Wildlife Conservation and Habitat Monitoring

Achieving Sustainable Development Goal 15 (SDG 15: Life on Land) relies on effective animal monitoring and habitat conservation. This study leverages big data and machine learning technologies like Apache Spark and PySpark MLlib to analyze species distribution and habitat suitability. Using the GBIF dataset, pre-processed for analysis, it applies a Decision Tree model for habitat classification and K-means clustering to group species by environmental conditions. This research supports wildlife conservation by identifying optimal areas for species preservation based on latitude and longitude. Tableau visualizations enhance decision-making, utilizing distributed processing for real-time monitoring.