Sentinel remote sensing image processing
Budget: $20 – $30 CAD
You will receive two Sentinel Surface Reflectance images for 2 years in the same area.
Each image has a size of around 200GB, so you should be able to:
1) Use python to handle such a BIG Data. Processing time is important.
2) Access such a big data via Python without downloading data to the local disk.
3) Create land cover image for each year using Random Forest unsupervised classification.
4) Create a separate image from land cover image (10 classes like urban, forest, agriculture fields, water), and save it as a GeoTiff image.
5) Calculate vegetation change only in Agriculture areas from a year to another year. Lest say NDVI.
Your Python code must be executable, well structured, well documented and indicate the runtime.
Project deadline is two days.
If you were a right candidate, I am willing to pay more and continue working with you.
Each image has a size of around 200GB, so you should be able to:
1) Use python to handle such a BIG Data. Processing time is important.
2) Access such a big data via Python without downloading data to the local disk.
3) Create land cover image for each year using Random Forest unsupervised classification.
4) Create a separate image from land cover image (10 classes like urban, forest, agriculture fields, water), and save it as a GeoTiff image.
5) Calculate vegetation change only in Agriculture areas from a year to another year. Lest say NDVI.
Your Python code must be executable, well structured, well documented and indicate the runtime.
Project deadline is two days.
If you were a right candidate, I am willing to pay more and continue working with you.