地球科学进展 ›› 2018, Vol. 33 ›› Issue (4): 425 -434. doi: 10.11867/j.issn.1001-8166.2018.04.0425

研究简报 上一篇    下一篇

基于GF-4数据分析低分辨率卫星云检测尺度误差对下行辐射计算的影响
裔传祥 1, 2( ), 辛晓洲 2, 胡继超 1, 张海龙 2, 李小军 2, 龚围 3   
  1. 1.南京信息工程大学 应用气象学院,江苏 南京 210044
    2.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,北京 100101
    3.重庆师范大学,重庆 400047
  • 收稿日期:2017-10-09 修回日期:2018-02-10 出版日期:2018-04-20
  • 基金资助:
    *中国科学院重点部署项目“混合像元能量平衡遥感模型及其参数化方法研究”(编号:KZZD-EW-TZ-18);国家自然科学基金项目“卫星像元尺度地表能量平衡遥感算法研究”(编号:41371360)资助.

Analysis of Cloud Scale Error of Low Resolution Satellite Based on GF-4 and Its Influence on Downward Radiation Calculation

Chuanxiang Yi 1, 2( ), Xiaozhou Xin 2, Jichao Hu 1, Hailong Zhang 2, Xiaojun Li 2, Wei Gong 3   

  1. 1.School of Applied Meteorology,Nanjing University of Information Science & Technology,Nanjing 210044,China;
    2.State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100101,China
    3.Chongqing Normal University,Chongqing 400047,China
  • Received:2017-10-09 Revised:2018-02-10 Online:2018-04-20 Published:2018-05-24
  • About author:

    First author:Yi Chuanxiang(1992-), male, Yancheng City, Jiangsu Province, Master student. Research areas include application of meteorological.E-mail:18761808890@163.com

  • Supported by:
    Project supported by the Key Deployment Project of the Chinese Academy of Sciences “Study on the energy balance remote sensing model of mixed pixel and its parameterized method”(No.KZZD-EW-TZ-18);The National Natural Science Foundation of China “Research on remote sensing algorithm for surface energy balance of satellite pixel scale”(No.41371360).

为研究低分辨率气象卫星数据云检测的尺度误差及其给下行辐射计算带来的影响,利用高分辨率静止卫星GF-4数据进行云检测并进行误差分析。首先运用可见光通道阈值法和时间序列法,对GF-4数据进行云检测,以GF-4云检测结果为基准,分析Himawari-8和FY-2(FY-2G和FY-2E)云检测结果的误差。在研究区内FY-2G,FY-2E与Himawari-8云图能够将云和晴空较好的区分开,造成误差的主要原因是不同空间分辨率卫星所产生的尺度效应(云检测算法不同造成的差异在此不予讨论),误差大多发生在薄云以及碎云较多的区域,高分辨率数据能够较好地检测出碎云,而低分辨率数据则会产生误检、检等情况。在此基础上对下行短波辐射遥感计算的误差进行分析,发现像元中实际云量的误差会给下行辐射的估算带来明显误差,所选试验区瞬时下行辐射相对误差最大为-173.52%,日总下行短波辐射相对误差最大为-20.20%。研究结果表明,在碎云较多的区域,利用高分辨率静止卫星数据可以显著提高下行短波辐射的估算精度。

In order to study the scale error of low resolution meteorological satellite cloud detection and its impact on the calculation of downlink radiation, cloud detection using high resolution stationary satellite GF-4 data and error analysis were carried out. Firstly, the cloud detection of GF-4 data is carried out by using visible channel threshold method and time series method, and the error of cloud detection results of Himawari-8 and FY-2 (FY-2G, FY-2E) is analyzed based on the results of GF-4 cloud detection.In the study area, FY-2G, FY-2E and Himawari-8 cloud images could distinguish the clouds and clear sky. The main reason for the error was the scale effect produced by different spatial resolution satellites(the differences caused by cloud detection algorithms are not discussed here).Most of the errors occurred in the areas of thin clouds and broken clouds.High resolution data could detect broken clouds, while low resolution data lead to false and missed detection. On this basis, the error of remote sensing calculation of short wave radiation was analyzed,and it was found that the error of the actual cloud amount in the pixel would bring significant error to the estimation of the downward radiation.The relative error of the instantaneous downward radiation in the selected test area was -173.52%, and the maximum relative error of shortwave radiation was -20.20%.The results show that the high resolution stationary satellite data can significantly improve the estimation accuracy of the downlink shortwave radiation in the regions with more broken clouds.

