Skip to content

kkumar555/Segment-fractional-built-up-map-to-seperate-high-built-up-regions

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Segment-fractional-built-up-map-to-seperate-high-built-up-regions

Author: Krishna Kumar Perikamana / https://www.researchgate.net/profile/Krishna-Kumar-Perikamana / 03.2022

I am intrested in Computer vision, Image processing and Machine learning. If you use my code or some form of it in published work, please cite my GitHub repository: If you use this code or some form of it in published work, please cite this repository: @misc{Fractional-Built-up-Prediction-10m, author = {Perikamana, K.K}, title = { Fractional-Built-up-Prediction-10m-from-Landsat-8-using-Random-Forest-Algorithm}, year = {2022}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url {https://github.com/kkumar555/Fractional-Built-up-Prediction-10m-from-Landsat-8-using-Random-Forest-Algorithm}} }

If you are interested on collaborating to do something interesting with this type of analysis...send me an email.

About this script: This script select the high built-up region from the exisiting fractional built map and make it into multiple segments. The segmentation is based on the neighbourhood characteristics extracted from the image. You may need to modify this code according to your requiremnts. This is just a sample code to illustrate the usefulness of fractional built-up map.

test

About

This script select the high built-up region from the fractional built map and make it into multiple segments

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages