python 读取 modis hdf文件

最新推荐文章于 2024-10-31 11:53:01 发布

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最新推荐文章于 2024-10-31 11:53:01 发布

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分类专栏： python 文章标签： python 数据分析

原文链接：https://blog.youkuaiyun.com/dym755833564/article/details/78143038

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python 读取 modis hdf文件
数据分析


 
 
   
   
    
    
   
   
   
   
    
    
     
     from pyhdf.SD 
     
     import SD, SDC
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     import pprint
    
    
   
   

   
   
    
    
   
   
   
   
    
     
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     HDF_FILR_URL = 
     
     "E:\MyDownloads\MOD021KM.A2012156.0115.006.2014225090534.hdf"
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     file = SD(HDF_FILR_URL)
    
    
   
   

   
   
    
    
   
   
   
   
    
     
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     print(file.info())

输出(31, 58)，说明有31个科学数据集


 
 
   
   
    
    
   
   
   
   
    
    
     
     datasets_dic = file.datasets()
    
    
   
   

   
   
    
    
   
   
   
   
    
     
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     for idx,sds 
     
     in enumerate(datasets_dic.keys()):
    
    
   
   

   
   
    
    
   
   
   
   
    
        
     
     print（idx,sds）

输出数据集编号名称
0 Latitude

1 Longitude

2 EV_1KM_RefSB

3 EV_1KM_RefSB_Uncert_Indexes

4 EV_1KM_Emissive

5 EV_1KM_Emissive_Uncert_Indexes

6 EV_250_Aggr1km_RefSB

7 EV_250_Aggr1km_RefSB_Uncert_Indexes

8 EV_250_Aggr1km_RefSB_Samples_Used

9 EV_500_Aggr1km_RefSB

10 EV_500_Aggr1km_RefSB_Uncert_Indexes

11 EV_500_Aggr1km_RefSB_Samples_Used

12 Height

13 SensorZenith

14 SensorAzimuth

15 Range

16 SolarZenith

17 SolarAzimuth

18 gflags

19 EV_Band26

20 EV_Band26_Uncert_Indexes

21 Band_250M

22 Band_500M

23 Band_1KM_RefSB

24 Band_1KM_Emissive

25 Noise in Thermal Detectors

26 Change in relative responses of thermal detectors

27 DC Restore Change for Thermal Bands

28 DC Restore Change for Reflective 250m Bands

29 DC Restore Change for Reflective 500m Bands

30 DC Restore Change for Reflective 1km Bands

sds_obj = file.select(‘Latitude’) # select sds


 
 
   
   
    
    
   
   
   
   
    
    
     
     sds_obj = file.select(
     
     ‘cloud_top_temperature_1km’) 
     
     # select sds
    
    
   
   

   
   
    
    
   
   
   
   
    
     
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     data = sds_obj.get() 
     
     # get sds data
    
    
   
   

   
   
    
    
   
   
   
   
    
    
     
     print data

输出cloud_top_temperature_1km数据

[[19875 19720 19740 …, 19608 19591 19533]

[19473 19413 19272 …, 19431 19422 19420]

[19125 19335 18972 …, 19344 19475 19347]

…,

[18335 18240 18584 …, 12935 12819 12955]

[18437 18747 18843 …, 13152 13085 12855]

[18662 18858 18584 …, 13241 12866 12797]]

[[23891 24528 24340 …, 23878 23999 24114]

[23780 23818 24004 …, 23648 23735 23648]

[23934 24230 23675 …, 23861 23544 23839]

…,

[22585 22190 22585 …, 18565 18332 18656]

[22169 22499 22573 …, 18441 18818 18247]

[22313 22571 22719 …, 18555 18521 18443]]]

pprint.pprint(sds_obj.attributes())

输出数据性质

{'_FillValue': 65535,
'band_names': '20,21,22,23,24,25,27,28,29,30,31,32,33,34,35,36',
'long_name': 'Earth View 1KM Emissive Bands Scaled Integers',
'radiance_offsets': [2730.58349609375,
2730.58349609375,
2730.58349609375,
2730.58349609375,
1077.44482421875,
1560.3333740234375,
2730.583251953125,
2317.48828125,
2730.58349609375,
1560.333251953125,
1577.3397216796875,
1658.2213134765625,
2501.297607421875,
2501.297607421875,
2501.2978515625,
2501.2978515625],
'radiance_scales': [6.262398528633639e-05,
0.0031495101284235716,
6.921597378095612e-05,
7.910397835075855e-05,
3.155614103889093e-05,
5.639820665237494e-05,
0.00011755729792639613,
0.0001924497337313369,
0.000532486941665411,
0.0004063234373461455,
0.0008400219958275557,
0.000729697581846267,
0.00026226387126371264,
0.00020069582387804985,
0.0001767082721926272,
0.0001183385684271343],
'radiance_units': 'Watts/m^2/micrometer/steradian',
'units': 'none',
'valid_range': [0, 32767]}