A Python module for satellite image classification and land valuation
Project description
GeoClass - Land Classification and Valuation System
A Python module for satellite image classification and land valuation using machine learning.
Features
- Satellite image classification into different land categories
- Automated land scoring based on proximity to key features
- Real estate data scraping from major property websites
- Machine learning-based land price prediction
Installation
pip install -r requirements.txt
Project Structure
geoclass/
├── geoclass/
│ ├── satellite/ # Satellite image processing
│ ├── scoring/ # Land scoring system
│ ├── scraper/ # Web scraping modules
│ ├── ml/ # Machine learning models
│ └── utils/ # Helper functions
├── tests/ # Unit tests
└── examples/ # Usage examples
Usage
from geoclass.satellite import ImageClassifier
from geoclass.scoring import LandScorer
from geoclass.scraper import PropertyScraper
from geoclass.ml import PricePredictor
# Initialize components
classifier = ImageClassifier()
scorer = LandScorer()
scraper = PropertyScraper()
predictor = PricePredictor()
# Process satellite image
classified_image = classifier.classify("path/to/satellite_image.tif")
# Score land parcels
land_scores = scorer.score_land(classified_image)
# Scrape property data
property_data = scraper.scrape_properties(latitude, longitude)
# Predict land prices
predictions = predictor.predict(property_data, land_scores)
Development
To run tests:
pytest tests/
License
MIT License
Project details
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