transit time is about 11:29bjt. Local surface data can provide a basic ground data set for the development and verification of ENVISAT ASAR remote sensing inversion of soil moisture.", "ds_quality": "
Good data quality
", "ds_ref_way": "", "ds_abstract": "During the pre-test on September 19, 2007, ENVISAT ASAR satellite ground synchronous observation test was carried out at Linze station, and an ENVISAT ASAR image was successfully obtained on September 19, 2007. ENVISAT ASAR data is AP mode, VV / VH polarization combination mode, and the transit time is about 11:29bjt. Local surface data can provide a basic ground data set for the development and verification of ENVISAT ASAR remote sensing inversion of soil moisture.\n
\nMeasurement content:\n
\n1. soil moisture. Quadrat distribution: Linze reed land, Zhangye farmland, Zhangye Gobi, Linze corn land, Linze alfalfa land, Zhangye Observatory and Linze wetland. Observation method: ring knife method.\n
\n2. GPS position, measuring instrument: Garmin GPS 76.\n
\n3. Vegetation information. Record information: plant height, plant fresh weight, plant dry weight, sampling method and description (e.g. surface type, uniformity, dry and wet degree, etc.).\n
\n4. Atmospheric parameters.\n Measuring instrument: CE318 solar spectrophotometer produced by French cimel company of Remote Sensing Institute.\n Measurement target: atmospheric parameters measured by solar spectrophotometer. Measuring location: Dawan water pipe station.\n Measurement content: CE318 solar spectrophotometer can inverse the optical thickness, Rayleigh scattering and aerosol optical thickness of non water vapor channel through the direct solar radiation measurement data. The water vapor content of atmospheric column can be obtained from the 936nm measurement data of water vapor channel, and the horizontal visibility can also be derived from CE318 data. CE318 of Beijing Normal University is used in this measurement, which can provide the optical thickness of five bands: 1020nm, 936nm, 870nm, 670nm and 440nm, and the water vapor content of the atmospheric column can be retrieved from the 936nm measurement data.\n Data storage: this data includes original data and processed atmospheric data. The original data is stored in CE318 unique file format *. K7, which can be opened with astpwin software, and the description file readme.txt is attached; The processed documents include the optical thickness, Rayleigh scattering, aerosol optical thickness, horizontal visibility and near surface atmospheric temperature retrieved from the original data, as well as the solar azimuth, zenith angle, sun earth distance correction factor and atmospheric column mass number involved in the calculation.\n
\n5. Roughness observation. The roughness data is measured by the roughness board and collected by digital photography. Then, under the ArcView software, the top of each spoke in the photo and the four corners of the board are manually digitally sampled to obtain its image coordinate value. After geometric correction, the height of each spoke is calculated, and then the surface height standard deviation and surface related length are calculated according to the formula. The calculation formula is shown in pages 234-236, Volume II, microwave remote sensing. In the roughness data, the first is the sample name, and then the data body includes 4 columns (number, file name, standard deviation and correlation length). Each file name, i.e. TXT file, corresponds to a sampling photo, and the standard deviation (CM) and correlation length (CM) represent the roughness. This is followed by the length of 101 spokes in each photo, which belongs to the intermediate result to check and correct.
", "ds_time_res": "时", "ds_acq_place": "Heihe River Basin, intensive observation area of Observatory, hydrological test area of arid area in the middle reaches, intensive observation area of Yingke oasis, intensive observation area of Linze station and intensive observation area of Linze grassland", "ds_space_res": "", "ds_projection": "", "ds_process_way": "Soil moisture. Quadrat distribution: Linze reed land, Zhangye farmland, Zhangye Gobi, Linze corn land, Linze alfalfa land, Zhangye Observatory and Linze wetland. Observation method: ring knife method\n
GPS position, measuring instrument: Garmin GPS 76\n
Vegetation information. Record information: plant height, plant fresh weight, plant dry weight, sampling method and description (e.g. surface type, uniformity, dry and wet degree, etc.)\n
Atmospheric parameters. Measuring instrument: CE318 solar spectrophotometer produced by French cimel company of Remote Sensing Institute.\n
Roughness observation. The roughness data is measured by the roughness board and collected by digital photography. Then, under the ArcView software, the top of each spoke in the photo and the four corners of the board are manually digitally sampled to obtain its image coordinate value. After geometric correction, the height of each spoke is calculated, and then the surface height standard deviation and surface related length are calculated according to the formula.", "ds_ref_instruction": " \nThis data is generated by \"Heihe integrated remote sensing joint test\". 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, "recommendation_value": 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": [ "环刀", "ASAR", "气溶胶光学厚度", "地面同步观测", "预试验", "土壤水分", "CE318太阳分光光度计", "地表粗糙度", "大气光学厚度" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "黑河流域", "观象台加密观测区", "中游干旱区水文试验区", "盈科绿洲加密观测区", "临泽站加密观测区" ], "ds_time_tags": [ 2007 ], "ds_contributors": [ { "true_name": "戴礼云", "email": "dailiyun@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "车涛", "email": "chetao@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "李新", "email": "lixin@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "韩旭军", "email": "hanxj@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "郝晓华", "email": "haoxh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "晋锐", "email": "jinrui@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "李弘毅", "email": "lihongyi@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "梁继", "email": "leung@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "潘小多", "email": "panxiaoduo@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "冉有华", "email": "ranyh@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "王旭峰", "email": "wangxufeng@lzb.ac.cn", "work_for": " 中国科学院西北生态环境资源研究院", "country": "中国" }, { "true_name": "刘强", "email": "toliuqiang@bnu.edu", "work_for": "北京师范大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "戴礼云", "email": "dailiyun@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_managers": [ { "true_name": "戴礼云", "email": "dailiyun@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "遥感及产品" }