{ "created": "2023-05-08 16:38:58", "updated": "2026-04-15 02:01:20", "id": "7a2557d6-e60f-41c5-8f7b-5aaa88286088", "version": 7, "ds_topic": null, "title_cn": "阿尔泰山喀纳斯冰川消融期反照率空间分布数据集（2009-2019年）", "title_en": "Surface Albedo data set on the Kanas Glacier during the Ablation Season in Altai Mountains (2009-2019)", "ds_abstract": "

  卫星遥感仪器并不能直接测量地表反照率，而是来自一定方向的包括地面和大气在内的地球系统的辐射。需要对原始遥感数据进行一系列预处理、计算得到地表宽波段反照率。本数据集基于Landsat数据，主要通过辐射定标，大气校正、地形校正、BRDF校正以及窄-宽波段转换的方法，反演得到喀纳斯冰川消融期表面反照率空间分布数据。并利用野外实测反照率数据对遥感反照率结果进行精度验证，准确度较高。总体上，消融期冰川表面反照率呈现随海拔的升高而增大的趋势，在冰川中部附近增速最快。\n

  数据格式为tiff。文件名为原始遥感影像获取时间，例如20090809代表数据于2009年8月9日获取。数据为0-1之间的无量纲。坐标系为WGM84。", "ds_source": "

  1.Landsat陆地卫星影像数据：从美国地质调查局网站(https://www.usgs.gov/) 和地理空间数据云 (http://www.gscloud.cn/)下载。\n

  2.冰川编目数据：中国第二次冰川编目数据(http://westdc.westgis.ac.cn) 和RGI 6.0 (https://www.glims.org/RGI/rgi60_dl.html)。\n

  3.ASTER GDEM V3数据：空间分辨率为30米，下载地址 https://lpdaac.usgs.gov/products/astgtmv003/。", "ds_process_way": "

  采用Klok等针对Landsat影像提出的冰川反照率反演算法来计算冰川反照率。其主要步骤包括：辐射定标，大气校正，地形校正，各向异性校正，窄-宽波段转换。其中辐射定标为常规遥感影像预处理步骤，在此不做赘述。\n

  大气校正：本文采用FLAASH模型进行大气校正。进行FLAASH大气校正时需要输入的影像中心点坐标、传感器类型、飞行日期、影像分辨率等信息通过影像头文件获得，地面高程是根据DEM数据计算的冰面平均值，大气模式选择中纬度夏季标准大气模式。\n

  地形校正：本文利用黄微等改进的一种C校正算法，在不进行线性拟合的情况下也可以达到良好的校正效果。改进后的校正方程为：\nLH=(LT-Lmin )×[cos⁡β-cos⁡αmin ]/[cos⁡α-cos⁡αmin] +Lmin\n

式中：LT为倾斜地表的反射率；LH为水平地表的反射率；Lmin阴影地区最小的反射率值；α为局地太阳天顶角；β为太阳天顶角；αmin为最小天顶角。\n

  各向异性校正：由于雪冰具有强烈的各向异性反射特性，因此，本文引入各向异性校正因子来对反演反射率进行各向异性校正，公式为：\na=r/(f(θr,θv,⁡ϕ))\n

式中：f利用Greuell等和Reijmer等分别针对冰川冰和积雪提出的各向异性校正公式来计算，公式如下：\n

  冰川冰：fice=a0+a1×cos⁡θ+a2×θ2×cos⁡ϕ+a3×θ2×(cos⁡ϕ )2\n

  积雪：fsnow=b0+b1×θ2+b2×θ2×cos⁡ϕ+b3×θ2×(cos⁡ϕ )2\n

式中：ai和bi为回归系数；θ为卫星与太阳的相对天顶角；⁡ϕ为卫星与太阳的相对方位角。\n

  窄-宽波段转化：从Landsat窄波段计算短波宽带反照率主要依赖反射率和地面实测宽带反照率的关系，用如下线性关系进行转换：\nα=0.726×α2or3-0.322×α2or32-0.051×α4or5+0.581×α4or52\n

  由于积雪在可见光波段有很高的光谱反射率，因而该波段内积雪区的象元值经常达到饱和，即影像象元值达到最大，随着光谱反射率的增加不在增加。故当其（ETM+ 2或OLI 3）达到饱和时，用ETM+ 4或OLI 5的光谱反照率进行转换：\nα'=0.782×α4or5+0.148×α4or52", "ds_quality": "