中图分类号: 

表1 数据源统计表
Table 1 Data source statistics table
表1 数据源统计表
Table 1 Data source statistics table
图1 GF-4彩色合成图以及云检测结果图
(a)5,4,3波段合成图;(b)云检测结果
Fig.1 GF-4 color composite map and cloud detection result
(a)5, 4 and 3 band composite graph;(b)Cloud detection result
图1 GF-4彩色合成图以及云检测结果图
(a)5,4,3波段合成图;(b)云检测结果
Fig.1 GF-4 color composite map and cloud detection result
(a)5, 4 and 3 band composite graph;(b)Cloud detection result
图2 GF-4的5,4,3波段合成图(a,b,c)以及GF-4(d,e,f)、Himawari-8(g,h,i)和FY-2G(j,k,l)云图结果
第一列时间为2016年12月14日9:00;第二列时间为12:00;第三列为15:00
Fig.2 GF-4, 5, 4 and 3 band composite graphs (a, b, c), and GF-4 (d, e, f),Himawari-8 (g, h, i) and FY-2G (j, k, l) cloud picture results
The first column is at 9 o’clock in December 14, 2016; The second column is at 12 o’clock; The third is at 15 o’clock
图2 GF-4的5,4,3波段合成图(a,b,c)以及GF-4(d,e,f)、Himawari-8(g,h,i)和FY-2G(j,k,l)云图结果
第一列时间为2016年12月14日9:00;第二列时间为12:00;第三列为15:00
Fig.2 GF-4, 5, 4 and 3 band composite graphs (a, b, c), and GF-4 (d, e, f),Himawari-8 (g, h, i) and FY-2G (j, k, l) cloud picture results
The first column is at 9 o’clock in December 14, 2016; The second column is at 12 o’clock; The third is at 15 o’clock
图3 14日12点Himawari-8与FY-2G云检测误检示意图
蓝色为晴空像元误检,红色为云像元误检
Fig.3 At 14, 12 o’clock Himawari-8 and FY-2G schematic diagram of cloud detection error detection
The blue part is the clear sky pixel error detection,the red part is the cloud pixel error detection
图3 14日12点Himawari-8与FY-2G云检测误检示意图
蓝色为晴空像元误检,红色为云像元误检
Fig.3 At 14, 12 o’clock Himawari-8 and FY-2G schematic diagram of cloud detection error detection
The blue part is the clear sky pixel error detection,the red part is the cloud pixel error detection
图4 FY-2G,FY-2E,Himawari-8云像元对应GF-4云所占比例统计结果
Fig.4 FY-2G,FY-2E,Himawari-8 cloud pixels of cloud products statistical results corresponding to the GF-4 cloud
图4 FY-2G,FY-2E,Himawari-8云像元对应GF-4云所占比例统计结果
Fig.4 FY-2G,FY-2E,Himawari-8 cloud pixels of cloud products statistical results corresponding to the GF-4 cloud
表2 风云二号数据模拟下行短波辐射误差统计表
Table 2 Short wave radiation error statistics table for FY-2 data simulation
序号 时间 像元标志 实际云所占
比例/%
绝对误差
/(W/m2)
下行短波辐射
相对误差/%
一天相对误差
/%
1 9:00 91.56 -46.97 -10.51 1.32
10:30 100.00 490.67 153.07
12:00 82.70 -76.79 -22.00
13:30 99.16 -3.30 -0.97
15:00 100.00 0.00 0.00
16:30 32.00 -327.76 -39.34
2 9:00 98.70 -6.63 -1.50 -20.20
10:30 100.00 452.99 56.07
12:00 30.77 -285.02 -94.57
13:30 64.44 -178.82 -78.21
