Tutorial code for geospatial analysis using machine learning techniques
Project created by Dr. Azad Rasul
Email: azad.rasul@soran.edu.iq
This repository contains a collection of scripts demonstrating various applications and techniques in geospatial analysis, machine learning, and data processing. Each section provides code examples for different tasks, including data normalization, clustering, classification, and more.
- Data Normalization and Feature Extraction
- Applying K-means Clustering
- Random Forest Classifier
- Building a CNN with Keras
- ARIMA Model for Time Series Forecasting
- Anomaly Detection with Isolation Forest
- Geospatial Data Manipulation with GeoPandas and Folium
- Geospatial Clustering with K-means
- Spatial Join with GeoPandas
- Kriging Interpolation
- Time-Series Geospatial Data
- Digital Elevation Model (DEM) Visualization
- Terrain Slope Calculation
- Terrain Aspect Calculation
- Edge Detection on Satellite Images
- LSTM Model for Time Series Prediction
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Clone this repository:
git clone https://github.com/yourusername/yourrepository.git
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Install the required libraries:
pip install numpy pandas scikit-learn matplotlib keras statsmodels geopandas folium pykrige rasterio scipy
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Navigate to the project directory:
cd yourrepository
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Run the scripts according to your needs. Each script contains detailed comments and instructions.
Feel free to contribute to this project by submitting pull requests or opening issues. Your contributions and feedback are welcome!
This project is licensed under the MIT License - see the LICENSE file for details.
If you use this repository in your research or projects, please cite it as follows:
@misc{rasul2024ml_geospatial_analysis, author = {Dr. Azad Rasul}, title = {ML_Geospatial_Analysis: Tutorial code for geospatial analysis using machine learning techniques}, year = {2024}, url = https://github.com/Azad77/ML_Gespatial_Analysis