Thank you for this very interesting tutorial, and also thank you for considering our request to share the code. It really helps us a lot in our practice. I encourage you to keep up the exceptional work you're doing.
Thank you so much for your kind words and appreciation! I'm glad to hear that you found the tutorial helpful and that sharing the code has been beneficial for your practice. Your encouragement means a lot to me, and it motivates me to continue sharing valuable content. I'm committed to keeping up the exceptional work and providing valuable resources for the community. Thank you for your support and encouragement!
Inshallah, thank you very much for your kind words of encouragement and motivation! Your support means a lot as I strive to continuously improve and make a positive impact. Your words truly inspire me to keep shining and raising the bar. JazakAllah khair!
@adilos12345 Thank you for your suggestion! I'll explore incorporating surface water area calculations into future iterations of the analysis. Your feedback is greatly appreciated, and I'm committed to improving the depth and accuracy of our analysis.
@@KraivKris Yes, exactly. To calculate the surface water area over time, we can perform a classification using the Normalized Difference Water Index (NDWI) to identify water bodies in the satellite imagery. By setting a threshold on the NDWI values, we can classify pixels as water or non-water, thus estimating the surface water area. This approach allows us to track changes in surface water over the specified time period. Let me know if you need further clarification!
If the code is not identifying water bodies in your study area, it might be due to several reasons, including incorrect threshold values for NDWI, cloud cover, or differences in the spectral characteristics of water in your area compared to the default settings in the code. Here are some steps you can take to troubleshoot and improve the water body identification:Adjust NDWI Threshold,Check Cloud Cover,Refine Masking.
@@rajeshgm6294 Thank you for your interest! Yes, you can indeed monitor groundwater levels using satellite data. While the GLDAS dataset (ee.ImageCollection("NASA/GLDAS/V022/CLSM/G025/DA1D")) provides valuable information, it's important to note that its resolution is relatively coarse at 27830 meters. This may not be ideal for detailed analysis, especially in regions with complex hydrological dynamics. That is why I don't prefer it .
Thank you for this very interesting tutorial, and also thank you for considering our request to share the code. It really helps us a lot in our practice. I encourage you to keep up the exceptional work you're doing.
Thank you so much for your kind words and appreciation! I'm glad to hear that you found the tutorial helpful and that sharing the code has been beneficial for your practice. Your encouragement means a lot to me, and it motivates me to continue sharing valuable content. I'm committed to keeping up the exceptional work and providing valuable resources for the community. Thank you for your support and encouragement!
You are doing great job. Keep shining and raising
Inshallah, thank you very much for your kind words of encouragement and motivation! Your support means a lot as I strive to continuously improve and make a positive impact. Your words truly inspire me to keep shining and raising the bar. JazakAllah khair!
It will be better is the code can calculate the surface water area over time not just the NDWI mean values
Hi. How that can be made? You mean doing a classification?
@adilos12345 Thank you for your suggestion! I'll explore incorporating surface water area calculations into future iterations of the analysis. Your feedback is greatly appreciated, and I'm committed to improving the depth and accuracy of our analysis.
@@KraivKris Yes, exactly. To calculate the surface water area over time, we can perform a classification using the Normalized Difference Water Index (NDWI) to identify water bodies in the satellite imagery. By setting a threshold on the NDWI values, we can classify pixels as water or non-water, thus estimating the surface water area. This approach allows us to track changes in surface water over the specified time period. Let me know if you need further clarification!
@@geographerpakistani oh ok now I got It. Thank you !
Great job mister. Amazing!
Sinto muito pelos acontecimentos nos últimos tempos.
Deus o abençoe grandemente.
Thanks U2
Great sir ❤️❤️
TYSM 😇
i am unable to open the code.
it showing source file didnt exists.
Okay Drop Your Mail At alihasnainnokia4@gmail.com I will share code with you over there ..
how to make exported data into shp sir?
Simply Use ArcMap for this purpose
You are amazing sir
TYSM 😇
Excellent video sir
TYSM 😇
i performed the Code on my study area but ,mine cant identify the water body
If the code is not identifying water bodies in your study area, it might be due to several reasons, including incorrect threshold values for NDWI, cloud cover, or differences in the spectral characteristics of water in your area compared to the default settings in the code. Here are some steps you can take to troubleshoot and improve the water body identification:Adjust NDWI Threshold,Check Cloud Cover,Refine Masking.
@@geographerpakistani Ok thank you i will do that
Keep going ❤
May Allah make your knowledge wise
Amen JazakAllah
what is your emali? thanks
alihasnainnokia4@gmail.com
A helpful video. Can i get the code sir
It's in description
@@geographerpakistani when i opened it to extract, it required password sir
@@HuyaoBa-bg6ux watch complete video you will get it
sir ,kindly provide password for extracting file
It is in description i think
Watch Full Video Password is in Video
@@geographerpakistani thank you sir
sir, plz do tutorial on groundwater level monitoring using grace satellite data
@@rajeshgm6294 Thank you for your interest! Yes, you can indeed monitor groundwater levels using satellite data. While the GLDAS dataset (ee.ImageCollection("NASA/GLDAS/V022/CLSM/G025/DA1D")) provides valuable information, it's important to note that its resolution is relatively coarse at 27830 meters. This may not be ideal for detailed analysis, especially in regions with complex hydrological dynamics. That is why I don't prefer it .