  利用野外实测反照率数据对遥感反照率结果进行精度验证，数据比较准确，精度小于0.05。", "ds_acq_start_time": "2009-08-09 00:00:00", "ds_acq_end_time": "2019-08-13 00:00:00", "ds_acq_place": "阿尔泰山喀纳斯冰川", "ds_acq_lon_east": 87.86944444444444, "ds_acq_lat_south": 49.075, "ds_acq_lon_west": 87.73305555555555, "ds_acq_lat_north": 49.11666666666667, "ds_acq_alt_low": 2507.0, "ds_acq_alt_high": 4319.0, "ds_share_type": "apply-access", "ds_total_size": 394100044, "ds_files_count": 12, "ds_format": "tif", "ds_space_res": "30m", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "7a2557d6-e60f-41c5-8f7b-5aaa88286088.png", "ds_thumb_from": 2, "ds_ref_way": "岳晓英，阿尔泰山喀纳斯冰川消融期反照率空间分布数据集（2009-2019年），国家冰川冻土沙漠科学数据中心(www.ncdc.ac.cn)，2023，doi：10.12072/ncdc.nieer.db2880.2023", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "c6ac5c3c-eb4f-4119-86fb-c4534a9bd7fb", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "10.12072/ncdc.nieer.db2880.2023", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2023-06-19 10:16:13", "last_updated": "2023-06-21 11:54:01", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.NIEER.DB2880.2023", "i18n": { "en": { "title": "Surface Albedo data set on the Kanas Glacier during the Ablation Season in Altai Mountains (2009-2019)", "ds_format": "", "ds_source": "

\n
\n

  1. Landsat Land Satellite Image Data: From the US Geological Survey website（ https://www.usgs.gov/ ）And Geospatial Data Cloud（ http://www.gscloud.cn/ ）Download.\n

  2. Glacier Cataloging Data: China's Second Glacier Cataloging Data（ http://westdc.westgis.ac.cn ）And RGI 6.0（ https://www.glims.org/RGI/rgi60_dl.html )。\n

  3. ASTER GDEM V3 data: spatial resolution of 30 meters, download address https://lpdaac.usgs.gov/products/astgtmv003/ 。", "ds_quality": "

                                                                                                                                                                          <p>&emsp; The difference between the height of the snow line defined by manual visual interpretation and the height of the snow line extracted in this study is between 8-67 meters.\n
", "ds_ref_way": "", "ds_abstract": "
\n
\n

 & emsp; Satellite remote sensing instruments cannot directly measure the surface albedo, but the radiation from the earth system including the ground and atmosphere in a certain direction. It is necessary to preprocess the original remote sensing data and calculate the surface broadband albedo. This data set is based on Landsat data, mainly through radiometric calibration, atmospheric correction, topographic correction, BRDF correction and narrow to wide band conversion methods, to retrieve the spatial distribution data of surface albedo during the ablation period of Kanas Glacier. The accuracy of remote sensing albedo results is verified by using the field measured albedo data, and the accuracy is high. In general, the surface albedo of glaciers in the ablation period shows an increasing trend with the increase of altitude, with the fastest growth near the middle of the glacier.\n

 & emsp; The data format is tiff. The file name is the acquisition time of the original remote sensing image, for example, 20090809 represents the data obtained on August 9, 2009. The data is dimensionless between 0 and 1. The coordinate system is WGM84.

", "ds_time_res": "年", "ds_acq_place": "Kanas Glacier in Mount Taishan", "ds_space_res": "30m", "ds_projection": "", "ds_process_way": "
\n
\n

  1. Remote sensing data pre-processing: the glacier surface albedo is retrieved by radiometric calibration, atmospheric correction, topographic correction, BRDF correction and narrow to wide band conversion.\n

  2. Snow line height recognition: using the results of albedo retrieved from the DEM and remote sensing in the glacier area, calculate the albedo values and standard deviations of each altitude zone near the glacier midstream line (7 pixels near the midstream line, about 210m range) at 50m contour interval, and obtain the change curve of albedo along the midstream line with altitude. The point with the maximum standard deviation on the curve indicates that the difference of ice surface types in this altitude zone is the largest, which is the transition zone between snow covered area and bare ice area, and its albedo value is recorded as α 0 As the altitude increases, the area above this altitude zone becomes a snow covered area, while the area below is a bare ice area. Therefore, the α As the threshold for snow line extraction, 0 divides the glacier surface into snow covered areas and bare ice areas, with the lower boundary of the snow covered area being the snow line. However, the height of glacier snow lines may not necessarily be distributed regularly along contour lines, and it is likely to cross several contour lines. Here, based on contour lines extracted at 5m intervals, the nearest contour line or the average of the nearest contour lines is taken as the final snowline height.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [ "喀纳斯冰川", "消融期", "反照率", "Landsat" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "阿尔泰山" ], "ds_time_tags": [ 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019 ], "ds_contributors": [ { "true_name": "岳晓英", "email": "yuexiaoying@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_meta_authors": [ { "true_name": "岳晓英", "email": "yuexiaoying@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": "岳晓英", "email": "yuexiaoying@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": "冰川" }