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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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