15:00 100.00 -0.00 0.00
16:30 8.65 -591.86 -173.52
3 9:00 54.16 -45.06 -5.17 -9.70
10:30 53.47 56.02 7.71
12:00 64.44 -38.04 -6.12
13:30 100.00 0.00 0.00
15:00 61.36 -126.90 -19.32
16:30 27.33 -251.82 -28.43
4 9:00 59.84 -65.18 -8.52 -8.70
10:30 97.59 161.06 20.51
12:00 46.85 -86.73 -16.39
13:30 64.12 -67.45 -12.61
15:00 23.22 -147.12 -22.14
16:30 20.07 -151.52 -19.21
5 9:00 36.11 12.12 1.33 -10.73
10:30 56.77 21.32 2.81
12:00 48.57 -20.50 -3.07
13:30 80.26 -50.51 -9.72
15:00 15.59 -230.01 -28.19
16:30 19.63 -225.85 -24.40
6 9:00 10.53 0.87 0.09 -3.62
10:30 80.97 7.53 0.97
12:00 1.10 -9.92 -1.46
13:30 21.13 -71.97 -11.42
15:00 46.59 -46.03 -5.99
16:30 29.77 -55.97 -6.24
7 9:00 0.81 -102.09 -19.54 -4.39
10:30 1.00 0.00 0.00
12:00 0.94 -26.37 -8.43
13:30 1.00 0.00 0.00
15:00 1.00 0.00 0.00
16:30 1.00 0.00 0.00
8 9:00 0.00 0.00 0.00 -14.76
10:30 0.05 0.97 0.12
12:00 0.23 -15.96 -2.40
13:30 0.27 -250.91 -65.37
15:00 1.00 0.00 0.00
16:30 0.04 -392.80 -68.34
表2 风云二号数据模拟下行短波辐射误差统计表
Table 2 Short wave radiation error statistics table for FY-2 data simulation
序号 时间 像元标志 实际云所占
比例/%
绝对误差
/(W/m2)
下行短波辐射
相对误差/%
一天相对误差
/%
1 9:00 91.56 -46.97 -10.51 1.32
10:30 100.00 490.67 153.07
12:00 82.70 -76.79 -22.00
13:30 99.16 -3.30 -0.97
15:00 100.00 0.00 0.00
16:30 32.00 -327.76 -39.34
2 9:00 98.70 -6.63 -1.50 -20.20
10:30 100.00 452.99 56.07
12:00 30.77 -285.02 -94.57
13:30 64.44 -178.82 -78.21
15:00 100.00 -0.00 0.00
16:30 8.65 -591.86 -173.52
3 9:00 54.16 -45.06 -5.17 -9.70
10:30 53.47 56.02 7.71
12:00 64.44 -38.04 -6.12
13:30 100.00 0.00 0.00
15:00 61.36 -126.90 -19.32
16:30 27.33 -251.82 -28.43
4 9:00 59.84 -65.18 -8.52 -8.70
10:30 97.59 161.06 20.51
12:00 46.85 -86.73 -16.39
13:30 64.12 -67.45 -12.61
15:00 23.22 -147.12 -22.14
16:30 20.07 -151.52 -19.21
5 9:00 36.11 12.12 1.33 -10.73
10:30 56.77 21.32 2.81
12:00 48.57 -20.50 -3.07
13:30 80.26 -50.51 -9.72
15:00 15.59 -230.01 -28.19
16:30 19.63 -225.85 -24.40
6 9:00 10.53 0.87 0.09 -3.62
10:30 80.97 7.53 0.97
12:00 1.10 -9.92 -1.46
13:30 21.13 -71.97 -11.42
15:00 46.59 -46.03 -5.99
16:30 29.77 -55.97 -6.24
7 9:00 0.81 -102.09 -19.54 -4.39
10:30 1.00 0.00 0.00
12:00 0.94 -26.37 -8.43
13:30 1.00 0.00 0.00
15:00 1.00 0.00 0.00
16:30 1.00 0.00 0.00
8 9:00 0.00 0.00 0.00 -14.76
10:30 0.05 0.97 0.12
12:00 0.23 -15.96 -2.40
13:30 0.27 -250.91 -65.37
15:00 1.00 0.00 0.00
16:30 0.04 -392.80 -68.34
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