urban-change-google-25d - Updated environment and readme file for codebase of urban change classification

📦 What's included in this release? This repository contains the complete codebase developed for the study "Understanding Informal Settlement Transformation through Google's 2.5D Dataset and Street View-based Validation"

It includes:

• Google Earth Engine script to download building count, height, and presence bands from the Open Buildings 2.5D temporal dataset.
• Python jupyter notebooks for:
  • Preprocessing and mosaicking high-resolution tiles.
  • Zonal statistics of building metrics at grid level.
  • Change detection using building count and height differences
  • Classification into 8 urban change typologies.
  • Slum-level analysis and top-5 slum extraction.
  • Spatial zone-based comparison (slu, buffer, other city areas)
  • Environment file to replicate the python environment.

All scripts are modular and well-documented to support reproducibility and adaptation for other cities using Google's 2.5D dataset

- Jupyter Notebook
Published by saiga143 about 1 year ago

urban-change-google-25d - Initial release of codebase for urban change classification using Google 2.5D

📦 What's included in this release? This repository contains the complete codebase developed for the study "Understanding Informal Settlement Transformation through Google's 2.5D Dataset and Street View-based Validation"

It includes: - Google Earth Engine script to download building count, height, and presence bands from the Open Buildings 2.5D temporal dataset. - Python jupyter notebooks for: - Preprocessing and mosaicking high-resolution tiles. - Zonal statistics of building metrics at grid level. - Change detection using building count and height differences. - Classification into 8 urban change typologies. - Slum-level analysis and top-5 slum extraction. - Spatial zone-based comparison (slu, buffer, other city areas) - Environment file to replicate the python environment.

All scripts are modular and well-documented to support reproducibility and adaptation for other cities using Google's 2.5D dataset

- Jupyter Notebook
Published by saiga143 about 1 year ago