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Hi, everyone, I’m Xiaopang who studies geography. It’s been a long time since I’ve seen you. I’ve been crippled by data preprocessing. Recently, I’m processing high-resolution 6 wide-format image (GF6-WFV) data in ENVI. During the period, there were some problems in the relevant data preprocessing. On the way to find a solution, I thought of using other software and methods to solve it. I found PIE-Basic 6.3 under Aerospace Hongtu. It turned out that I encountered many problems and shared them with you. Take a look, I hope it can be solved, and I will also make a note for my own study, hoping to grow up with everyone in the exchange of experience and learning. here is the image!
提示：这里的相关问题都是自己探索得到了，问了好多人（老师，航天宏图技术支持人员和ENVI技术支持等），走了好多弯路，与各位共勉，也谢谢那些帮助我的人, thank you all!
1. Raw data:
2. Raw data open:
In this section, you will find that when the data is opened, you can choose to open the (.TIL) file in the entire standard GF6-WFV, or you can open a separate (.TIF) file, both of which are possible.
2.1 Open the overall (.TIL) file
2.2 Open the overall (.TIF) file
3. Data splicing:
Select the output location, it is recommended to create a new folder, because a folder with the same name will appear after the splicing is completed
I did it myself before
3. Radiation calibration:
Radiometric calibration is to convert the recorded original DN value into the surface reflectance of the outer layer of the atmosphere (or called radiance value). When users need to calculate the spectral reflectance or spectral radiance of ground objects, or when they need to compare images acquired by different sensors at different times, they must convert the brightness gray value of the image into absolute radiance. This process is radiation target. Its purpose is to eliminate the error of the sensor itself and determine the accurate radiation value at the entrance of the sensor.
I have encountered such a problem when I was doing it myself before. The radiation calibration coefficient in ENVI will change. This is normal, and it will change every year, but GF6-WFV will happen in 2018, 2019, 2020, and 2021. Change, but in 2019 when reading ENVI, we don’t know. Anyway, it is different from the official one. I suspect that I have corrupted the data.
The specific problem is like this:
2019 read at ENVI
Calibration coefficient official website
So later, when doing calibration, I will take a look at this calibration coefficient.
3.1 The default calibration type is apparent reflectance/brightness temperature
result
3.2 Select the calibration type as apparent radiance
result
Comparison of Results under the Probe Tool - Water Body
Comparison of results under the probe tool - urban area
Comparison of results under the probe tool - vegetation
The help manual chooses the default effect, in this step
4. Atmospheric correction:
The atmospheric correction function of PIE-Basic software is based on the 6S atmospheric radiation transfer model. The 6S model assumes a cloudless atmosphere, taking into account the absorption of water vapor, CO2, O3 and O2, the scattering of molecules and aerosols, and the non-uniform ground and two-way reflectivity.
The FLAASH atmospheric correction method was used in ENVI before. Here, the 6S atmospheric correction method is used. It is an atmospheric correction algorithm generated by the classic radiation transfer model. Let’s verify it. At present, I feel that the FLAASH atmospheric correction method seems to be better. I’m not sure that many people haven’t thought about it. It still feels a little problematic.
The relevant parameter settings here are basically the same as those in ENVI, and the result is the same. The result is put directly, but the file name has changed, but the result is the same. One is the previous result, and the other is writing while writing a blog. I did it, in order to reduce errors, I did the final cropping.
The relevant settings are default, and you can also take a general look at ENVI, and make a reference 
##### Image feature statistics (spectral profile) results comparison - water body
Comparison of image feature statistics (spectral profile) results - urban areas 
##### Comparison of image feature statistics (spectral profile) results - vegetation
5. Orthorectification:
How to say, the image size is too large to avoid mistakes, there is no cropping, the process is rough, and the result is credible. Here, direct orthorectification has been done.
Result 
##### Image Feature Statistics (Spectral Profile) Results Comparison - Water Body 
##### Image Feature Statistics (Spectral Profile) Results Comparison - Urban 
##### Image Feature Statistics (Spectral Profile) Comparison of Results - Vegetation
6. Research area clipping:
How to say, to avoid mistakes, finally select the area near Yuqiao Reservoir to complete the area clipping, the process is relatively rough, the result is credible, here is the picture directly 
##### image feature statistics (spectral profile) results comparison - water body
Comparison of image feature statistics (spectral profile) results - architecture
Comparison of image feature statistics (spectral profile) results - vegetation
Seven, there are problems:
How to say, there are still some problems here, but you may not be able to see it here (the header file information lacks wavelength information and other related information), so finally open all the results in ENVI to see it quickly, and now I have also contacted technical support. Solving.
I didn't find this problem before
Later, some functions were missing, so the problem found when opening the process file in ENVI, the current solution is to find a way to edit and modify the header file information later
Comparison of Image Feature Statistics (Spectral Profile) Results——Water Body
Comparison of image feature statistics (spectral profile) results - architecture
Comparison of image feature statistics (spectral profile) results - vegetation
8. Summary:
At present, I can’t think of a good solution, so I’m powerless. Try to try it yourself. Thank you for sharing this matter with me. I hope you can ask more questions and leave more comments. Thank you for helping me too! Goodbye, I'm still that chubby guy who studies geography, see you next time!