I am trying to super-resolve my Sentinel-2 images (rgb-10m) to 2.5m but my results do not come out well, what do you think the min max values of three bands of Sentinel-2 images should be so they can be ready for the analysis? Thanks for the video.
Very useful demonstration indeed, wondering if you would be able to show us the code for downloading multiple Sentinel and Landsat imagery using a single code
Thanks for your interest! Stay tuned. I will show you the process of downloading multiple images from multiple sensors and multiple locations in future video.
Hi for the model to detect deforestation, you need to prepare your training dataset first either by manual digitization work or by semi-automation way (NDVI etc). After that, train your model for the 1st year and predict for the next year (Here you need to take the same month dataset because fall season has less vegetation than in rainy season).
My work requires climate change scenario evaluation, for example correlating deforestation with population increase or infrastructure development. Can you help teach me?
I am trying to super-resolve my Sentinel-2 images (rgb-10m) to 2.5m but my results do not come out well, what do you think the min max values of three bands of Sentinel-2 images should be so they can be ready for the analysis? Thanks for the video.
I don't think your max, min range will be constant for all the images. The best way I can think up us using percentile clip (2% clip).
@@geodev thanks
Hey, very informative video.
can you suggest how to get satellite images for cyclone detection?
Very useful demonstration indeed, wondering if you would be able to show us the code for downloading multiple Sentinel and Landsat imagery using a single code
Thanks for your interest! Stay tuned. I will show you the process of downloading multiple images from multiple sensors and multiple locations in future video.
Hello, Thank you for your perfect videos. How we can create a Model for predicting deforestation from time series for the next years?
Hi for the model to detect deforestation, you need to prepare your training dataset first either by manual digitization work or by semi-automation way (NDVI etc). After that, train your model for the 1st year and predict for the next year (Here you need to take the same month dataset because fall season has less vegetation than in rainy season).
@@geodev Hi, how does this work, can you speak to me 1:1?
My work requires climate change scenario evaluation, for example correlating deforestation with population increase or infrastructure development. Can you help teach me?