Tracking 30 Year Of Water Change Detection & River Course Change Analysis using Google Earth Engine
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- Опубликовано: 17 сен 2024
- "Tracking 30 Years of Water Change Detection & River Course Change Analysis using Google Earth Engine"
Link: drive.google.c...
Welcome to my RUclips channel! In this video, I'll be taking you on a fascinating journey through three decades of environmental change, focusing on water bodies and the course of rivers. Using the powerful tools of Google Earth Engine, we'll dive deep into analyzing satellite imagery to track the transformation of the Indus River and detect changes in water bodies over the past 30 years.
Throughout this tutorial, I'll walk you through the step-by-step process of accessing and utilizing satellite imagery datasets, filtering them to isolate the relevant data, and performing advanced analysis techniques to visualize and interpret changes in water bodies and river courses. We'll explore how to identify areas of water expansion, contraction, and even alterations in the course of the river, providing valuable insights into environmental dynamics and land use patterns over time.
But wait, there's more! To access the code used in this analysis, I've provided a link to download the code archive. However, to unlock and access the code, you'll need to watch the full video, where I'll reveal the password required to extract the code. It's a fun and interactive way to engage with the material and ensure that you're fully equipped to replicate and adapt this analysis for your own projects.
So, if you're ready to embark on this exciting journey of environmental exploration and data analysis, be sure to hit play on the video, and let's uncover the secrets hidden within the satellite imagery of the Indus River basin together!
Don't forget to like, share, and subscribe for more insightful tutorials and data analysis adventures. See you in the video!
#Tracking30Years #IndusRiverChange: "Tracking 30 Years of Change in the Indus River: Satellite Imagery Analysis"
#RemoteSensing #LandscapeChanges: "From 1990 to 2020: Analyzing 3 Decades of Landscape Changes with Remote Sensing"
#GISJourney #IndusRiverEvolution: "Indus River Over Time: A GIS Journey Through 30 Years of Data"
#IndusRiverDiscovery #SatelliteStudy: "Discovering Pakistan's Indus River Evolution: 1990-2020"
#LandCoverChanges #RemoteSensingStudy: "Exploring Land Cover Changes Along the Indus River: A Remote Sensing Study"
#EnvironmentalMonitoring #IndusRiverBasin: "Monitoring Environmental Changes: A 30-Year Study of the Indus River Basin"
#GISAnalysis #LandUseDynamics: "GIS Analysis: Visualizing 30 Years of Land Use Dynamics in the Indus River Region"
#IndusRiverTransformation #TimeLapseAnalysis: "Unveiling the Indus River's Transformation: 1990-2020 Time-Lapse Analysis"
#PastToPresent #SatelliteDataStory: "From Past to Present: A Story of Indus River Changes Using Satellite Data"
#IndusRiverMapping #EnvironmentalChanges: "Indus River: Mapping Environmental Changes Over Three Decades"
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Great job mister. Amazing!
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!
You are amazing sir
TYSM 😇
Great sir ❤️❤️
TYSM 😇
Excellent video sir
TYSM 😇
Keep going ❤
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 !
May Allah make your knowledge wise
Amen JazakAllah
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
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
what is your emali? thanks
alihasnainnokia4@gmail.com
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 .