This project aims to analyze the patterns of urban growth and its impact on home prices using satellite images from 2015 to 2017. Utilizing data from Google Earth Engine, we gather monthly snapshots to observe and predict the trends in urbanization one year beyond the collected data. This study serves as a valuable tool for urban planners, economists, and policymakers.

• Google Earth Engine 🌐: Satellite images for the city of Tangier, Morocco collected monthly from January 2015 to May 2024.

Each image in the dataset captures:

• High-resolution geographical imagery of urban areas 🏙️
• Timestamps for temporal analysis ⏳

1. Data Acquisition: Collect monthly satellite images from Google Earth Engine.
2. Image Processing: Standardize and preprocess images for analysis.
3. Data Analysis: Employ statistical and machine learning techniques to identify patterns and predict future urbanization.
4. Visualization: Create visual representations of urban growth over the study period.

The project employs various predictive models to estimate urban growth trends a year after the last collected data. These models help in understanding potential impacts on home prices and urban planning.

The data will be made available upon request.

Clone this repository to your local machine using:

git clone [https://github.com/zgcharaf/Urbanization-Growth-Analysis-Using-Satellite-Imagery/]

• Python 3.8+
• Libraries: numpy, pandas, matplotlib, sklearn, tensorflow, rasterio

Install the required libraries using:

pip install -r requirements.txt

Provide instructions on how to run the scripts/modules:

python main.py

TBD

-Charaf ZGUIOUAR [[email protected]]

MIT Licence