EE 508 Data Science for Conservation Decisions

Contents

  • About this course
  • Schedule
  • Getting started
  • Labs
    • 1. Spatial data processing and visualization
    • 2. Systematic conservation planning with Marxan
    • 3. Optimal policy targeting with predictive machine learning
    • 4. Quasi-experimental impact evaluation with matching
  • Tests
  • Project
EE 508 Data Science for Conservation Decisions
  • Labs
  • View page source

Labs

Labs will appear here as the term progresses.

  • 1. Spatial data processing and visualization
    • 1.1. Countries and threatened species with QGIS
    • 1.2. Prior knowledge and interests of EE 508 students: pandas
    • 1.3. Countries and threatened species with geopandas
    • 1.4. Species priorities in Colombia: rasterio, numpy, and GDAL
    • 1.5. Spatial analytics exercise: ecosystem value mapping
  • 2. Systematic conservation planning with Marxan
    • 2.1. Getting to know Marxan: the case of Tasmania
    • 2.2. Building a Marxan analysis from scratch
    • 2.3. Improving the plan: cost proxy and planning units
  • 3. Optimal policy targeting with predictive machine learning
    • 3.1. Predicting land acquisition cost and forest change across Massachusetts
    • 3.2. Optimality of policy targeting: simulating incentives to avoid carbon loss
  • 4. Quasi-experimental impact evaluation with matching
    • 4.1. Estimating the effects of protected areas in the Amazon
Previous Next

© Copyright 2025, Christoph Nolte.

Built with Sphinx using a theme provided by Read the Docs.