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https://github.com/azad77/ml_geospatial_analysis

Tutorial code for geospatial analysis using machine learning techniques

https://github.com/azad77/ml_geospatial_analysis

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Repository

Tutorial code for geospatial analysis using machine learning techniques

Basic Info
  • Host: GitHub
  • Owner: Azad77
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 21.9 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created almost 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License

README.md

MLGeospatialAnalysis

Tutorial code for geospatial analysis using machine learning techniques

Project created by Dr. Azad Rasul
Email: azad.rasul@soran.edu.iq

Introduction

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.

Table of Contents

  1. Data Normalization and Feature Extraction
  2. Applying K-means Clustering
  3. Random Forest Classifier
  4. Building a CNN with Keras
  5. ARIMA Model for Time Series Forecasting
  6. Anomaly Detection with Isolation Forest
  7. Geospatial Data Manipulation with GeoPandas and Folium
  8. Geospatial Clustering with K-means
  9. Spatial Join with GeoPandas
  10. Kriging Interpolation
  11. Time-Series Geospatial Data
  12. Digital Elevation Model (DEM) Visualization
  13. Terrain Slope Calculation
  14. Terrain Aspect Calculation
  15. Edge Detection on Satellite Images
  16. LSTM Model for Time Series Prediction

Usage

  1. Clone this repository: bash git clone https://github.com/yourusername/yourrepository.git

  2. Install the required libraries: bash pip install numpy pandas scikit-learn matplotlib keras statsmodels geopandas folium pykrige rasterio scipy

  3. Navigate to the project directory: bash cd yourrepository

  4. Run the scripts according to your needs. Each script contains detailed comments and instructions.

Contributing

Feel free to contribute to this project by submitting pull requests or opening issues. Your contributions and feedback are welcome!

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use this repository in your research or projects, please cite it as follows:

@misc{rasul2024mlgeospatialanalysis, author = {Dr. Azad Rasul}, title = {MLGeospatialAnalysis: Tutorial code for geospatial analysis using machine learning techniques}, year = {2024}, url = https://github.com/Azad77/MLGespatialAnalysis

Owner

  • Name: Dr Azad Rasul
  • Login: Azad77
  • Kind: user
  • Company: Soran University

As a geographer, I use remote sensing and GIS methods and techniques to study LST, urban environment, earth observation and natural disasters.

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Dependencies

requirements.txt pypi
  • folium *
  • geopandas *
  • keras *
  • matplotlib *
  • numpy *
  • pandas *
  • pykrige *
  • rasterio *
  • scikit-learn >=0.20
  • scipy *
  • statsmodels *
  • tensorflow *